Category Archives: Uncategorized

Brain Tumor Detection Based on Watershed Segmentation and Classification Using Deep Learning
Authors:- Shivam Tamrakar, Prof. Mahesh Prasad Parsai

Abstract- The computer-aided diagnostic-based that supports deep learning (DL) algorithms consists of several processing layers, which symbolize data with several stage of construct. In current years, the use of deep learning has increased speedily in almost all areas, especially in the field of medical imaging, medical image investigation or bioinformatics. Therefore, deep learning has effectively untouched or enhanced the methods of recognition, calculation or diagnosis in many medical and health areas such as pathology, brain tumors, lung cancer, stomach, heart or retina. Given wide application of deep learning, the purpose of this paper is to appraise the most important deep learning perception related to tumour analysis detection and classification In recent applications of pre-trained models, normally features are extracted from bottom layers which are different from natural images to medical image. To overcome this difficulty, in the proposed method GLCM feature and Resnet-50 techniques used for feature extraction and watershed based segmentation is used for brain tumour detection and its classification. A significant, practical deep learning model is proposed which uses back propagation neural network feature to predict brain stroke through CT/MRI scan images. The performance and accuracy of the proposed model is evaluated and compared with existing models and it produces high sensitivity, specificity, precision and accuracy.

Study of Factors Affecting to Behavioural Intention on Adopt Mobile Payment
Authors:- P.K.C. Adeesha Rathnasinghe

Abstract- This paper provides an analysis and evaluation of the factors that influence mobile payment adoption in Sri Lanka, as well as an examination of the customer-driven characteristics of mobile payment solutions and their associated value proposition. The convenience feature of mobile payment has replaced interactions with actual currency and shortened transaction times, which better satisfies the convenience needs of modern people. As mobile payments play a major part in mobile business, gaining an understanding of the characteristics that attract consumers to mobile payment will provide mobile businesses with additional chances for growth and substantially increase their output value. Based on the core theoretical framework of the Theory of Acceptance and Use of Technology, this study investigates how to further affect customer behavioural intention in Sri Lanka (UTAUT2). In this investigation, data analysis is conducted to validate the research model and hypotheses. Social influence, facilitating conditions, hedonic motivation, compatibility, innovation, relative benefit, complexity, performance expectations, and observability have been identified as dependent variables that influence customer desire to use mobile payment. One hundred eighty samples will be chosen using a random sampling technique for the investigation. Utilizing statistical analysis and regression analysis, the impact of these nine parameters on mobile payment adoption was confirmed. Perceived danger, perceived cost, perceived advantage, perceived ease of use, perceived usefulness, perceived behaviour, social influence, credibility, and compatibility have a major impact on mobile payment uptake, according to the results of a study.

Detection of Glaucoma by the Use of Convolutional Neural Network
Authors:- M.Tech. Scholar Pankaj Goud, Asst. Prof. Miss Priyanshu Dhameniya

Abstract- Glaucoma is a disease that affects human eyes and makes it difficult for people to see clearly. In recent years, the prevalence of this condition has increased significantly. The result of this illness is a permanent impairment of vision that cannot be reversed once it has taken place. In the past, the diagnosis of glaucoma was carried out with the assistance of a number of different deep learning (DL) algorithms. The results of our research on recognising glaucoma illness are presented in this journal. For the purpose of recognising the ailment, we used a deep learning model known as a Convolutional neural network (CNN). The convolutional neural network provides us with a distinct pattern for both eyes afflicted by glaucoma and eyes that are not impacted by glaucoma. This pattern may be used by us to diagnose glaucoma. When CNN is used, a hierarchical framework is provided for distinguishing between images of glaucoma-affected eyes and photographs of eyes that are not affected by glaucoma. This facilitates more accurate categorization. Using the method that we offer, it is possible to do a review in a total of six phases. The dropout mechanism is used in the study that is advised in order to improve the overall efficiency of the performance. This is done in the context of glaucoma disease detection. In order to carry out an analysis of the work that was intended, this study made use of the datasets provided by SCES and ORIGA. The values acquired for the ORIGA dataset come in at 92.3, while the SCES dataset has values that come in at 94.2.

Load Balancing in Cloud Computing Through Multiple Gateways
Authors:- Research Scholar Rani Danavath, Asst. Prof. Dr. V. B. Narsimha

Abstract- Cloud computing is a structured model that defines computing services, in which data as well as resources are retrieved from cloud service provider via internet through some well formed web-based tool and application. As the numbers of users are increasing on the cloud, the load balancing has become the challenge for the cloud provider. As most of the traffic is oriented towards the Internet and may not be distributed evenly among different IGWs, some IGWs may suffer from bottleneck problem. To solve the IGW bottleneck problem, we propose an efficient scheme to balance the load among different IGWs within a WMN Our proposed load-balancing scheme consists of two parts: a traffic load calculation module and a traffic load migration algorithm. The IGW can judge whether the congestion has occurred or will occur by using a linear smoothing forecasting method. When the IGW detects that the congestion has occurred or will occur, it will firstly select another available IGW that has the lightest traffic load as the secondary IGW and then inform some mesh routers (MPs) which have been selected by using the Knapsack Algorithm to change to the secondary IGW. The MPs can return to their primary IGW by using a regression algorithm.

Blockchain and Its Use in Financial World
Authors:- Lokesh Yadav

Abstract- A Blockchain Is Essentially A Digital Ledger That Is Replicated And Distributed Across A Networkof Computer Systems On The Blockchain. Each Block On The Chain Contains A Set Oftransactions, And Each Time A New Transaction Occurs On The Blockchain, A Record Of Thattransaction Is Added To Each Participant’s Ledger. A Distributed Database Managed By Multipleparticipants Is Called Distributed Ledger Technology (Dlt).

Control Strategy for Bidirectional AC-DC Interlinking Converter in AC-DC Hybrid Microgrid Using PV System
Authors:- Vikram Sirohi, Asst. Prof. Somya Agarwal, Dr. Raghavendra Patidar

Abstract- In this article, a single-stage bidirectional converter that is connected to the grid is suggested. This converter would have a power conversion stage and an unfolding circuit. The power conversion stage would be a two-way DC-DC converter. The goal of this research is to get the most energy out of photovoltaic (PV) energy systems as possible. When the temperature, the amount of sunlight, or the load changes, so does the maximum amount of power that the photovoltaic module can produce. The photovoltaic system uses a maximum power point tracker (MPPT) to keep getting the most power out of the solar panel and send it to the load. This is done so that the system is as efficient as possible. The Maximum Power Point Tracking (MPPT) system is made up of a controller and a DC-DC converter, which are its two main parts. The DC-DC converter is a piece of electronic equipment that changes the voltage of DC energy from one level to another. MPPT uses a tracking algorithm so that it can find the place with the most power and keep working there even when the weather changes. Many different algorithms for MPPT have been made and talked about in published research, but most of these methods have problems with how well they work, how precise they are, and how well they can be changed. Conventional controllers can’t give the best response because the PV module’s current-voltage characteristics don’t behave in a linear way and switching makes the DC-DC converter behave in a non-linear way. This is especially true when the line parameters and transients change in a lot of different ways. The goal of this work is to make a maximum power point tracker and then use it. This will be done by using fuzzy logic control algorithms. When fuzzy logic is used, it is natural that a good controller will be made for nonlinear applications. This method also uses techniques from artificial intelligence, which can make modeling nonlinear systems easier and offer other benefits. Simulink was used to build an MPPT system with solar modules, DC-DC converters, batteries, and fuzzy logic controllers, and to simulate it. This had to be done so that the job could be done well. Characterize the buck, boost, and buck-boost converters to find out which topology is best for the PV system being used. In MATLAB, a model of the PV module, the indicated converter, and the battery were all put together to get the experience needed to build and tune the fuzzy logic controller. The results of the simulation show what happens when the parameters are changed.

Energy Optimization of Underwater WSN by Wolf Based Clustering
Authors:- M.Tech. Scholar Kush Paliwal, Asst. Prof. Sumit Sharma

Abstract- Communication is basic need of any age, although medium and technique is different. In this era wireless communication is common and acceptance of this in various applications is also wide. Out of different field of WSN (Wireless Sensor Network), underwater is highly desirable as study of such area may give new material or learning. This paper has developed a model that works for underwater WSN optimization by clustering and routing. Clustering of nodes were done by Wolf optimization technique, algorithm is able to provide solution dynamic situation. Cluster nodes selection done on the basis of device energy, distance from the base station. Routing of packet is also done from the nodes by means of cluster centers. In order to reduce the load of cluster nodes, shuffling of nodes were done time to time. Experiment was done on different environment of underwater and varying number of nodes. Model was compared with existing technique of underwater WSN network optimization.

An Analytical Study Using Dynamic Analysis on Buildings With and Without Expansion Joints
Authors:- Ashutosh Dabral , Rashmi Sakalle

Abstract- Vibration is effectively dampened by expansion joints, which also serve to keep individual building components together while allowing for their natural movement in response to things like ground settlement and earthquakes. In addition to protecting against moisture and water damage, this facilitates the transportation of live cargo. Expansion joints may be used to completely separate many different construction components, including ceilings, floors, roofs, walls, and facades. Additionally, they may be set up wall to wall, ceiling to ceiling, roof to roof, or roof to wall. They’re versatile enough to do more than one thing at once. These connections separate a frame into individual segments with sufficient breadth to accommodate the building’s thermal expansion and contraction. This thesis presents an experimental software analysis on the expansion joint of a hospital building to find: Displacement, Bending moment, Shear force and Axial force. Two samples were designed on STAAD PRO and a comparative study was made to find the expansion joint design with better performance.

A Comprehensive and Novel Approach to Design of Carbon Reinforced Alloy Wheel with Material Selection
Authors:- Anurag Tiwari, Prof. G.R. Kesheorey

Abstract-Main objective is to selection of material, analyze the reason of failures of the rim. Mainly the cracks on the surface, bending due to impact loading. Vibration and the hold pressure of the tire can damage the rim. The damage such as rust, dents, etc. which results in increased vibration while running, loss of air pressure and even sometimes the complete structural failure. This can damage the rims which could result in failure of the Rim during running conditions. Changes can be made to a rim and visible damage could lead to greater damage which can’t be seen by naked eye, so a repaired rim will never be structurally sound as original rim. There are some more causes of failure, this project will discuss about these failures which can arise in rim. This project is all about the design, analysis and calculation of von-mises stresses and deflections with the help of CATIA and ANOVA method. The part which is under maximum stress as well as respective deformation value can be easily detected.

Mitigating Shear Failure of Flexurally Strengthened Reinforced Concrete Beams Using Carbon Fibre Reinforced Polymer
Authors:- Dr. Muhammad Ashiqur Rahman, Dr. A. B. M. Saiful Islam, Prof. Ir. Dr. Mohd Zamin Bin Jumaat

Abstract- Shear failure is sudden, brittle and catastrophic in nature, which starts without advance warning of any distress. Hence, ensuring shear failure will not happen in reinforced concrete (r.c.) beams must be given due consideration in design. Practically beams can be allowed to take more loads if they are flexurally strengthened. Premature shear failure will occur when the shear reinforcements present can no longer take the increased shear loads due to flexural strengthening. Hence, when a r.c. beam is flexurally strengthened, care must be taken to ensure it does not fail under premature shear. Eight beams were prepared and tested in this research. Technical Report -55 (TR-55) was used to design the carbon fibre reinforced polymer (CFRP) plate for flexural strengthening. According to TR-55, the design strain for flexural plate is 0.006 for preventing intermediate crack (IC) debonding. Experimental data showed that the flexural CFRP plate strain reached 0.0072 without IC debonding. The CFRP strips for shear strengthening were designed using ACI 440-2R, 2008 and fib TG 9.3 2001. The key parameter for designing shear was the effective strain of the CFRP shear strips. Experimentally, CFRP shear strips experienced strain about half of the designed value according to ACI 440-2R, 2008 and fib TG 9.3 2001. The internal stirrups and external CFRP shear strips had almost the same strain values before failure. Overall, the strengthened beam capacity was increased by 160% compared with the control unstrengthened beam by mitigating the shear failure using CFRP.

Energy Optimization of Underwater WSN by Wolf Based Clustering
Authors:- Kushagra Paliwal, Asst. Prof. Sumit Sharma

Abstract- Communication is basic need of any age, although medium and technique is different. In this era wireless communication is common and acceptance of this in various applications is also wide. Out of different field of WSN (Wireless Sensor Network), underwater is highly desirable as study of such area may give new material or learning. This paper has developed a model that works for underwater WSN optimization by clustering and routing. Clustering of nodes were done by Wolf optimization technique, algorithm is able to provide solution dynamic situation. Cluster nodes selection done on the basis of device energy, distance from the base station. Routing of packet is also done from the nodes by means of cluster centers. In order to reduce the load of cluster nodes, shuffling of nodes were done time to time. Experiment was done on different environment of underwater and varying number of nodes. Model was compared with existing technique of underwater WSN network optimization.

Grade Recommendation Using Privacy Preserving Mining and Genetic Algorithm
Authors:- M.Tech. Scholar Priyanka Vishwakarma, Asst. Prof. Sumit Sharma

Abstract- Data analysis depends on quality of input data but this increase chance of privacy break of organization or individual or community. So reverse mining process is applied that performs both the data privacy preserving and knowledge extraction. In order to improve education quality student data analysis is more sensitive and needs good set of features for prediction. This paper has proposed a model that extracts features from the different city schools and trains a model for grade prediction. Proposed model has not shared student data to any third party, instead of this random features selected by the genetic algorithm were used for the training of model. These features were taken in form of presence and absence of student activities. Experiment was done on real dataset of Maharashtra Districts School Students. Comparisons result shows that proposed model has improved the prediction accuracy by % as compared to similar models of privacy preserving.

Multi-modal medical image analysis using Wavelet Fusion
Authors:-M.Tech. Scholar Khurshed Akhtar, Prof .Deepak Mishra

Abstract-Techniques for pixel-level image fusion have been the most important for remote sensing data processing and analysis up until this point. Typically based on empirical or heuristic rules, feature based fusion techniques are utilized for this purpose. Multimodal transport image registration and fusion technologies play an important role in routine screening, screening, screening and evaluation of chronic disease radiotherapy, surgical and radiotherapy programmes. Multimedia media algorithms and tools have made great strides in supporting the reliability of clinical decisions on medical imaging and will continue to make great strides. Combining the two types of information and mixing the two images. Image aggregation methods include simple methods (e.g. pixels) and complex methods (such as wavelet transforms). The advantage of using wavelet manipulation is it has a large part of each image. Its main objective is to improve the understanding of medical images through the use of discrete wavelet transformation technology. DWT uses mainly consolidation rules involving average pixels. The discrete wavelet transformation was carried out using fusion techniques designed specifically for integrated medical images. The fusion performance is calculated based on PSNR, MSE and whole progression moment.

Review on Renewable Energy Based Electric Vehicles Charging Technology
Authors:- Kuldeep Gautam, HOD Ravi Hada

Abstract-Many different types of electric vehicle (EV) charging technologies are described in literature and implemented in practical applications. This paper presents an overview of the existing and proposed EV charging technologies in terms of converter topologies, power levels, power flow directions and charging control strategies. An overview of the main charging methods is presented as well, particularly the goal is to highlight an effective and fast charging technique for lithium ions batteries concerning prolonging cell cycle life and retaining high charging efficiency. Once presented the main important aspects of charging technologies and strategies, in the last part of this paper, through the use of genetic algorithm, the optimal size of the charging systems is estimated and, on the base of a sensitive analysis, the possible future trends in this field are finally valued.

Effect of Environmental Factors on the Performance of Savonious Wind Rotor
Authors:- Associate Prof. P. Venkateswara Rao

Abstract- Savonious rotors continue to interest research investigators in view of its many advantageous features. The simple design of the rotor enables the achievement of a low cost and compact wind power device, although its efficiency may not be comparable with other vertical axis machines such as Darraeus rotor. In low wind velocity zones, one can adapt these rotors with success. Different configurations of the Savonious rotor have been proposed to overcome some of the limitations of the earlier Savonious rotors, which have very low tip speed ratios. Design guidelines have been enunciated for the design of the rotors, based on experience with field-installed rotors. Although a few CFD investigations have been reported earlier on the flow analysis of Savonious rotors, there appears to be no serious attempt made for analysis of flow distribution in these rotors at rarified atmospheric conditions to enable a more realistic understanding of the rotor performance. The rarified atmospheric conditions result from the ambient temperature occurring as per seasonal variations. In the present paper, an attempt is made to carry out a detailed two-dimensional CFD analysis of the basic configuration of the Savonious wind rotor with eccentricity to assess the performance at different atmospheric conditions. A parametric analysis is carried out to understand the pressure and velocity distribution of the rotor. The commercially available Fluent has been used extensively in the present analysis.

Analysis of RQD-RMR-GSI Geo-Mechanical Parameters of the Lithology Exposed In the Portion NE-SE of the City of La Paz, B.C.S., Mexico
Authors:- Joel Hirales Rochin

Abstract- Since ancient times, natural rocks have been used to improve the quality of life of populations, as base materials for the construction of infrastructure works in structural elements, cladding materials, as well as aesthetic finishes.Rock mass classification systems are a global communication system for explorers, designers and builders that facilitate the characterization, classification and knowledge of the rock mass properties.The applied methodology was the geotechnical tool of the Geomechanical classification of Bieniawski RMR, RQD Classification, GSI, as well as with the support of GIS (ArcGIS) where data and field information were worked.The objective of this study is to carry out a geo-mechanical characterization of different lithological zones of the city of La Paz, Baja California Sur., Mexico in its NE-SE portion.Geologically, the study area is based on Holocene deposits that correspond to alluvial material and outcrops of volcanic and volcanoclastic rocks (sandstones, volcanoclastic conglomerates, rhyolitic tuffs, andesitic lahars and lava flows) that are part of the Comondu Formation with an age between 30 and 12 Ma. The information will be the basis of a future comprehensive study to determine the quality indices with geotechnical parameters of the outcropping rocky massif and will allow a sustainable urban development of the improvement of the current construction regulations in the excavation and support criteria.

A Review of Load Balancing Technique in Cloud Computing
Authors:- M.Tech. Scholar Ms. Aarti Jaiswal, Assistant Professor Ms.Trapti Sharma

Abstract- Cloud registering shares information and give numerous assets to clients. Clients pay just for those assets as much they utilized. Cloud computing stores the information and disseminated assets in the open condition. The measure of information stockpiling increments rapidly in open condition. Along these lines, stack adjusting is a primary test in cloud condition. Load adjusting is dispersed the dynamic workload over various hubs to guarantee that no single hub is over-burden. It helps in legitimate usage of assets .It additionally enhance the execution of the framework. Many existing calculations give stack adjusting and better asset use. There are different composes stack are conceivable in Cloud computing like memory, CPU and system stack. Load adjusting is the way toward finding over-burden hubs and after that exchanging the additional heap to different hubs.

Robotic Patient Monitoring and Medicine Delivery
Authors:- Syed Mohammed Ali, Mohd Abdul Sattar, Shanila Mahreen

Abstract- In this project, I propose a robot with some functionality of providing medicine as well as to measure the vital parameters (Heart rate,Blood Pressure, Temperature) of the patient. We can attain the locomotion procedure of the robot using the principle of Radio-frequency identification (RFID) that automatically identifies and tracks tags attached to the objects. The movement and finding the path to patient location is done through a line follower and with RFID tag. Line following method is used to identify the path with help of two infrared sensors. The robot will move towards the patient’s room by following a non-reflective line and use RFID cards to identify the patient’s room number. Using the Medicine box, the medicine delivery is made possible to the patients. Relevant box will be open based on the RFID reader. All the measured parameters will be stored to the cloud using the application of the Internet of Thinking (IOT).If the read values varied from threshold, then an alert message will be sent to doctors through GSM Module.

Development of a Microcontroller-Based Water Fountain Control System
Authors:- Engr. Lyndon R. Bermoy, Vendy Von P. Salvan

Abstract- Entertainments are designed to attract or entice individuals. In some cities in the Philippines, there are only a few entertainment venues, making it difficult to attract people’s attention. The introduction of a new form of entertainment, such as a water fountain, can be a positive factor in the tourism industry’s expansion. The opportunity to observe water spurts of varying quantity and velocity at rhythmic intervals may reduce fatigue and aid in relaxation. People, especially children, would prefer the Water Fountain Show as a form of recreation and enjoyment, given that the Water Fountain is unlike any other form of entertainment available in the Philippines. This study’s sole objective is to design and develop an MCU-Based Water Fountain Control System. The system includes a control circuit that regulates the quantity of water released in a tube based on the pressure applied, thereby producing a sequence of water combinations. The project will feature a variety of lighting effects with corresponding colors and music that will make the overall display more colorful and enjoyable.

Performance Analysis of PID Controller for an Automatic Voltage Regulator System Using Simplified Particle Swarm Optimization
Authors:- Saleha, Vinay Pathak

Abstract- This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminates the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of50% to50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population-based optimization algorithms.The tuning performance of this algorithm and its contribution to the robustness of the control system are also extensively and comparatively investigated. In the performance analysis, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm are used for the purpose of comparison. These analyses are realized by benefiting from different analysis methods such as transient response analysis, root locus analysis, bode analysis and statistically Receiver Operating Characteristic (ROC) analysis. Afterwards, the robustness analysis is applied to the AVR system, which is tuned by ABC algorithm in order to determine its response to changes in the system parameters. At the end of the study, it is shown that the ABC algorithm is successfully applied to the AVR system for improving the performance of the controller and shows a better tuning capability than the other similar population-based optimization algorithms for this control application.To solve these control problems, which are explained above, an Automatic Voltage Regulator (AVR) system is applied to power generation units. The AVR system is a closed loop control system that provides terminal voltage at the desired value. The configuration of this control system will be investigated.

A Review of 5G Architecture with Emphases on Security, Energy and wide Applications
Authors:- Riya Sharma, Professor Dr. Pramod Sharma

Abstract- The eventual goal of the forthcoming 5G wireless networking is to have relatively fast data speeds, incredibly low latency, substantial rises in base station’s efficiency and major changes in expected Quality of Service (QoS) for customers relative to the existing 4G LTE networks. In order to deal with state-of-the art technologies and connectivity in the form of smart cell phones, internet of things (IoT) devices, autonomous vehicles, virtual reality devices and smart homes connectivity, the broadband data use has risen at a fast rate. Further, to meet the latest applications, the bandwidth of the system needs to be increased widely. This development will be accomplished by using a modern spectrum with higher data levels. In particular, the fifth generation (5G) mobile network seeks to resolve the shortcomings of previous telecommunication technologies and to be a possible primary enabler for future IoT applications. This paper briefly discusses the architecture of 5G, following by the security associated with the 5G network, 5G as an energy efficient network, various types of efficient antennas developed for 5G and state of-the-art specifications for IoT applications along with their related communication technologies. We have also outlined the broader usage of 5G and its future impacts on our lives. Furthermore, at the end of each subtopic, the necessary recommendations are given for the future work.

A Review on Collapse Behaviour of Cable Stayed Bridge
Authors:- M. Tech. Scholar Masoud Ahmed Khan, Asst. Prof. Dhanesh Khalotia

Abstract- Cable stayed bridges have good stability, ultimate use of structural materials, aesthetic, tremendously low design and protection costs, and efficient structural traits. Therefore, this kind of bridges are becoming more and more famous and are generally preferred for lengthy span crossings as compared to suspension bridges. A cable-stayed bridge includes more than one tower with cables helping the bridge deck. In phrases of cable arrangements, the most not unusual forms of cable stayed bridges are fan, harp, and semi fan bridges. Because of their big length and nonlinear structural behaviour, the analysis of those kinds of bridges is greater complex than conventional bridges. However in these bridges, the cables are the principle supply of nonlinearity. An optimal design of a cable-stayed bridge with minimum cost with reaching power and serviceability necessities is a challenging project. Therefore a review on collapse behaviour of cable stayed bridge has been done.

Implementation and Utilization of Deep Learning Approach in the Medical Field
Authors:- Research Scholar Vishal Acharya, Associate Prof. & HOD. Dr. Bharti Chourasia

Abstract- The COVID-19 epidemic has brought about an unusually terrible circumstance for the entire planet, terrifyingly stopping life as we know it and taking thousands of lives. Due to the expansion of COVID-19 to 212 countries and territories, as well as the rise in infection cases and fatalities. The public health system continues to be seriously threatened. The deep learning strategy for predicting the severity of the decline in COVID-19-infected patients was proposed in this research and is based on CNN. The suggested model may learn complicated connections between a variety of heterogeneous parameters using this new methodology, including census data, intra-county movement, inter-county mobility, data on social distance, previous infection growth, and more. According to the simulated results, total accuracy is 23.85% higher than prior work, and classification error is 32.86% lower than prior methodology. The prior method yielded precision values of 6.29%, recall values of 78%, and f-measure values of 36.01%. The simulation results demonstrate that the overall enhancement of performance parameters is superior to the current method.

Digital Image Watermarking by Select ed Feature of Group Search Genetic Algorithm
Authors:- Dilesh Khairwar, Asst. Prof. Sumit Sharma

Abstract- Image is a proof of any instant happened in the universe. Transformation of image from hard to digital brings different flexibility and uses for the analysis and storage. Digital images need security from the intruder for that many communication protocols were developed. For the validity of authentic source watermarking plays an important role. This paper has proposed a model that embedded watermark into the original image by extracting DWT feature from the image. For embedding at Least significant coefficient proposed model has uses Group Search genetic algorithm. Food sources cloning and mutation steps has reduces the iteration count that decreases the embedding process time as well. Experiment was done on real and standard digital images. Result shows that proposed model has maintained the PSNR value of image even after embedding.

A Study on Various Continuous Functions
Authors:- Mrs. K.Kiruthika, Dr. N.Nagaveni

Abstract- In this paper, we present and study a new concepts namely strongly rb-continuous and Perfectly rb-continuous, Contra rb-continuous and Totally rb-continuous. Also examine some of their properties of such functions.

Review on Milli Meter-Wave (mmW) Imaging for Humans Bio-field
Authors:- Mangukiya Hitesh Kumar Bhupatbhai

Abstract- Increasing demands for screening personnel for concealed objects lead to additional research efforts related to suitableimaging systems and their industrial realization. In this context millimeter-wave systems are a promising approach, because the radiation does not present a health hazard to people under surveillance and readily passes through manyoptically opaque materials such as clothing fabrics allowing for the identification of concealed objects. Due to theextent of the human’s body and the resultant required amount of 3D resolution cells with a magnitude of 15mm orless, in principle all existing and proposed systems have to deal with a huge amount of scattering data which have tobe acquired and processed. For a highly resolved image principally as much information as available should be used. Interestingly electromagnetic field is associated with such activities. Psychological perception of one’s environment or a person’sthought process induces characteristic electrical impulses in the brain. These signals travel throughout the central, sympathetic and parasympathetic nervous system, creating the unique electromagnetic field of the organism that can radiate out of the body and is termed ‘Aura’ or ‘Bio-energyfield’. Thus, ‘aura’ gives the signature of the statusof health prior to its manifestation in the physical body.Therefore, human health can be effectively monitored bymeasuring this radiation field.

A Literature Review on Brain Tumor Detection and Segmentation
Authors:- Mithilesh Nandini Malviya , Asst. Prof. Ms. Priya Sen

Abstract- A Brain Tumor is essentially a malformed cell growth that can be cancerous and non-cancerous. The tumor in the Brain is the most dangerous disease and can be diagnosed easily and reliably with the help of detection of the tumor with automated techniques on MRI Images. Several methods of efficient diagnosis and segmentation of brain tumors have been suggested by many researchers for effective tumor detection. Magnetic Resonance Imaging (MRI) images are used by specialists and neurosurgeons for the diagnosis of brain tumors. The accuracy depends on the experience and domain knowledge of these experts, and is also a time consuming and expensive process. To overcome these restrictions, several deep learning algorithms have been proposed for the detection of presence of brain tumors. In this review paper, an extensive and exhaustive guide to the sub-field of Brain Tumor Detection, focusing primarily on its segmentation and classification, has been presented by comparing and summarizing the latest research work done in this domain. For that purpose, it is proposed to review the detection of brain tumor from MRI images by using hybrid computerized approaches. Therefore, brain tumor growth performance and analysis are described to generalize symptoms and guide diagnosis towards a treatment plan. Several approaches for the segmentation process of MRI are discussed from existing papers, the detection of brain tumors can be conclude.

Review on Milli Meter-Wave (mmW) Imaging for Humans Bio-field
Authors:- Mangukiya Hitesh Kumar Bhupatbhai

Abstract- Increasing demands for screening personnel for concealed objects lead to additional research efforts related to suitableimaging systems and their industrial realization. In this context millimeter-wave systems are a promising approach, because the radiation does not present a health hazard to people under surveillance and readily passes through manyoptically opaque materials such as clothing fabrics allowing for the identification of concealed objects. Due to theextent of the human’s body and the resultant required amount of 3D resolution cells with a magnitude of 15mm orless, in principle all existing and proposed systems have to deal with a huge amount of scattering data which have tobe acquired and processed. For a highly resolved image principally as much information as available should be used. Interestingly electromagnetic field is associated with such activities. Psychological perception of one’s environment or a person’sthought process induces characteristic electrical impulses in the brain. These signals travel throughout the central, sympathetic and parasympathetic nervous system, creating the unique electromagnetic field of the organism that can radiate out of the body and is termed ‘Aura’ or ‘Bio-energyfield’. Thus, ‘aura’ gives the signature of the statusof health prior to its manifestation in the physical body.Therefore, human health can be effectively monitored bymeasuring this radiation field.

Review on Robotic Arm Component and Functions
Authors:- M.Tech. Student Siddharth Jaiswal, Asst. Prof. Kriti Srivastava , Asst. Prof. Shweta Mishra

Abstract- Robots are used in a variety of production processes, including monitoring processes, doing pick-and-place tasks, and even carrying out remote surgical procedures. The robotic arm manipulator must be able to perform a variety of duties depending on the application. The robots are designed to carry out responsibilities that need all 6 degrees of freedom (DOF). The present study conducts a literature review on previous studies that have been done on the design, materials, and operation of robots. Studies that have already been conducted have focused on the use of VLSI systems, mechanical systems, and image processing to the operation of robots. Various researchers have also presented their work on the inclusion of new approaches based on artificial intelligence with the goal of boosting the functioning and decision-making capabilities of robots.

A Review on Solar Wind Hybrid Renewable Energy System
Authors:- Twinkle Kumara ,Prof. Neeti Dugaya, Dr. Geetam Richhariya, Dr. Manju Gupta

Abstract- Renewable Energy System comprising of solar and wind energy, is eco-friendly, and cost-effective option for powering the rural areas compared to conventional sources. The drawback of these systems is they are less reliable as the generated power depends on meteorological conditions. A properly designed hybrid renewable energy system (HRES) that combines two or more renewable energy sources like wind turbine and solar system with battery back-up increases the reliability of these systems in standalone modeThis Paper provides a succinct and well-organized overview of different maximum power point tracking (MPPT) algorithms used in photovoltaic (PV) generating systems that may operate in partial shade. To far, a broad range of algorithms, PV modelling methods, PV array designs, and controller topologies have been investigated. However, every method has both benefits and drawbacks; as a consequence, while building a PV generating system (PGS) under partial shade conditions, a thorough literature study is required. The thorough review of MPPT algorithms has been done in this article. The review of MPPT methods has been divided into four major categories. The first group consists of entirely new MPPT optimization algorithms, the second group consists of hybrid MPPT algorithms, the third group consists of novel modelling approaches, and the fourth group consists of different converter topologies. This article offers an accessible reference for doing large-scale research in PV systems under partial shadowing conditions in the near future..

The Covid-19 And Its Impact on Insurance Participation in Indonesia: A Case Study of BPJS Ketenagakerjaan
Authors:- Andri Afrianto, Tony Irawan, Alla Asmara

Abstract-The COVID-19 virus has become a worldwide pandemic, and studies of its impact on insurance are needed. The research is specifically about insurance participants, especially during the pandemic, to ensure the survival of insurance in the long term. However, research linking COVID-19 and insurance is lacking. This paper aims to look at the impact of the COVID-19 pandemic on insurance by using active membership data from BPJS Ketenagakerjaan in Indonesia, which covers 34 provinces. This study uses a time series spanning 2018 to 2021 and across 11 regional offices of BPJS Ketenagakerjaan. Empirical findings suggest that COVID-19 cases are associated with reduced insurance participation. Compared to before the pandemic, COVID-19 caused a decrease in active participation by an average of 0.0577709 per cent. Active participation tends to increase yearly, but in 2020, there was a decline. Based on the results of this study, BPJS Ketenagakerjaan must reduce the risk of future pandemics by maximizing digital transformation in its business services to provide excellent service to formal and informal workers, as well as strengthening collaboration with the government in designing fiscal policies such as relaxation of contributions and direct cash transfers. While for companies, they can transfer socio -economic risks that can occur to their employees by buying insurance such as BPJS Ketenagakerjaan insurance.

Generating Transmitting Codes for MIMO Radar Using Polyphase Codes to Reduce Side-lobe Levels
Authors:- Manzoor Ahmad Wani, Shaveta Bala

Abstract-High side-lobe levels reduction is an exhausting task in Multiple- Input Multiple-Output (MIMO) radar. Transmit sequence design plays a significant role in radar to overwhelm correlation side-lobe levels. In general, side-lobe levels performance of the incoming signals is observed by their cross-correlation function with other transmitted signals. New polyphase codes are projected that shows good auto-correlation and cross-correlation function responses to reduce peak side-lobe levels (PSL) and cross-correlation levels (CCL). Performances of the various poly phase codes are compared and the P4 code is chosen for the design of new poly phase code. The proposed composite poly phase codes (CPC) are produced by adding the left and right shifted versions of P4 code asP4 code is much Doppler accepting to another polyphase codes. Using ambiguity function, the influence of CPC on the delay-Doppler plane is observed. Finally, simulation results validate superiority of the proposed CPC equated to the counterpart techniques.

Pulse Compression Radar Waveform Design Using Classical Orthogonal Polynomials to Mitigate Range Side-Lobes
Authors:- Aamir Hussain Khan, Shaveta Bala

Abstract- Transmitting waveforms plays a significant role in radar system. The benefits of both long and short duration pulses are achieved using pulse compression technique. Radar waveforms performance is observed using matched filter response. Practically, the matched filter response consists of higher range side-lobes which creates accurate detection problem. On the other side, wider bandwidth is much desirable for a better range resolution. Therefore, waveforms are to be designed in such a way that offers mitigation in matched filter side-lobes having wider bandwidth. Using classical orthogonal polynomials, new radar waveforms are designed for transmission purposes. We observed the performance of different order polynomials and finally, choose that polynomial which offers wider bandwidth and significant side-lobes reduction in pulse compression radar. The designed waveform performances are compared with the existing linear frequency modulated (LFM) waveforms.

Machine Learning Algorithm Based Health Care Monitoring System
Authors:- M.Tech. Scholar Sonal Shrivastava , Prof. Rajesh Kumar Boghey

Abstract- The regular measurement of vital signs enables early diagnosis and warning of developing problems. Furthermore, it allows closer monitoring of the effects of medication and lifestyle, making more personalized treatment plans possible. The system contains a patient loop interacting directly with the patient to support the daily treatment. It shows the health development, including treatment adherence and effectiveness. An educated and motivated patient can improve his/her treatment compliance and health. The system also contains a professional loop involving medical professionals (e.g. alerting to revisit the care plan). The patient loop is securely connected with hospital information systems, to ensure optimal personalized care. Big data analytics provides services to various organizations, especially in the healthcare field. The medical field contains a large amount of data and is well suited for data analysis. Medical big data is mainly used for clinical data, and chronic disease monitoring and health monitoring are mainly used to detect changes in patients’ health. First, you must process the data to remove unnecessary data and provide effective prediction results. The second is the data analysis process – this is the process of cleaning, transforming and modeling data for the purpose of discovering useful information. In this process, we propose privacy protection to keep patient information secure. And support vector Machine learning algorithms are mainly used to predict diseases and provide more efficient prediction results. Finally, our system will predict the disease based on the patient’s symptoms and show the treatment to the patient.

Conditions Total Factor Productivity (TFP), Competitiveness, Democracy and Oligarchy in ASEAN
Authors:- Maulin Kusuma Wardani, Didin S. Damanhuri, Widyastutik

Abstract- The purpose of this study is to analyze the condition of Total Factor Productivity (TFP), competitiveness, democracy and oligarchy in ASEAN. This study uses secondary data sources in the period 2010-2019 and five (5) selected countries, namely Indonesia, Malaysia, the Philippines, Thailand and Singapore. The TFP variable is measured by TFP Growth, competitiveness is measured by The Global Competitiveness Index, the level of democracy is measured by the Democracy Index and oligarchy is measured by calculating the Material Power Index. The results of the descriptive qualitative analysis method show the differences in the conditions of each country in terms of TFP, competitiveness, democracy and oligarchy even though they are in the same region.

Review Of Pv Generation And Power Transmission Analysis Using Power Flow Controllers
Authors:- Dipak Borse, Assistant Professor Lovkesh Patidar

Abstract- Energy security is one of the most crucial factor in the development of any nation. Inter-Connections among different power system networks are made to lower the overall price of power generation as well as enhance the reliability and the security of electric power supply. Different types of interconnection technologies are employed, such as AC interconnections, DC interconnections, synchronous interconnections, and asynchronous interconnections. It is necessary to control the power flow between the interconnected electric power networks. The power flow controllers are used to (i) enhance the operational flexibility and controllability of the electric power system networks, (ii) improve the system stability and (iii) accomplish better utilization of existing power transmission systems. These controllers can be built using power electronic devices, electromechanical devices or the hybrid of these devices. In this paper, control techniques for power system networks are discussed. It includes both centralized and decentralized control techniques for power system networks.

Power System Transient Analysis For Wind And Solar Based Hybrid System
Authors:- Garima Jain, Prof. Rajeev Chouhan

Abstract- Energy is critical to the economic growth and social development of any country. Indigenous energy resources need to be developed to the optimum level to minimize dependence on imported fuels, subject to resolving economic, environmental and social constraints. This led to an increase in research and development as well as investments in the renewable energy industry in search of ways to meet the energy demand and to reduce the dependency on fossil fuels. Wind and solar energy are becoming popular owing to the abundance, availability and ease of harnessing the energy for electrical power generation. This paper focuses on an integrated hybrid renewable energy system consisting of wind and solar energies. Many parts of Libya have the potential for the development of economic power generation, so maps locations were used to identify where both wind and solar potentials are high. The focal point of this paper is to describe and evaluate a wind-solar hybrid power generation system for a selected location. Grid-tied power generation systems make use of solar PV or wind turbines to produce electricity and supply the load by connecting to the grid.

Internal Factor of Return-To-Work (RTW) Program for Work Injured Laborer in Indonesia
Authors:- Dwi Aprianto, Dedi Budiman Hakim, Sahara

Abstract- Workplace accidents can define the level of safety in the workplace, which helps to drive national economic development. Annual GDP losses from occupational injuries are projected to be 3.94%. There were 374 million non-fatal work accidents worldwide, and 2.78 million individuals died as a result of work injuries. With 1.1 million fatalities, the Asia Pacific area has the greatest rate of occupational injury compared to other regions globally. South-East Asia generates the most work injuries to this area. Indonesia had the highest number of fatal injuries, with 15.973 fatal accidents per 100,000 employees (20.9%). It is critical to revive work-injured individuals in order for them to be productive. The purpose of this study is to identified the internal factors that determine the the RTW Program for workers who have been injured on the job. Data were acquired from BPJS Ketenagakerjaan from 2020 to 2021, with 195 people participating in this program as a result of fatal workplace injuries. This is cross-sectional research. As a consequence, 75.90% of participants were able to work after completing this program. Younger age (18-29 years), lower working years (0-5 years), male (86%), and upper limb amputation (55%) dominated the participation in RTW program. Several groups require further attention by delivering information about the workplace and road dangers. This data may be used to develop the RTW program in order to increase help to high-risk patients who are unable to work following the RTW program.

Problems Formulation and Observation Of Repairing Damaged Floor Laid Expansive Soil
Authors:-Ritu Mewade

Abstract-Engineering structures constructed on expansive soils detrimental behavior of such soils, leading to their damage and cracking. The structure which can not resist the heave pressure of soil and undergo temporary or permanent deformation is known as light structure. Less lightly loaded structures like, house, canal banks and linings, cross drainage works, have been damaged and cracked due to these soil. The damage occurs, due to the swelling and shrinking behavior of such soils. Since the structures built on such soils get lifted up during rainy season due to the heave of the foundation soil and settle down during summer season due to the shrinkage of the foundation soil, there is a need to adopt remedial measures so as to prevent lifting and sinking of the structures.

The Tendency of Unemployment with Several Elements in Labour Market Institutions
Authors:- Gleys Kasih Deborah Simanjuntak, Yeti Lis Purnamadewi, Dedi Budiman Hakim

Abstract- Labour market institutions facilitate the arrangement of employment quality and working conditions that can influence the trend in employment and unemployment, thus, the elements regulated in labour market institutions are often contentious in public policy areas. Since unemployment can be jeopardised, the arrangement of effective and efficient policies in labour market institutions should prevent its growth. Hence, it is necessary to analyse the tendency of unemployment by the existence of several elements of labour market institutions such as the unemployment benefits system, collective bargaining, employment protection, and minimum wages. This takes into account whether there is a different tendency when comparing emerging and advanced economies. Moreover, the study also includes some factors outside labour market institutions to complement the analysis known as non-institutional factors consisting of macroeconomic variables such as GDP growth, exchange rates, and inflation and other relevant factors such as corporate tax and population growth. The study is analysed descriptively using cross-tabulation from thirty-two countries. The findings indicate that countries that have more generous unemployment benefits, higher collective bargaining coverage rates, minimum wage, inflation rates, corporate tax, and population growth tend to have higher unemployment rates. Meanwhile, countries tend to hold a lower unemployment rate with stricter employment protection legislation, a weak exchange rate of domestic currency, and higher GDP growth. Meanwhile, there are no different trends based on country economy comparison except for collective bargaining, employment protection legislation, and inflation.

Design of Electronic Device To Prevent On-Road Wheeling For Two-Wheelers
Authors:- Asst. Prof. Jaya Shubha J , Spoorthi P Shetty, Subhashini D, Vadde Sneha

Abstract- Driving has become difficult in the presence of bikers, who resort to dangerous stunts on busy roads despite the ban on the practice of the same. It is evident through enough cases where reckless youngsters risk their lives and perform dangerous stunts, one is wheeling. Recent years have seen an alarming rise in this dangerous trend amongst the youth. However, the police have miserably failed to curb this fatal practice amongst which has claimed several lives in the past. The project aims at developing an electromechanical device to prevent the wheeling of two wheelers on road. The need of such device is necessary for our society. These daredevils are often seen driving their motorcycles during the day and night on the back wheel, driving inversely and doing other dangerous tricks. So here is an electronic mechanical equipment which avoids the same. The bike consists of inbuilt sensor which sends a signal to the arduino board and stops the vehicle. It also sends a message to the police control room about the vehicle number and its location. The increasing trend of one-wheeling and bike-racing continues on roads, creating troubles for traffic. Therefore here comes a small effort of us for curbing the same. The usage of this device can save many lives and prevent such injuries that could not be repaired and cured by surgery as it would be a complicated task and minimize the chances of survival.

Image and Video Datasets for Yoga Pose Estimation: A Review
Authors:- Hukam Chand Saini, Dr.Renu Bagoria, and Dr. Praveen Arora

Abstract- Research and experimentation in various technical and scientific fields are based on benchmark datasets. Specifically in the field of deep learning, finding a high-quality dataset is a must for developing the model of any AI application. Dataset is an integral part of the field of deep learning as learning of the model depends on the quantity, quality, and relevancy of the dataset. In this paper, we present the literature review and summarized comparison of the different existing Yoga Pose datasets available publically for research and experiment. The purpose of this study is to help researchers to identify and select an appropriate yoga posture dataset for yoga pose recognition under human pose estimation using deep learning and machine learning technology.

Optimizing Task Scheduling in Cloud Computing Environments using hybrid approach MM-MM
Authors:- Assistant Professor Renu Tiwari

Abstract- In today’s era of rapid development in information and computing technologies, cloud computing has emerged as a highly scalable and widely used technology worldwide. It operates on the pay-per-use, remote access, Internet-based and on-demand concepts, providing customers with a shared pool of configurable resources. However, as the number of user requests continues to increase, efficient task scheduling and resource allocation have become major requirements for effective load balancing of workloads among cloud resources, thereby enhancing the overall cloud system performance. To address this issue, various types of task scheduling algorithms have been introduced. Heuristic task scheduling algorithms such as MET, MCT, Min-Min, and Max-Min play an essential role in solving the task scheduling problem. In this paper, a novel hybrid algorithm is proposed for the cloud computing environment based on two heuristic algorithms: Min-Min and Max-Min algorithms. To evaluate the effectiveness of this algorithm, the Cloudsim simulator is used with different optimization parameters such as average waiting time and total response time between small and large tasks. The results demonstrate that the proposed algorithm optimized the resource allocation and outperforms both the Min-Min and Max-Min algorithms for these parameters.

Automated Product Recognition for Retail Shopping from Video Imaging Using Machine Learning
Authors:- Sanghita Datta, Ankita Sah, Upamita Das, Debmitra Ghosh, Aman Malhotra

Abstract- The key factor to increase the profit in grocery stores now-a-days is the availability of items on the shelf. The growing market of computer vision has made it possible for the grocery stores to grow in various aspects. To tackle is growing market of on shelf detector, our model has been designed where the products kept on the shelf would be scanned and their recognition would be done in the computer screen using machine learning for the training of data onto the model. This study examines the creation of a real-time, video-based action recognition system for removing items from shelves and putting them back. In order to prevent the two classification components from operating continually, the system also includes a detector component. The action classification component of the system is evaluated to have an accuracy of 80 percent, and the object identification component of the system to have an accuracy of 70 percent.

Facial Image Data Preparation for Early Detection of Autism
Authors:- Debmitra Ghosh

Abstract- ADHD starts to appear in childhood and continues to keep going on into adolescence and adulthood. Propelled by the rise in the use of machine learning techniques in the research dimensions of medical diagnosis, this paper there is an attempt to explore the possibility to use VGG16, Mobilenet v2, Densenet-121, Resnet-51, Inceptionv3, and Convolution Neural Network for predicting A novel data-set is created with ADHD individuals of a toddler, adolescent, and adult agegroups to evaluate the model. The first data set related to ADHD screeningin children has 292 instances and 21 attributes. Second data-set related to ADHD screening. Adult subjects contain a total of 704 instances and 21 attributes. The third data-set related toADHD screening in Adolescentsubjects comprises 104 instances and 21 attributes. ACGAN is applied to increase the data set as there is an imbalance of data between healthy individuals and healthy individuals. After applying various deep learning architectures results strongly suggest that CNN-based prediction models work better on increased data sets with higher accuracy of 99.53, 98.30, and 96.88 % in Data for Adults, Children, and Adolescents respectively.

A Review on online learning and Emergency remote teaching in Music Education courses
Authors:- Urja Joshi

Abstract- This paper considers review of changes to music industry education in the digital era and evaluates the current level of technology use within the music industry curriculum as a result of a survey on student perception. Since analysis of the collected data revealed a need to enhance the curriculum with computing and information technology competences, thesepropose and discuss novel courses that would facilitate students’ acquisition of digital knowledge and skills. Theseadditionally provide comments on the possible enrichment of existing courses with material on digital technologies applications. The information in this study is aimed not only at music industry educators but also at instructors in other disciplines willing to make their students aware of the latest technological trends.

Review on Novel Approach to observation of Brain Image Anomaly
Authors:- Ronit Dey

Abstract- – An early diagnosis of brain anomaly plays a pivotal role in better prognosis, treatment outcomes and higher patient survival rate. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a difficult process. Thus, there is a crucial need for computer-aided methods with better accuracy for early anomalydiagnosis. Computer-aided brain anomaly diagnosis from MRI images consists of tumor detection, segmentation, and classification processes. Over the past few years, many studies have focused on traditional or classical machine learning techniques for brain tumor diagnosis. Recently, interest has developed in using deep learning techniques for diagnosing brain tumors with better accuracy and robustness. This study presents a comprehensive review of traditional machine learning techniques and evolving deep learning techniques for brain tumor diagnosis. This review paper identifies the key achievements reflected in the performance measurement metrics of the applied algorithms in the three diagnosis processes. In addition, this study discusses the key findings and draws attention to the lessons learned as a roadmap for future research.

Unlocking Success: Integrating AI in Traditional Banking Operations
Authors:- Kinil Doshi

Abstract- – This article reviews the practical application of Artificial Intelligence in the framework of traditional banking, focusing on three major vectors – efficiency increase, customer service and compliance strengthening. Acknowledges that AI is an opportunity for banks to keep up with the times and improve business processes, adapt services to users, optimize workflow and ensure the purity of the market and adherence to procedures. In particular, the work considers options for using AI, identifies the benefits of its application and the challenges that must be addressed, taking into account the regulatory framework and the need for impeccable data governance. Thus, the provision of strategies for successful introduction and reflection on the experience of successful banks creates a fundamental basis for banks that still need to gamify their business in terms of AI.

DOI: 10.61137/ijsret.vol.8.issue6.537

Facial Sentiment Analysis Using CNN Models: Applications of IoT Integration across Various Fields
Authors:- Arin Saxena, Disha Rathi

Abstract- – Facial sentiment analysis is an increasingly important area of research, with applications ranging from healthcare to marketing, education, and security. The rise of Internet of Things (IoT) devices has allowed for the seamless integration of sentiment analysis into real-world applications by enabling real-time data collection and processing. Convolutional Neural Networks (CNNs) have proven to be highly effective in the task of facial sentiment analysis due to their ability to automatically extract features from images, making them a popular choice for various IoT-integrated applications. This paper reviews existing research before 2022, focusing on the use of CNNs for facial sentiment analysis and their integration with IoT systems across different fields. We explore the methodology behind CNN-based facial recognition, key applications in healthcare, education, security, and customer engagement, as well as challenges such as data privacy, model scalability, and deployment constraints in IoT environments.

Blockchain-Based Framework for Secure OTA Updates in Autonomous Vehicles
Authors:- Siranjeevi Srinivasa Raghavan

Abstract- – This paper presents a blockchain-based framework designed to enhance the security of Over-the-Air (OTA) updates in autonomous vehicles. By leveraging the decentralized, immutable, and transparent nature of blockchain technology, the framework ensures the authenticity and integrity of software updates. A smart contract-driven approval mechanism prevents unauthorized modifications while addressing critical challenges such as latency, scalability, and energy efficiency. The study evaluates the trade-offs in blockchain adoption for vehicular systems, offering a detailed analysis of its impact on operational performance. Results demonstrate that the proposed framework significantly improves OTA update security without compromising real-time requirements or resource constraints, making it a viable solution for secure vehicular ecosystems.

DOI: 10.61137/ijsret.vol.8.issue6.426

A Comparative Study on the Estimation of Protein Content in 3 Leguminous Seeds:Vigna Unguiculata, Cicer Arietinum and Glycine Max
Authors:- Dr.Jyothi Kanchan A.S.

Abstract- – A comparative study was conducted to find out the protein content in three leguminous seeds: Vigna unguiculata (cowpea), Cicer arietinum (chickpea), and Glycine max (soybean). The study was conducted in these seeds with and without the seed coat using the Lowry method. Seed extracts were prepared by grinding, centrifuging, and treating with trichloro-acetic acid (TCA) and sodium hydroxide (NaOH). A standard graph for protein estimation was prepared using Bovine serum albumin (BSA). The optical density of the extracts was measured at 650 nm, and the protein content was determined using the standard graph. Results showed protein content in micrograms for seeds with and without the seed coat was 44 and 38 for cowpea, 64 and 26 for chickpea, and 48 and 38 for soybean. Chickpea seeds with the seed coat had the highest protein content. The presence of the seed coat contributed to higher protein content in all cases. The findings support earlier reports on protein content variation among pulses and the influence of factors such as location, nutrition availability, climatic conditions, and germination. The study highlights legumes as a rich protein source and potential interference of compounds with the Lowry’s method for protein estimation.

Entrepreneurship in the Digital Age: New Ventures and Innovative Business Models
Authors:- Lakshmi Kalyani Chinthala

Abstract- – The landscape of entrepreneurship is being reshaped by the rapid advancements in technology, changing consumer preferences, and the rise of digital platforms. This paper explores how digital transformation is influencing entrepreneurship, with a focus on the development of new ventures and innovative business models. It highlights the role of technology in creating opportunities for entrepreneurs to scale their businesses, disrupt traditional industries, and reach global markets. The paper delves into key trends, such as the gig economy, digital platforms, and the rise of e-commerce, and examines how these trends are shaping the entrepreneurial ecosystem. It also discusses the challenges and opportunities presented by digital tools, including the need for entrepreneurs to adapt to new technologies and navigate complex regulatory environments. Furthermore, the paper explores the role of venture capital, funding options, and the growing importance of digital marketing and customer acquisition strategies. By analyzing these trends and challenges, the paper provides insights into how aspiring entrepreneurs can leverage digital tools and innovative business models to succeed in the digital age.

DOI: 10.61137/ijsret.vol.8.issue6.542

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Authors: Santhosh Reddy BasiReddy

Abstract: Customer Relationship Management (CRM) systems have evolved from static data repositories into dynamic enterprise platforms that orchestrate complex workflows across sales, service, and marketing functions. Despite these advances, many CRM implementations remain constrained by deterministic, rule-based automation, limited personalization, and inflexible interaction models. Recent progress in generative artificial intelligence, particularly transformer-based language models, introduces new opportunities to augment CRM systems with adaptive, context-aware intelligence capable of understanding intent, generating natural language responses, and supporting real-time decision-making. This paper investigates how generative AI can be systematically integrated into CRM workflows to enhance customer engagement, automate operational processes, and improve organizational efficiency. Building on prior research in natural language processing, conversational agents, recommender systems, and knowledge representation, we propose a conceptual architecture for AI-augmented CRM workflows that combines generative models with structured enterprise data and workflow orchestration. We analyze key enabling technologies, review empirical studies on AI-driven customer interactions, and examine ethical, privacy, and governance considerations essential for responsible enterprise adoption. Rather than replacing existing CRM platforms, we position generative AI as a complementary intelligence layer that transforms customer engagement from reactive, rule-driven processes into proactive, context-aware experiences.

DOI: https://doi.org/10.5281/zenodo.18324413

 

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Authors: Oluwabanke Aminat Shodimu, Kofi Mensah

Abstract: The integration of big data analytics into credit scoring and lending practices has fundamentally transformed the financial services landscape in the United States. This transformation represents a paradigm shift from traditional credit assessment methods to sophisticated, data-driven approaches that leverage vast amounts of structured and unstructured data. This article examines how big data analytics is revolutionizing credit scoring processes, making them more personalized and dynamic while simultaneously raising important questions about fairness, privacy, and financial inclusion. Through comprehensive analysis of current practices, regulatory frameworks, and emerging trends, this study evaluates the multifaceted implications of big data adoption in the credit industry, highlighting both the unprecedented opportunities for improved risk assessment and the potential challenges that accompany this technological evolution.

 

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Researchers, academicians, professors, lecturers, scholars, and other individuals do research in the field of science, mathematics, physics, medicine, chemistry, bio-technology, aerospace, arts, humanities, social sciences, computer science, engineering, machine learning, AI and various other branches and subjects of their interest. After that, they write research papers or articles to arrange their findings in a sophisticated manner so that people will learn and understand the process and outcomes easily. The aim of writing research papers is to make them available to other people to read, review, suggest, learn and understand their work all over the globe.

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Digitization opens up more opportunities and possibilities in front of people like researchers, scholars, academicians etc. their research or findings can be easily available to the other side of people. They can now discuss, criticise, suggest, and comment on the things publicized in front of them; which is quite good for academics and helps to improve in no time.

As it mentioned above the aim is to reach a wider audience so they find platforms that provide them with global reach and make their work readable by a larger audience around the world.

Most of the journals publish academic work, research papers or articles from specific fields. Some journals publish research papers and articles from a variety of fields as well.

In this blog, we are going to let you know about top paper publishing journals. As there is no journal that can be stated as a top journal because every journal has its own specialty and above all its own discipline to publish quality work with open access to everyone so that transportation of knowledge becomes easy and one can make their finding available to the audience worldwide.

In the field of journals, it is not necessary that the journal tops in one field also tops in other as well. It also depends on the reviewing panel if a journal has reviewers from different fields then it may accept papers from that field as well. But in most cases, they accept only from their domain. Quality matters all above so they take time in reviewing. If reviewing goes well then it proceeds further.

Here in this section we are going to provide the list of the journals which tops in their respective fields. We remind you once again there is no top journal but each has their own significance in their areas.

• Check the publication count in the regular issue of the journal.
• Check foreign author publication in each few issue, this help to understand the popularity of journal.
• Check the certificate, number of pages, and charges before submission of the paper.

Consult with the mentor as well before final submission of paper.

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Journals receive papers from various fields but they accept only those in their domains and reject others. Journals run on the papers and articles provided by authors without them their existence means nothing.

Most of the journals publish articles or research papers for free. Submitting papers free of cost looks fascinating but it takes a more valuable or precious thing called time. Reviewing is the first process after submitting the papers and it is a time taking process. In some big journals, it took more than 3 months for peer review. And things regarding publishing let it complete in more than 6 to 8 months to get published on their portal. Some researches need to be reviewed sooner so that scholars can work on them further and as researchers have no time to waste so they earnestly seek journals and other platforms which make their findings available to readers as soon as possible.

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The need for fast publication leads journals to begin a paid publications category. It helps individuals to make their writings available to wider audiences in less time. For this, they just have to pay some amount so that their research paper or article gets more attention from journals to be reviewed fast and published on the forum in less time compared to free publication.

Some journals work two-dimensional; they provide fast publication facilities along with free publication. Basically, fast publications are paid.

Some fast-publishing journals with low processing fee

 In this segment, we are going to discuss journals that publish fast without compromising quality content. They are as follows:

IJSRET – international journal of scientific research and engineering trends is a well-known journal. This publishes research papers and articles on the ongoing scientific research and engineering trends that are performed by individuals or researchers in their respective fields. It is a paid journal but always focused on authenticity and originality so it accepts only quality journals to be published on the platform. The paper here will be processed within 3 to 5 days and the amount is also negotiable.

All the information given here will certainly help you in finding your answers. We believe in and support the circulation of good quality content for people all around the world. One can look for other sites as well to find satisfactory answers.

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If you are a student or fellow researcher, scholar or academician who has completed their research and has written a research paper recently for the first time; and now wants to publish it but has no idea how it’s done then you are in the right place to find out how to publish a paper in a journal.

In the following article, we are going to help you in publishing your paper in a journal. Further information can be useful for beginners and intermediate researchers who want to publish their research work in a journal to letting their work or findings known by other scholars or individuals who have an interest or doing research in that field.

Before knowing how to publish a paper in a journal let us make sure by following points if the paper is written in the right order so that chances of getting published will be high. They are as follows :

Things to be considered before submitting the paper in a journal

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1. Check if a paper is written in an ideal format.
2. The paper should be plagiarism free.
3. All formatting is done correctly.
4. Check headings and spelling mistakes if any.

How to publish a paper in a journal

The following points given below describe the process of the paper getting selected to be published in the journal. it may differ from the one you have learned from others. Here in this segment, the most common approach is explained so that one can have an overview of the process. It is as follows :

1. Go to the journal site selected by you and apply for journal submission.
2. Fill the necessary details asked by the journal like the title of the paper, area of research, type of manuscript, email, contact no. etc.
3. Upload the manuscript in the format asked by the journal.
4. Fill correct email address or other contact information because all the upcoming information regarding the paper will be notified by email.
5. After that one would be notified by the journal if the paper got accepted for review.
6. Reviewing takes time so wait patiently for their feedback.
7. It is possible the reviewer may ask you some questions regarding your research or recommend suggestions to improve the quality so don’t demoralize and accept them as a compliment.
8. Try to improve things as suggested by the reviewer or answer them accordingly.

If your paper has good quality and the board thinks it should be published then it proceeds further and get published on that platform.

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In most of the journals, Usually, Papers get published for free and some of the journals ask for minimum charges to publish a paper according to journal norms.

 Publishing a paper free of cost actually costs the time and motivation of individuals in a big journal. It costs them more than 3 months to get peer-reviewed. After that if some changes are required then it is delayed from 6 to 8 months; Sometimes it gets rejected as well if they don’t have experts in that field for reviewing. All of this makes them impatient and demoralized to do other research work.

Researchers, scholars, academicians, and other individuals who engulf themselves in the field of research write about their works, outcomes, methods, tools, and processes in the form of research papers or articles in a sophisticated manner.

Many of them don’t have that much money to spend on publishing so they seek the cheapest journal to publish their work in a given time.

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There are many journals that publish research work free of cost or ask for minimum charges to publish academic work. IJSET is one of those journals which provide publication facilities free of cost to its users. It accepts only good quality papers or articles that are free from plagiarism and have authenticity in them. As publications without any charges took at least 3 months to get listed, people usually move to fast publications which cost them more than the research cost so they seek well-reputed journals that charge less. On this platform, one can also choose a fast publication option to publish their work on time.

Apart from that, there is another journal called IJSRET which also publishes research work in the field of scientific research and engineering trends. So if you are from this field you can opt for this journal. This journal also provides a good communication facility so that users can resolve their problems or issues easily.

The present time is full of technologies so everyone can find the solutions of their issues in no time. The information provided here will surely help those who are looking for good-quality journals with low publishing charges. One can also visit other platforms as well to find solutions for them.

Consult your mentor and student of the same domain they also suggest your journals that may fulfill your requirement. Apart from taking suggestions, scholars can make its own list of journals that are good, and professional, and process papers for review in less time.

Published by: vikaspatanker

This article covers the following points to help young scholars for getting Good journals for Publishing.

• How to get a good journal for publication
• Benefits of a good journal
• Things should keep in mind while selecting a journal
• Some good journals
• Conclusion

Many students, scholars, and researchers do research under their mentors. After conducting each research they have to write it down in the research paper or article so that everyone related to that field can learn and understand the work done by them. For that, they seek help from their mentors and others who can suggest to them some good journals that accept papers or articles in that particular field to publish their work.

How to find a good journal or get a good journal for publication

At present, almost all journals get digitized and are available online. One can search for them on the internet easily. There are more than 30000 journals in the world that publish lakhs of papers and articles every year. Finding a good journal from the sea of journals is quite a work..

But as you know if there is a problem, so the solution is. There are several good journals out there, IJSET is one of them that is focused on promoting quality research work and providing its facility in the publishing industry from last decade.

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Review Article Processing Charges

As a mentor one can guide their fellow students and researchers in finding good journals for publishing their work. One should go for

Benefits of A Good Journal

• Get more citations for research papers or articles.
• Get connected to a wider audience.
• Get academic work indexed on good platforms.
• Get global recognition.
• Get your work reviewed by experts.

There are some things that one should consider before applying for submitting the paper or article in a selected journal for publishing. They are as follows :

Check ISSN No. – before submitting the paper or article check the ISSN no of that journal. It is an eight-digit code that conceals information about that journal’s validity.

Check impact factor – a journal’s credibility depends on its impact factor. If a journal has more than 3 markings in impact factor then it is considered good by academicians.

Check indexing – indexing plays a major role in reaching to the target audience and increasing one’s reach so check if the journal is indexed in some good indexing platforms i.e. ABCD INDEX, google scholar, academia Edu, cite factor etc.

Volumes – if a journal is existing for more than 6 years in the particular field you are looking for, then the reliability and credibility of that journal is considered more in comparison to new journals.

Conclusion

There is no system to distinguish good or bad journals in the research field but one can utilize a basic code of conduct to identify them and also use suggestions given in the blog to find good journals for them. The world is full of information, good suggestions, and advice; so one can freely rely on other sources to find the best for oneself.

Published by: vikaspatanker

Students who are in the final years of their studies, academicians, scholars, and fellow researchers, write papers about the research or survey they have done. After that, they seek a platform from where they can reach the target audience easily. As you know, doing research and then concluding it in a research paper or article is not an easy task. Apart from that, making it available to the target audience is another thing to accomplish.

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Review Article Processing Charges

Everything needs financial assistance in different parts of their execution or level whether it is conducting research, survey, other accessories, tools, or writing processes.  Due to all of this they seek journals that publish papers free of cost or charge little; so that they can publish their papers or articles without extra financial burden on themselves.

Here in this article, we are going to give you a direction of journals that either publish free or charge a minimum cost for accepting papers and articles. But before that, it is suggested to know the things that will help in selecting a quality journal.

We are going to discuss some of the things that one should know or consider while looking for a journal to publish research papers or articles. They are in the following points given below :

Scope of the journal – The scope of the journal means the area of expertise in which that journal accepts papers and articles. It is important to know the domain in which journals mainly work so that you can have an idea if the journal would be able to accept your work or not.

Previously published work – there are many journals which are publishing works in different fields so one should know the

Indexing – indexing shows the credibility of the journals. If a journal is indexed in some good indexing sites or platforms then It is considered good and get acceptance among the researchers.

Citation – demand, and acceptance of any paper depend on its quality and citation. So if a journal has good citations for its former published work then it will surely help you in getting a good citations for your papers or articles and recognition as well.

Validity – there are more than 0.25 million journals that are publishing work at the present time but finding a valid journal is tricky, so one should check the ISSN no of the journal to avoid any fraudulence.

Most journals provide free access to their portal. In other words, they won’t charge a penny from scholars for publishing their work on their platforms. But for kind information free publishing took time. Sometimes it delays more than 6 months to publish the paper because they have a lot of pending work to review. If one wants to publish their work on time they can move to paid publication. There are several good journals that provide this facility along with free publications. IJSET is one of those platforms which provide the fast publication with low charges along with a formatting facility; as researchers don’t have that much time to arrange data in a particular format.

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Whale Optimization Algorithm for Optimal Reactive Power Dispatch and Voltage Control
Authors:-Reza Azimi

Abstract- The Whale Optimization Algorithm is used in this study to perform multi objective probabilistic optimum reactive power dispatch and voltage control in distribution networks (WOA). To obtain the ideal value of voltage deviation, losses, reactive power flow through the OLTC, and voltage variations, control factors such as on-load tap changer (OLTC) settings at substations and substation and feeder switching capacitors must be determined. As a result, a precise optimization strategy is necessary to address this complex problem. The Whale Optimization Algorithm, one of the unique optimization algorithms inspired by humpback whales, is used in this study to tackle the challenge mentioned above. Because the proposed problem is a multi objective optimization problem with several answers rather than a single answer, we employed the Pareto optimum solution approach to finding all Pareto optimal solutions. In addition, the fuzzy decision technique is used to find the best compromise solution. The suggested approach is tested using the IEEE-33 bus system. The numerical results illustrate the efficacy of the suggested approach.

Independent Remote Therapy for Muscular Lumbago using IMU Sensor Network, Computer Vision and Machine learning
Authors:- Dhruva Iyer

Abstract- This project introduces a new potential tool that will help with independent detection and real-time check on the rehabilitation process of Low Back Pain(LBP) patients. This tool uses an integration of the sensors – IMU sensor to check the range of motion, FSR flex sensors to check flexibility, and an EMG sensor to check core muscle activation. The core of this tool is a PCB that houses the foundation of the multiple sensors and their connections to the microcontroller, the Arduino Nano. These sensors are coded on the Arduino software to give a collaborated result, which is then directly taken onto a python file. This is saved as a CSV file and runs on an algorithm to produce a graph through matplotlib. Then a program is performed on it to make a comparison of the collected data values to the initial threshold values which helps create the buzz and the skeleton mapping for the client. This way, the user knows if they are doing the correct postures of exercises as prescribed by the therapist and on the right track to enhancing their recovery, which might even help with psychosomatic instincts. Furthermore, remote physiotherapy becomes possible and the frequency of visiting the physiotherapist in distressing times of pain and anxiety caused due to the problem is reduced, a major plus point for sales. Dr Indu Tandon, a well-known physiotherapist, who has gained much appreciation for her work in the 20 years of her physiotherapy career helping local, national, and international people says that currently, there is no such device in the market that helps with LBP. So far we are testing and finding multiple ways to solve this very problem. In this research paper we have mentioned a detailed analysis and design approach of our two test prototypes which give us commendable analysis results.

A Review Article of Statcom Design and Inhancement Controlling of Power Quality
Authors:- M.Tech. Scholar Rashmi Singh, Prof. Mr. Arun Pachori, Asst. Prof. Mr. Pawan Kumar Pandey

Abstract- This paper deals with A New design of D-STATCOM (Distribution Static Compensator) is Used for Mitigation of Power Quality Problems under unbalance caused by various loads in distribution system. This paper addresses the modeling and analysis of custom power controllers, power electronic-based equipment aimed at enhancing the reliability and quality of power flows in low voltage distribution networks using DSTATCOM. A new PWM- based control scheme has been proposed that only requires voltage measurements the operation of the proposed control method is presented for D-STATCOM. Simulations and analysis are carried out in MATLAB/SIMULINK with this control method for two proposed systems.

Design and Development of Remotely Firmware Upgradation Based on Wired and Wireless Protocols
Authors:- Arbaaz khan, Mohd Anas Ali, Shanila Mahreen

Abstract- The focus of this work is on design considerations and the implementation of a highly portable bootloader for embedded devices with limited resources that allows for fail-proof firmware upgrades over the air. For STM32 series system on chips, a bootloader was created in this thesis that enables firmware upgrades over Wi-Fi networks. The implementation is for the STM32, but there are also general design considerations for bootloaders for fail-proof firmware updates presented here. As a result, I think that the concepts discussed here can be easily applied to projects involving similar embedded systems. First, a brief explanation of the over-the-air firmware upgrade process, its difficulties, and the related system components follows. The specifics of the implementation are then explained. A number of individual components are discussed in detail based on the System architecture. Discussion of the dependability and fault tolerance of the firmware upgrade process is one of the thesis’ main focuses. Several experiments are run to validate the implementation.

Identification of Long Run and Short Run Linkage between Energy and GDP towards Carbon Emissions- An Indian Perspective
Authors:- Dr. Neetu Narwal

Abstract- Energy is the driving force behind the economic growth of any country, and it is said to be coupled with environment degradation. In India, CO2 emission is continuously increasing, and the major contribution lies in coal burning to meet electricity demands. This study is an attempt to analyse the World Bank data pertaining to India in order to find the aggregate effect of different energy sources on economic growth. The results show that energy variables and GDP are cointegrated and hence there exist long term relationship between these variables. The outcomes are evident for existence of both short-term and long-term association of all energy variables and GDP with the carbon emission. This study further analyses the current energy scenario of India and suggests that there is urgent need to Transend towards alternative resources of energy like hydroelectric or nuclear energy.

Productivity Enhancement in Machining of Al6061 alloy Subjected to Dry and Nano-fluid Assisted Minimum Quantity Lubrication Approach
Authors:- Durgesh Singh, Sankalp Verma

Abstract- Since there is a lot of concern regarding energy wastage in the current world, so it is important to develop alternative methods which can be energy efficient for machining. Dry, minimum quantity lubrication (MQL) and nanofluid MQL-assisted are some of those processes. Investigation of experimental machining process parameters has been on notice for several decades among researchers. Aluminium (Al) 6061 alloys have been widely used in the field of automobile and aerospace industries owing to exceptional characteristics. In this paper, the Al6061 alloy specimen has been employed for the machining investigation subjected to dry, MQL and nanofluid (h-BN and Graphene) MQL-assisted CNC turning operation. The influence of the machining parameter on the wear response in the turning of Al6061 with dry and MQL employing nanoparticles-based nanofluid (h-BN and Graphene) was examined. These Al6061 alloy specimens were machined by varying the cutting speed (CS) (180-200 m/min), feed rate (FR) (0.1-0.3 mm/rev) and depth of cut (DOC) (0.5 mm) their influences on surface finish and tool wear were analyzed. The processes were performed in dry, MQL and nanofluid (h-BN and Graphene) MQL-assisted environments. It was found that machining under the nanofluid MQL-assisted conditions is preferable due to better surface finish and tool wear. Moreover, it was evident that machining characteristics were much more satisfactory in MQL-assisted conditions over the dry and MQL conditions.

An Overview of Fundamentals to Prospective of Immunometabolism in New Therapy
Authors:- Ahmad M Khalil

Abstract- Mitochondria represent a unique quality control cellular system, wherein they coordinate multiple functional activities. They are highly dynamic organelles and can easily modify their morphology by fusion or fission to adapt to cellular responses to various challenges. The intercommunication among mitochondria and other cellular organelles is responsible for the assembly and maintenance of the cell. The current overview followed PRISMA guidelines and used the PubMed/Medline databases to explore and summarize the entire literature generated and dedicated during the past few years to applications of mitochondrial biology in biomedicine. Analysis of the data demonstrated that mitochondria have a dual cellular function the “Immunometabolism”; in addition to their well-recognized bioenergetic function, they are key members of the innate immune system. Further, it is found that many disorders are associated with insufficient mitochondrial quality control. It is concluded that understanding the molecular mechanisms of mitochondrial function and dysfunction is a new exciting field. Outstanding candidate potential therapeutic roles of mitochondria are emerging. This research topic may take humanity to a new era of secure and efficient diagnosis, prevention, or therapy of human diseases.

Optimization of Machining Process Parameters of Al6061 alloy Subjected to Dry and Nano-fluid Assisted Minimum Quantity Lubrication Approach
Authors:- Durgesh Singh, Sankalp Verma

Abstract- Investigation of experimental machining process parameters has been on notice for several decades among researchers. Aluminium (Al) 6061 alloys have been widely used in the field of automobile and aerospace industries owing to exceptional characteristics. Surface finish and less tool wear for better productivity are prime requirements during machining processes. In most machining operations the main objective is the achievement of less surface roughness and tool wear. In this study, analysis has been performed for optimizing CNC machining process using Taguchi Method. We are analyzing the machine parameters and optimization of CNC machining employing Taguchi Method (L9 Orthogonal array); the parameters are cutting speed, feed rate and machining environment. We have considered three process parameters and their levels based on the analysis parameters which are affecting the machining process. For input machining process parameters experiments are designed using Taguchi L9 orthogonal standard array. For this purpose, MINITAB17 software is employed. While optimizing machining parameters lowest surface roughness (Ra) of 0.42310 μm was achieved corresponding to FR: 0.1 mm/rev, CS: 200 m/min. and Machining Environment: Groundnut oil/h-BN based nanofluid MQL-assisted machining.

Optimization for Speech to Text Conversion Using Convolutional Neural Network
Authors:- Rahul Singh Sengar, Vatsal Mehta

Abstract- The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of artificial intelligence in common machine learning tasks. One of the most impressive forms of ANN architecture is that of the Convolutional Neural Network (CNN). CNNs are primarily used to solve dif icult image-driven pattern recognition tasks and with their precise yet simple architecture, of er a simplified method of getting started with ANNs. This document provides a brief introduction to CNNs, discussing recently published papers and newly formed techniques in developing these brilliantly fantastic image recognition models. This introduction assumes you are familiar with the fundamentals of ANNs and machine learning. The ability to accurately represent audio signals is central to language understanding. The network uses Conv1d, a global pooling operation over linear sequences. The network handles input audio signals of varying lengths and induces a feature graph over the audio signals that are capable of explicitly capturing short and long-range relations. The network does not rely on a parse tree and is easily applicable to any language. We test the CNN in Modeling Audio signals to Texts. The network achieves the excellent performance of a greater than 25% error reduction in the last task with respect to the strongest baseline.

MPPT Integrate with Fuzzy Logic Control Compared with Conventional Techniques
Authors:-Krishan Kumar Meeena, Mr. Neeraj Sharma, Mr. Pushpendra

Abstract- Photovoltaic (PV), which functions on the concept of the photoelectric effect, is considered one of the environmentally beneficial Renewable Energy Sources (RES) that has a large deal of capacity and converts solar energy directly into electricity. Continually changing physical properties of PV systems are dependent on their surroundings. Therefore, it is crucial to regularly track the Maximum Power Point (MPP) in order to get the most power possible from PV. This paper discusses one artificial intelligence control tool, the fuzzy logic controller (FLC), as well as traditional hill climbing methods like perturb and observe (P&O) and incremental conductance (IC) for MPP tracking. Fuzzy controller application results in superior performance versus traditional methods. In comparison to other methods, the MPP stability produced by a fuzzy controller is higher. The amount of energy extracted from PV panels is also contrasted with other methods.

Asset Tracking Solution Based On Iot
Authors:- Shah Mohammed Aliuddin, Mohammed Anwaruddin, Shanila Mehreen

Abstract- The purpose of this project of this project is to integrate and implement IoT technology with Asset Tracking Solution. Asset Tracking Solution is a program that manages and monitors the IT assets found. It tracks an asset for its entire duration in the organization. You can manage LAN as well as work from home endpoints from a central location. Using FATS, you can manage both hardware and solution assets in your network anywhere, anytime, from your laptop or mobile phone. Fixed Assets Tracking Solution applies asset with Unique Asset Id (UAID) by means of barcode or RFID tags. These tags can be in compliance with requirements of various authorities like IEEE, SOX, etc.

A Review of System for Detecting Intruders Using Convolutional Neural Networks
Authors:- M.Tech. Scholar Sanjay Soni, Assistant Prof. Aditi Khemariya

Abstract- Internet use has made computer networks vulnerable to cyberspace-related attacks. As a consequence, researchers invented intrusion detection systems, or IDSs. Identifying network intrusions is an issue in network security research. As a preventative measure, it helps identify unauthorised network usage and assaults. Methods such as machine learning (ML), Bayesian algorithms, nature-inspired meta-heuristic methods, swarm smart algorithms, and Markov neural networks have been developed to find the most important characteristics and boost intrusion detection system efficacy. Hundreds of active studies were compared to various data sets over many years. This work analyses single, hybrid, and ensemble classification approaches. The analysis is broad. We compared the publications’ IDS results, limitations, and datasets. This helped us evaluate the research’s quality. Below is a possible future research path.

System for Detecting Intruders Using Convolutional Neural Networks
Authors:- M. Tech. Scholar Sanjay Soni, Assistant Prof. Aditi Khemariya

Abstract- On the internet, malicious activities may take place, which can infect a single computer or bring down a whole network. It’s possible that they are chosen at random. The number of people connecting to the internet at an ever-increasing pace makes it more difficult to keep up. The internet, just like real life, may provide a number of potential safety hazards. The IDS software watches a network for activity that might be hostile or suspicious. IDS stands for intrusion detection system, and it is a kind of technology that helps detect attacks on computer systems and determine who carried them out. Machine learning (ML) strategies were used in the past to increase IDS accuracy and the results of intrusion detection. In this article, we will go through the process of constructing IDS by using CNN approach. This is a method that may be used when developing effective IDS. On the KDD, the technique that was proposed will be implemented (Knowledge Discovery Dataset). The accuracy of the technique that has been provided is clearly superior to that of SVM, Naive Bayes, and Decision Tree. It is possible to have faith in this because: The following outcomes were a consequence of using our method: 3.24 minutes is the amount of time required for performance, with an accuracy of 96.78% and an error rate of 0.21 percent.

Distant-Hit Algorithm for Longest Common Subsequence
Authors:- P. S. Sathya Narayanan

Abstract- LCS stands for Longest Common Subsequence. Generally a subsequence is a set of characters that appear in same order relatively but they necessarily need not be contiguous. For example let there be a word ‘LOVE’ here ‘LO’ , ‘LVE’, ‘OV’, ‘LOVE’, etc… are known as the subsequences of the word LOVE. We have been using the LCS algorithm all these days which uses the Dynamic Programming Approach to find the length of the Longest Common Subsequence between two words which has the time complexity of O(m*n) and the SpaceComplexity of O(m*n) where m is the length of comparing string (say String1) and n is the length of compared string (say String2). In this approach the data structure used to declare the comparison space is a 2D Array and the datatype used for it is Integer which costs literally 2 – 4 bytes of space for every digit based on the compiler. Contradicting to this way the Approach mentioned in this paper (Distant-Hit Algorithm/Dist-hit Algorithm) can do the same LCS task by using an 1D Array data-structure of Bool datatype which actually costs 1 byte per digit. The space complexity is O(m+n) and time complexity is same as O(m*n). Since This LCS algorithm is used in various modern-day fields like linguistics, bioinformatics, Common sequence identification, biometrics, revision control systems (GIT)etc… This sort of optimization will be helpful in reducing the memory used for the comparison space of two strings.

Gender Bias and Economic Growth in West Java
Authors:- Magdalena Sinaga, Asst. Dr. Lukytawati Anggraeni

Abstract- LCS stands for Longest Common Subsequence. Generally a subsequence is a set of characters that appear in same order relatively but they necessarily need not be contiguous. For example let there be a word ‘LOVE’ here ‘LO’ , ‘LVE’, ‘OV’, ‘LOVE’, etc… are known as the subsequences of the word LOVE. We have been using the LCS algorithm all these days which uses the Dynamic Programming Approach to find the length of the Longest Common Subsequence between two words which has the time complexity of O(m*n) and the SpaceComplexity of O(m*n) where m is the length of comparing string (say String1) and n is the length of compared string (say String2). In this approach the data structure used to declare the comparison space is a 2D Array and the datatype used for it is Integer which costs literally 2 – 4 bytes of space for every digit based on the compiler. Contradicting to this way the Approach mentioned in this paper (Distant-Hit Algorithm/Dist-hit Algorithm) can do the same LCS task by using an 1D Array data-structure of Bool datatype which actually costs 1 byte per digit. The space complexity is O(m+n) and time complexity is same as O(m*n). Since This LCS algorithm is used in various modern-day fields like linguistics, bioinformatics, Common sequence identification, biometrics, revision control systems (GIT)etc… This sort of optimization will be helpful in reducing the memory used for the comparison space of two strings.

A Review of Crime Detection Using Machine Learning
Authors:- Sameeksha Bhati, Assistant Professor Priyanshu Dhameniya

Abstract- As a societal and economic issue, crime has a negative impact on people’s standard of living and the health of the economy [1]. The particulars of criminal behavior vary greatly from one group or community to the next. The crime rate can be predicted, at least in part, by looking at socioeconomic indicators such as levels of education, poverty, unemployment, and weather. Vancouver, one of Canada’s most populous and diverse urban centers, is home to people of many different cultural backgrounds and ancestries. There was a 1.5% decrease in 2017’s overall crime rate in Vancouver, although a persistent problem remains with car theft. The residential burglary rate in Vancouver dropped by 27 percent after the Vancouver Police Department (VPD) used a crimepredictive model to predict such crimes. Predicting criminal activity is a tool used by law enforcement that relies on data and statistical analysis to pinpoint potential hotspots. Research in this area has continued in several countries.

A Review on Design and Thermal Analysis of Double Pipe Heat Exchanger by Changing Mass Flow Rate
Authors:- M.Tech Scholar Naveen Kumar, Prof Abhishek Bhandari

Abstract- Heat exchangers are employed in a variety of applications, included power plants, nuclear reactors in energy production, RAC systems, self-propelled industries, food industries, heat retrieval systems, & chemical handling. The techniques of upgrading can be divided into two categories: active and passive ways. The active approach necessitates the use of peripheral forces. Discrete surface geometries are required for passive approaches. These strategies are commonly utilized to increase heat exchanger performance. Helical tubes have already been designated as among the passive heat transfer enhancement materials. Due the short construction and high heat transfer coefficient, and they will be widely employed in various industrial applications. The thermo-hydraulic performance of various configurations of gas- to-liquid double-pipe heat exchangers featuring helical fins was reviewed.

Survey on Existing Online Election Systems
Authors:- Milna Eldho, Vindhuja K, Pooja Nair, Simi M S

Abstract- Traditional voting machines used are quite time-consuming, energy consuming and requires the tasks to be done at an assigned place. The basic idea of such systems is to create an Online Voting System that will help to reduce the use of the manual voting system with added security using various technologies to facilitate voting from a remote place. The proposed systems includes multiple layers of verification to ensure the reliability of the device which includes face verification, OTP, verification, biometrics etc with validation data. Each voter can access to the system only when being recognized and checked with the given database of enlist voter to proceed for the further process.

Development and Analysis of Flow through Annular Curved Diffuser with Fins
Authors:- K. Manoj Kumar, S. Deepthi, Dr. P. Srikar

Abstract-Diffusers are largely used in centrifugal compressors, axial flow compressors, combustion chambers, ram jets, gas turbine engines, inlet portions of jet engines, and so on. A minimal change in pressure recovery will increases the efficiency of the machinery. Hence diffusers are absolutely essential for good turbo machinery performance. The internal part of gas turbine engines are curved annular diffusers at high speed air craft. By decreasing the entire pressure loss the diffuser facilitate effective working of the combustor. Performance of those diffusers depends on the geometrical dimensions of diffuser and inlet conditions. In the present investigation, distribution of static pressures inside the diffuser and velocity of the fluid at outlet are studied with help of CFD on a curved annular diffuser of 70 angle of turn, circular hub of diameter to 20mm and also by varying the fins on circular hub of height to 5mm and 10mm with a thickness of 3mm and allowing the air as fluid to pass through the diffuser. Annular curved diffuser is modeled by using CREO Parametric. Modifications are done by adding fins to the model and CFD analysis is done in ANSYS Fluent to determine the flow characteristics.

Nanotechnology in Diagnosis
Authors:- Fayza Khan

Abstract-Background: The current study outlines nanotechnology’s applications and uses in the diagnosis, screening purpose and treatment of variety of ailments and used to deliver drugs, chemotherapeutic agents or imagining substances, or antigen, antibody, DNA or RNA. Main Body: Nanotechnology offers multiple benefits in treating chronic human diseases by Site specific and target-oriented delivery. The discovery and application of nanomaterials and nanotechnology in improving the efficacy of both new and old pharmaceuticals, such as natural products, as well as selective detection through disease marker molecules, allows for individualised treatment. Conclusion: Nanotechnology can be used to diagnose and treat a variety of deadly diseases, like tuberculosis, cancer and several neurological disorders.

Review of Wormhole Attack on Mobile Ad-hoc Network
Authors:- M.Tech.Scholar Ms. Babita Kumari, Prof. Dr Rakesh Sharma

Abstract- WSNs are unstable because to the wireless nature of communication since any attacker with the desire to steal the data may do so by inserting rogue nodes into the network. Attackers may carry out this by launching attacks such as wormhole, floods, grey hole, and others. The goal of routing protocols is typically to determine the shortest route between a source and a destination node. The hop count is used as a statistic to calculate the journey length. The wormhole attack, one of the several above-described attacks, is risky since it builds a tunnel by bypassing a few nodes in between them. The hop length is automatically decreased by the tunnel, resulting in a short route between the source and destination nodes. This article provides a concise overview of the methods or strategies for the identification and defence against wormhole attacks.

Review on Design and Analysis of Bridge Structures
Authors:- Dilip Patidar, Asst.Prof. Rahul Sharma

Abstract- Bridge is the structure which is used for carrying the traffic over the valley or river by connecting highways or railways. The current research reviews the existing work conducted in the field of design and analysis of bridge structure. The study presents the study of bridge structures using both experimental and numerical techniques. The formulation of different output parameters associated with strength and deformation of bridge structure is presented.

Design and Control Grid-Connected Isolated PV Microinverters: A Review
Authors:- Sonali Mathur, Assistant Professor Mukesh Kumar

Abstract- Galvanic isolation is a very significant feature that should be present in grid-connected photovoltaic (PV) microinverters because it addresses both power quality and safety concerns. However, the efficiency of the isolated varieties of microinverters is reduced due to the presence of high-frequency transformers and significant switching losses. In recent times, a number of different isolated topologies have been suggested as a means of increasing the efficiency as well as the lifetime of PV converters. The purpose of this work is to provide a thorough analysis and assessment of the most recent isolated topologies for PV microinverters. In terms of the number of stages at which they process power, these topologies can be divided into two distinct classes: 1) single-stage microinverter, and 2) multi-stage microinverter. A number of possible topologies are discussed, contrasted, and analyzed in terms of the power losses that occur at various stages, control mechanisms, where the decoupling capacitor should be located, and the overall cost. In order to acquire a comprehensive image of the framework for the future generation of isolated PV microinverters, recommendations are made to improve the existing topologies and select the relevant control mechanisms.

Published by: vikaspatanker