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IJSRET Volume 9 Issue 5, Sept-Oct-2023

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Design of Micro-Miniaturized Printed Monopole Antenna for WLAN/WIMAX Operations in Laptop Computers
Authors:- Zubair Nazir Sheikh, Shaveta Bala

Abstract-With an air-filled hole thickness between the receiving wire and the system ground, a one-of-a-kind labyrinth molded printed double band monopole miniature scaled-down receiving wire of 6 x4x1.6 mm3 is proposed. The essential elements of the labyrinth molded transmitting structure are to protract the surface current course on the emanating surface and to work on the transmission capacity across the two groups of interest, which are the Bluetooth fl (2.40-2.48)GHz band and the Wireless Local Area Network (WLAN) guidelines’ fu (5.15-5.85GHz high recurrence groups). The proposed receiving wire includes a more straightforward comparable circuit model, and its reproduction is done. The proposed receiving wire likewise has a respectable increase of (2.72-6.62) dBi and an ideal radiation effectiveness of (61 to 91)% over the functioning groups notwithstanding the previously mentioned qualities. The proposed receiving wire structure is viewed as appropriate for WLAN/WiMAX applications in the personal computer (PC) on the receiving wire’s reenactment and estimation discoveries, which are viewed as in great arrangement.

Mechanical Behavior of Concrete by Partial Replacement of Cement with Silica Fume and Polypropylene Fibers: An Analytical Approach
Authors:-Research Scholar Kalvala Abhiram, Assistant Professor Dr. G. Prashanth

Abstract-Fibre and PET are now being researched for use in reinforcing reinforced concrete members all over the world.PET bottles are the by-products of storing cold beverages, drinks, or even water. On the other hand, super high strength with high performance is becoming the order of the day in order to construct structures that are durable, environmentally conscious, and even cost effective. These days, composite materials are being developed to meet the needs of the building industry by providing more flexible and durable concrete. The makers and consumers of plastic face a significant issue in disposing of plastics in any form. In today’s scenario, the production of environmentally friendly plastics has not yet reached its pinnacle. This is an attempt to dispose of the same effectively by including it as an effective component in concrete. Because of its improved strength, crushed PET bottles have found their way into concrete as a replacement for fine and coarse materials. PET bottles, fine aggregate, and polypropylene fibre have been used to improve the tensile property of M35 grade concrete in order to make it more effective, light weight, and efficient. In this investigation, the mechanical properties of the concrete were investigated, as well as the performance of the concrete.

Waste Plastic as an Effective Construction Material in Flexible Pavement
Authors:- Research Scholar Kalvala Abhiram, Assistant Professor Dr. G. Prashanth

Abstract– Safeguarding of street foundation requires an orderly methodology for the great presentation of streets remembering the future condition and upkeep situations. Presently a-days asphalts are exposed to different sorts of stacking which influences the asphalt execution condition that causes different troubles. These upset incorporate rutting, weakness breaking, and temperature breaking. Anticipating the natural condition, total prohibition on plastic can’t be made. Hence, utilizing of plastic as an imaginative innovation reinforced the street development as well as increment the street life. This paper incorporates the consequences of the different lab tests directed on bitumen, total and bitumen-total plastic blend.

Effective Use Of Used Tyres In The Repair Work Of Damaged Bituminous Roads
Authors:- Research Scholar Kalvala Abhiram, Assistant Professor Dr. G. Prashanth

Abstract-Pavements are the major part of transportation in the view of highway constructions. Transportation involves within two wheelers to heavy wheelers. In the transportation point of view the pavement condition is very important. If the pavement condition is good, then the transportation will be done with ease. The major problem in pavements damages is due to heavy loading and environmental causes. When the load acting on the pavements heavily, the damage will effect mostly on surface course as well as base course. In environmental point the damages occurs by the heavy rains and earthquakes.

Mechanical Properties of Geo Polymer Concrete
Authors:- Research Scholar Kalvala Abhiram, Asst.Prof. Dr. G. Prashanth

Abstract- Concrete has occupied an important place in the construction industry in the past few decades and it is used widely in all types of constructions ranging from small buildings to large infrastructural dams or reservoirs. Cement is a major ingredient of concrete. The cost of cement is increasing day by day due to its limited availability and large demand. At the same time global warming is increasing day by day. Manufacturing of cement releases carbon dioxide. In the present study an attempt has been made on concrete and an experimental investigation on the concrete by replacing cement with FLYASH and GGBS to decrease the usage of cement as well as emission of carbon dioxide. Experimental studies were performed on plain cement concrete and replacement of cement with Fly ash and GGBS was done. In this study the concrete mix was prepared by using fly ash, GGBS, sodium silicate, sodium hydroxide. A comparative analysis has been carried out for concrete to the Geo polymer concrete in relation to their compressive strength, workability, tests on aggregate. The Geo- polymer concrete is an innovative and eco-friendly in construction. To reduce carbon dioxide emission, we are making geo-polymer concrete. The concrete made with fly ash (50%) and GGBS (50%) performed well in term of compressive strength, shows higher performance at the age of 7,14,28 days than conventional concrete. slump cone, compaction factor test was conducted to find the workability of Geo-polymer concrete and normal concrete. And test conducted on aggregate such as crushing strength, abrasion test, impact test.

Smart Parking Management System
Authors:- Sameep Karia , Tanay Temani, Varun Gajara

Abstract- Smart Parking Management System (SPMS) is a modern system that utilizes Deep Learning and Machine Learning techniques to provide efficient and effective parking solutions. The main goal of SPMS is to optimize the utilization of available parking spaces, reduce traffic congestion, and minimize parking-related problems such as illegal parking and over-parking. In recent years computer vision technologies have been developed which are very accurate and give promising results presented real-time number plate detection system using Artificial Intelligence. Smart Parking Management System is a system that will help to automate the process of parking toll collection and management. The proposed system aims to improve the efficiency of parking toll management, reduce traffic congestion, and enhance the user experience for parking. This will benefit the pay and parking facility owners as their system management will become more efficient. This paper discusses the system architecture, implementation, evaluation and accuracy of the proposed system. The paper concludes by highlighting the potential benefits of the proposed system and discussing future research directions.

Halitosis: The Antimicrobial Susceptibility Pattern of some Commercially Sold Toothpaste on Selected Isolates
Authors:- Umeoduagu, N.D, Chidozie, C.P, Ifemeje E.M. , Anazodo, C.A., Okoli, F.A., Okonkwo, N.N., Uwanta L.I., Agu, K.C., Azuka G.E.

Abstract- This study aims to investigate the antimicrobial susceptibility pattern of some commercially sold toothpaste on some selected isolates. The isolates used were Escherichia coli, Klebsiella spp, and Streptococcus spp. The commercially sold toothpaste used in this study were CU, PD, and OB. This study was conducted to assess the efficacy of these toothpaste in controlling halitosis. The results of the study showed that all the toothpaste exhibited varying levels of antimicrobial susceptibility against the various isolates tested. CU exhibited the highest level of susceptibility against E. coli and Klebsiella spp while PD showed the highest level of susceptibility against Streptococcus spp. OB had the highest susceptibility against all the isolates. The results of this study suggest that all the toothpaste tested can be used for the control of halitosis.

Development of a Hybrid Embedded Real-Time Operating System for Wireless Sensor Networks
Authors:-Associate Professor P.Murugesan, K.Senthil

Abstract- Real-time operating system plays a key role for embedded system even more for WSN due to resource constraints. So designing an energy efficient operating system dedicated to WSN which meets the requirements of all the real-time applications is still an open problem and a challenge. Due to resource constraints of WSN node and its diverse application domains, the key features of WSN operating systems (WSNOS) should be resource-aware and be configurable to adapt to each situation. Note that most of traditional embedded Real Time Operating Systems (RTOS) are resource consuming. On the other hand, the eventdriven operating systems are essentially single task systems. Consequently, they are not met the requirement of complex hard real-time applications, e.g.. Therefore, our objective is to design a configurable realtime dedicated WSNOS, which enables to adapt to an application to minimize resource consuming (memory footprint and power). Arduino based RTOS is used to design the WSN. WSN for agriculture monitoring and control system is proposed. Because of Agriculture is the back bone of India and nearly 70% of people in our country depend on agriculture. The yield of agriculture should be increased rapidly to fulfill the food requirements of population throughout the world. Now days Wireless Sensor Network (WSN) used for solving many real time problems. WSN plays vital role in many field like transport, medical, military, mobile phones, home appliances and so on. Agriculture is one of the important sources for all living things. But nowadays agriculture crops are affected due to many environmental changes. To overcome this WSN takes important role in the field of agriculture. In agriculture WSN used for monitoring, measuring temperature, irrigation system, measuring water supply and so on. WSN helps the farmer to produce the crop with high quantity and reduce the cost of yield. Agriculture gets affected by climatic change, environmental change, and natural disaster.Using WSN the soil and water management can be done. Here wireless sensors are used so the cost of implementation is very low. In this project wireless sensor nodes are used to monitor the crops. The temperature, humidity and some other theft detection can be made using sensors. This helps to increase the productivity of agriculture. The human effort is reduced by automatic process and it encourages the farmer to develop the farm land. Some components like sensor, Zigbee and some other devices are used to make the agriculture as smart. All the information’s are monitored through Personal Computer. Graphical User Interface (GUI) is developed for monitor the environment.

A Survey of the Self-Operative Trust Scheme against MANET Disruptions
Authors:- Assistant Professor Sujeet Gautam

Abstract- A mobile ad hoc network is a group of nodes that lacks an infrastructure, making it simple to set up and deploy right away. All nodes in this type of network perform the role of routers in addition to their normal operations. All nodes are allowed to move at random in a MANET because of the network’s mobility and dynamic nature, which causes frequent changes in topology. The complexity of routing the packets from source to destination is therefore invited. The numerous difficulties and problems relating to the trust value or scheme in the mobile ad hoc network are discussed in this article, and we also offer the survey for the network’s trust scheme.


DOI: 10.61137/ijsret.vol.9.issue5.101

A Selective Channel Estimation And Improvement Of The Performance In Ofdm Signal For 6g Communication
Authors:- Sanjoli Kushwaha, Assistant Prof. Shravan Kumar Namdev

Abstract- The sixth-generation (6G) wireless communication network is projected to incorporate the surface-dwelling, airborne, and naval communications into a strong network which would be more consistent, dissolute, and can provide a enormous number of devices with ultra-low potential requirements. Block chain, NOMA(non-orthogonal multiple access),quantum Machine learning(QML),edge Computing, small cells communication etc., are the highlighted technologies in the situation of beyond 5G(B5G) and 6G communication. Entire health sector will be dominated by 6G communication Technology in the upcoming era. Apart from health sectors diversified sectors are predominately occupy by 6G communication Technology. Perception of human Lifestyle are revolutionized by Artificial Intelligence based 6G communication Technology. In this paper Artificial Intelligent based 6G smart healthcare, haptic communication are briefly discussed. The key resistance of present healthcare system is time and space which is totally exhaust by implementing 6G communication technology interlinked with Internet of Things. Transportation of Patient from remote to Intensive care is facilitated by ambulance which can be serviced by normal vehicle also. Besides the hospitality for elderly peoples are very unsatisfactory most of them are died while transporting without having a proper communication. Real time date of a patient monitoring and accident detection system are lagging in the present scenario which is totally overcome by implementing AI-6G Integrated IoT based smart health care system.

Cost Efficient And Higher Accurate Intelligence Automated Highway System Using Artificial Intelligence
Authors:- Rajnandani, Prof. Shashikant B. Dhobale

Abstract- Automated highway system (AHS) is an intelligent transportation system, which removes human drivers from the operation of vehicles during driving. AHS includes control problems from the vehicle level to the highway network and its challenging opportunities for intelligent mechatronics. This technology requires extreme accuracy in vehicle location within the least times. AHS refers to a set of designed lanes on a limitedaccess roadway where specially equipped vehicles are operated under completely automatic control. It can help reduce fuel consumption and individual vehicle discharge. The AHS designed requires advanced sensors, actuators, and communication technologies. It managed transportation systems for traffic problems in big cities, congestions, accidents, delays. This technique can change the driving & safety scenario of India.

Design and Analysis of Reconfigurable Microstrip Antenna using for 5G Applications
Authors:- Pratibha Sen, Prof. MukeshYadav

Abstract-Conventional materials’ year-round availability in sufficient quantity and quality is a major challenge for construction workers in this age of energy crises and resource depletion. The need for these supplies rises steadily as the demand for shelter and living space rises at an ever- increasing rate. Researchers throughout the world are refocusing their efforts to develop locally accessible, low-cost masonry units in response to the problem. To allow for the use of low- quality materials and low-skilled labor in the mass manufacturing of building blocks, the idea of green material and construction has been properly defined in the study. In this light, there is a rising interest in using earth, as a sustainable material, in contemporary architecture. The proper disposal of trash is one of the most pressing environmental issues in the United States today. There are now millions of cubic meters of discarded plastic in our nation. Suitable accommodation of the trash in some form (as fibres) is one approach to resolving these solid waste management and environmental challenges. Basic research can examine their potential use in the production of fiber-based blocks (plastic fiber–mud blocks). Furthermore, the literature study reveals that with very few exceptions, investigations on natural fibers have concentrated on cellulose based/vegetable fibers generated from sustainable plant resources.

An Efficient Approach to Predict the User’s Interest Based upon the Current Data
Authors:- M.Tech. Research Scholar Sarabjit Kaur , Professor Gurpreet Singh

Abstract- In the field of Information Technology, finding the right information can be tough. The internet is filled with a massive amount of data, and keeping it organized is crucial but challenging. As the internet keeps growing, we have a chance to understand how people use it by looking at web access logs. To make sense of all this data, we use data mining techniques. However, web data is messy and not easy to work with using standard data mining methods. So, we came up with a way to study how users behave based on weblogs. Our method helps us mine useful information from these logs. We use what we learn about user behaviour to come up with new strategies for similar groups of users. This approach can be useful in areas like social media, online shopping, and figuring out what users are interested in from their web activity. Our experiments have shown that our method works better than older ones. The key to our success is the way we organize the data, making it easy to extract different types of information.

A Review of Anomaly Detection in Credit Card Fraud Using Machine Learning Techniques
Authors:- M. Tech. Scholar,Palak Shukla, HOD Vijay Shankar Mishra

Abstract-Credit card fraud, an escalating challenge in the digital era, poses significant financial implications for businesses and compromises the security of consumers. Traditional rule-based systems, although effective to a degree, often fall short in detecting sophisticated fraud schemes. This review delves into the applicability and advantages of employing machine learning (ML) techniques, specifically anomaly detection, to mitigate the threat of credit card fraud. Anomaly detection, with its ability to identify unusual patterns in large datasets, offers a more proactive and adaptive approach to fraud prevention. As we navigate through the vast array of literature, it becomes evident that innovations in this domain are burgeoning, from the use of autoencoders, hybrid models, to cutting-edge feature selection methodologies. However, challenges persist, especially in addressing the imbalanced nature of fraud data and the dire need for real-time detection mechanisms. This review culminates in emphasizing the transformative potential of ML-driven anomaly detection, suggesting that its continuous evolution could pave the way for a more secure financial transaction environment in the imminent future.

A Review on Finite Element Modeling and Analysis Of Gasket On Circular Bolted Flange Connection
Authors:-M.Tech Scholar Amit Kaushik, Prof.Prakash Pandey

Abstract- Flanged joints with gaskets are very common in pressure vessel and piping systems, and are designed mainly for internal pressure. These joints are also used in special applications such as in nuclear reactors and space vehicles. The connection of a fuel duct to a rocket engine is a typical application of these joints in space vehicles. Prevention of fluid leakage is the prime requirement of flanged joints. Many design variables affect joint performance and it is difficult to predict the behaviour of joints in service. Therefore, in this study, a review has been done.

Machine Learning Based – Data Analytics For Iot-Enabled Healthcare Systems
Authors:- G.Indhuja ,G.Sasireka

Abstract- One of the cutting-edge technologies that is gaining traction throughout the world is the Internet of Things. We can connect at anytime, anywhere, and with any network or service because to the enormous power and capacity of IoT. The Internet of Things (IoT) is growing to be a powerhouse for next-generation machines, and its effects may be seen in the present corporate landscape. IoT is assisting businesses or researchers in the development of solutions. By integrating the current internet infrastructure for the efficient use of resources, they communicate with smart devices and smart objects. Additionally, it has the ability to expand services and advantages for intelligent systems. Beyond M2M (machine-to-machine) situations, the interests at stake include serial communication between the network and devices for delivering extreme services. An intelligent hybrid classification algorithm for an unbalanced ECG dataset based on the Internet of Things has been discussed in this study. The AD8232 heart rate sensor, the NodeMCU ESP8266, and an intelligent hybrid classification algorithm for data categorization have been presented for an IoT-based ECG monitoring system.

ABCD Index RAMP

Re-Examining the External Drivers of Inflation in Nigeria (1986 to 2020)

Authors:-Oscar, Williams Anthony

Abstract- The study is a re-examination of the external drivers of inflation in Nigeria within the period 1986 to 2020 using a Vector Autoregressive Model. The finding of the study revealed that there is a moderate relationship between inflation and its external drivers, given the significant relationship that exist between inflation, exchange rate, oil price, and wheat price. This exposes the level of vulnerability of the domestic prices to the selected variables. Therefore, the study recommended amongst others, that there is need for the government to develop infrastructure and capital that would create domestic production of major import items in the country including oil and wheat.

Impact of Tobacco Cultivation on Rural People In Bangladesh: A Micro Level Study
Authors:-Syeda Naima Zannat, Sabrina Mim

Abstract- The study was conducted in one of the major tobacco growing areas of Bangladesh, which was Nilphamari district to identify the impact of tobacco cultivation on rural people. In total, 100 farmers were randomly selected as sample size for conducting the study. In the study areas, data were collected through semi-structured interview schedule. Tabular, descriptive statistics and profitability models were used to fulfill the objectives. The study found that, others crop (rice and corn) cultivation was highly profitable than tobacco cultivation. The average net return per hectare for tobacco was Tk. 19920 in FY 2020-2021 and Tk.15235 in FY 2021-2022 respectively. The net return for tobacco was highest in the year of 2020-2021. The average net return per hectare was for others crop (rice and corn) was Tk. 18995 in FY 2020-2021 and Tk. 29701 in FY 2021-2022 respectively. The net return for others crop was highest in the year of 2021-2022. Benefit cost ratio, was 1.16 and 1.13 in the year of 2020-2021 and 2021-2022 respectively which was profitable. Besides, we saw farmers faced some health issues. The major health issue were headache faced by 91% farmers. Others health issues were eye imitation, coughing etc. The major constraints were rainfall. Others constrains were no machinery, wholesaler didn’t give the price in time etc.

 

Determinants of Urban Households Saving in Hawassa City Sidima Regional State Ethiopia
Authors:-Birhan Densisa

Abstract- In developing countries like sub-Saharan African countries has lowest saving rate in developing countries. While figures vary from country to country, grass domestic savings in the region averaged about 18 percent of gross domestic product in (2005) compared with 26 percent in south Asia and nearly 43 percent in East Asia and pacific countries according to (WB) estimates.This study would be analyzing the determinants of household saving in the case of Hawassa city and to easily undertake the research, Tabor, Menaherya and Tula subcity was selected as the study area through using Simple random sampling (lottery) as well as multi- stage probability Sampling technique method because the target population is homogenous and large in area. so that the study incorporate the sample by chance.98 households were selected asa sample size through using the Yamane Taro formulaand in order to include the representative population, lottery method was easily adopted The data would be collected through primary sources and the data analysis would be conducted by using Descriptive and Econometric method of analysis. Descriptive method of analysis would be analyzed through using a simple table, frequency, percentage, charts. Econometric analysis would be also analyzed through diagnostic tests such as of data as well as Binary choice Model (tobit censored regression) estimation from Regression result. In order to conduct this research work the researcher would be applying 10% level of significance. Finally, the study would be recommended In order to encourage household saving Tradition (Improvement) in this study Area the finding result show that income, age and Family size is the Major Variable, which affect positively and significantly. The other variable that is employment condition affects the household saving performance significantly and negatively at 10% level of significance.

Mechanical Design of a Novel Low-Pressure Turbo Vapor Compressor
Authors:-Mostafa Shawky Abdel Moez, Amin Mobarak

Abstract- Optimum turbine’s position with respect to the compressor in TVC was selected for minimum work difference between them and maximum efficiency after including all types of losses. The current work objective is to make a complete mechanical design of the TVC system, including the starting system, bearing, blades assembly, shaft, clutch, and assembly of TVC. This occurs by discussing the main output results for three-dimensional simulation for turbo-vapor compressors such as toques, moments, and forces in three coordinates x, y, and z. Modal analysis is conducted for the turbovapor compressor at different bearing stiffness values to estimate the critical rotor speeds to be passed during system run-up. Finally, the static structure tool in Ansys is used to determine the values and the directions of forces at both bearings’ stresses using Von Mises stress analysis and deflection for the turbo-vapor compressor. Figure 3-2 shows the layout for TVC. The TVC design was developed under the supervision of Dr. Antoine Dimitri the lecturer at mechanical design and production department.

Influence of Mass Flow Rate on the Performance of Solar Flat Plate Collector in Forced Convection Mode
Authors:- Research Scholar Vikram Singh, Associate professor Bhupendra Gupta

Abstract- A Solar Water Heater (SWH) is a typical device that converts solar energy into thermal energy to heat a heat transfer fluid such as water, non-freezing liquid or air for domestic usage. Solar energy collectors are special kinds of heat exchangers that transform solar radiation energy intothe internal energy of the transport medium.To increase further the thermal performance of solar collectors the interaction between the radiation and mass flow rate was employed in an experimental study on a solar water heater system to evaluate better results. In this research work, experimental analysis has been carried out at different levels of mass flow rate concerning solar irradiance level. Results indicate that efficiency decreases with a decrease in factor x, but it is maximum at a low value of mass flow rate.

A Review On Cfd-Model Of The Piston Assembly In A Diesel Engine For The Analysis Of Piston Ring Dynamics,Mass Transport And Friction
Authors:-M.Tech. Scholar Amit Yadav, Prof. Prakash Kumar Pandey

Abstract- FEA is frequently used to characterise the stress distribution on an internal combustion engine’s piston. FEA is performed with the help of CAD and CAE software. Its major goals are to explore and analyse the thermal and mechanical stress distribution of the piston throughout the combustion process in such an actual engine. In this paper, a review on CFD-model of the piston assembly in a diesel engine for the analysis of piston ring dynamics, mass transport and friction has been done.

A Review onProperties of Self Compacting Concrete Using Recycled Coarse Aggregate
Authors:- Nishant Patil, Prof. Mahroof Ahmed

Abstract- Recycling of construction and demolition waste is a promising way towards sustainable construction. Coarse recycled concrete aggregates have been widely studied in recent years, and reported as a suitable alternative for natural coarse aggregates. However an extensive study of use of recycled aggregate in a new generation concretes is a relatively scarce field. Hence this study is a step forward which justifies and encourages the use of recycled aggregate in self compacting concrete to create a sustainable solution to warrant the problem of environment protection. In this paper the effect of coarse recycled concrete aggregates on the fresh and mechanical properties of self compacting concrete are investigated.

Intelligent Fraud Detection In Financial System Using Machine Learning Technique
Authors:-PG. Scholar N.Suganthi, Prof..S.P.Audline Beena

Abstract- Fraudulent financial statements (FFS )are the results of man ipulating financialelements by over valuingin comes,assets,sales, and profits while underrating expenses, debts, or losses. To identify such fraudulent statements, traditional methods,including manual auditing and inspections, are costly, imprecise, and time-consuming. Intelligent methods can significantlyhelp auditors in analyzing a large number of financial statements. In this study, we systematically review and synthesize theexisting literature on intelligent fraud detection in corporate financial statements. In particular, the focus of this review is onexploring machine learning and data mining methods, as well as the various datasets that are studied for detecting financialfraud. We adopted the Kitchenham methodology as a well-defined protocol to extract, synthesize, and report the results.Accordingly, 47 articles were selected, synthesized, and analyzed. We present the key issues, gaps, and limitations in the areaof fraud detection in financial statements and suggest areas for future research. Since supervised algorithms were employed more than unsupervised approaches like clustering,the future research should focus on unsupervised,semi-supervised,aswellas bio-inspired and evolutionary heuristic methods for anomaly (fraud) detection. In terms of datasets, it is envisaged that future research making use of textual and audio data.While imposing new challenges,this unstructured data deserves further study as it can show interesting results for intelligent fraud detection.

CFD Analysis of Double Pipe Heat Exchanger
Authors:- M.Tech. Scholar Ramesh Kumar Badhai, Prof. Ritesh Kumar

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.

Commercial and Technical Elements Evaluation of Highway Construction with Optimization Its Performance
Authors:- Amrendra Ranjan, Umesh Rathod

Abstract- The highwaynetworks were built to connect the rural people to the town area or to other destination required by the local residents. Normally the highwaywill be developed to connect or increase the socio-economic opportunity in rural area. The green road is one of the key areas that can be look into to create the sustainable concept based on three key aspects namely social, environmental and economic factors. The main focus of the commercial and technical elements evaluation of highway constructionis to increase the profits using more efficient resources, especially materials, improving the quality of life by meeting the national needs of social aspects and protecting the environment from the effects of CO2 emissions and efficient use of natural resources for environmental aspects. Therefore, it is important that stakeholders include sustainability criteria in their projects. The application of a sustainable concept on the road can be assessed by the green road evaluation tool. Therefore, the main aim of this study is to build review of commercial and technical elements to evaluate and declare highway.

Review of TVET Education in Afghanistan
Authors:- Fatema Haidari, Mortaza Kazemi

Abstract- Technical and Vocational Education and Training (TVET) is crucially vital in competitive, knowledge driven economy and rapidly changing job markets. Gap and mismatch of job requirements and what the education and training are providing leads to skills gaps, unemployment and less developed and broken economy. From global prospective, knowledge driven economy made the TVET significantly important for economic prosperity and sustainable development of each country. Hence, the primary objective of this study is to review the history, ups-and-downs, challenges, and future prospective of TVET in Afghanistan. Present study has been reviewed the TVET education based on three standpoints such as accessibility, quality and efficacy. The result shown that in spite of recent development in TVET education in Afghanistan, there is a lot needs to be done to make the system based on employers need and job market requirements. The high rate of unemployment and the practice of traditional methods in many industries demonstrate the mismatch of education system, particularly TVET with the job markets. Moreover, the study will help the TVET practitioners, teachers and students to have a clear vision about TVET in Afghanistan.

Analysis Of Health And Safety Agents Influence On Health And Safety Performance In The Indian Construction Industry
Authors:- Prof. Dr.K.Velusamy, Asst.Prof. R.Kabilan , Yuvan Aravind S

Abstract-Health and safety issues have always been a major problem in construction. industry. In previous record construction industry is found one of the most dangerous field in most developing countries, India is the one of them. In Indian construction industry worker do not have enough knowledge in health and safety on construction sites, they do not know welfare facility, health and safety plan and policy, health and safety management system and there are no health and safety compliance on site, if it given on construction site worker do not use this facility. they don’t know how much impact of health and safety knowledge and compliance on project performance. Building construction workers health and safety knowledge and compliance is poor. Fatalities, injuries, and illnesses continue to occur in the construction industry (CI), despite efforts made by clients, designers, and contractors. The lack of collaboration between these project actors and construction health and safety agents (CHSA) remains a challenge for both construction professionals and academics. Given the urgent need for CHSA to collaborate with other construction project members, this project proposes a model for improving CHSA collaboration and its influence on health and safety (H&S) performance.

Develop A Simulation Model And Signal Timing Improvements To Study Traffic Patterns And Identify Areas Where Congestion Occurs
Authors:- Raghuveer Badal, Dr. Sunil Sungandhi

Abstract- In recent years, traffic congestion prediction has led to a growing research area, especially of machine learning of artificial intelligence (AI). With the introduction of big data by stationary sensors or probe vehicle data and the development of new AI models in the last few decades, this research area has expanded extensively. Traffic congestion prediction, especially short-term traffic congestion prediction is made by evaluating different traffic parameters. Most of the researches focus on historical data in forecasting traffic congestion. However, a few articles made real-time traffic congestion prediction. This paper systematically summarises the existing research conducted by applying the various methodologies of AI, notably different machine learning models. The paper accumulates the models under respective branches of AI, and the strength and weaknesses of the models are summarised.

A Critical Analysis of Machine and Deep Learning Techniques for Gender Identification
Authors:- Yodhant Singh

Abstract- Gender classification has become a topic of growing interest, primarily because it can provide valuable insights into the distinct social activities and behaviors associated with males and females. Particularly, when it comes to visual representations, gender classification, especially in facial recognition, presents a unique set of challenges. This process involves determining an individual’s gender based on their physical appearance, and it has gained prominence due to the wealth of information gender can offer about societal behaviors. In recent years, the applications of automatic gender classification have expanded across various domains. For instance, in conservative societies, such a classification system finds utility in secure environments, where accurately identifying an individual’s gender becomes crucial, particularly in sensitive areas, to prevent unauthorized access and maintain safety. Additionally, this technology is employed in scenarios involving gender segregation, such as in female railway compartments, gender-specific marketing strategies, and within certain cultural or religious contexts like temples. The evolving capabilities of gender classification systems hold the promise of facilitating a wide range of applications, with potential future developments aimed at enhancing accuracy and inclusivity while addressing privacy and ethical concerns.

An Automated Fire Detection and Reporting System Based on AI and IoT Technologies
Authors:- Abubakari Abdul-Rahaman, Peter Awonnatemi Agbedemnab,Jacob Azaare

Abstract- Most of the fires that engulf public facilities and cause more damage to properties usually happen after working hours or when people are asleep, implying that, humans play a central role in fire reporting. In this paper, a Location Based Smart Fire Reporting system capable of eliminating human involvement is proposed. The proposed system employs two technologies, namely, the Internet of Things (IoT) and Artificial Intelligence (AI). The AI looks at the integration of sensors with the Arduino Nano board that works in converting the analogue data into digital data for decision making. The IoT technology communicates the converted digital data to the appropriate authorities or users. The proposed system is made up of a GPS sensor, Arduino Nano micro-controller, two temperature sensors, Gas (MQ4) Sensor, smoke (MQ5) sensor and GSM SIM900 module. A test implementation of the proposed system was conducted and it came to light the system able to detect naked fire, flames, gas leaks and smoke; a Short Message Services (SMS) is also sent to the users/owners with the exact GPS location coordinates of the fire incident. Another functionality of the system is its ability to disconnect power supply to an affected building whenever, fire is detected. There are threshold values set for each sensor, above which triggered the beeper. The system takes averagely 3ms to send and deliver messages in stable cellular network area.

DOI: 10.61137/ijsret.vol.9.issue5.102

A Comparative Study Of Gain And Phase Margin To Analyze Stability Of A System From Its Corrosponding Transfer Functions And The Plot Of Power Spectral Density Curve By Using Neumerical Results Obtained Fromcircular And Linear Convolutions And Fast Fourier Transformof Real And Complex Sets Of Neumerical Data Sequences
Authors:- Abir Chakraborty Senior Research Fellow

Abstract- This work is an application where we have tried to combine the basic concept of control system engineering with digital signal processing engineering. Actually there are so many application available regarding digital signal processing, out of all the applications we have selected only one basic terminology that is “CONVOLUTION” and “FAST FOURIER TRANSFORM”. That’s why we have used two very common convolution and transformation techniques Linear and Circular convolutions. The results of these two convolutions that we have generated have been used in control system engineering purpose. For our convenience we have used both real and complex data’s for both types of LINEAR and CIRCULAR convolutions as well as fast Fourier transformation then the outcomes that we have got after convolutions have been used as inputs for generating transfer functions. Then only from that transfer functions we have calculated the GAIN and PHASE margin related parameters and pole-zero values. In this way we have coupled one concept of digital signal processing with control system to show which data sets(REAL DATAS or COMPLEX DATAS)generate a stable transfer function. So our main aim is to judge the stability of a systemby using POLES and RELATIVE STABILITY [3] ANALYSIS. Side by side we have plotted the power spectral density of convoluted datas obtained after circular and linear convolutions.

Hazard Identification, Risk Assessment And Control Measures As An Iron Ore Pelletizing Industry
Authors:- Prof. Dr.K.Velusam, Assistant Prof. R.Ravishankar, Abdul Rasheed P

Abstract- With the growing numbers of iron ore pelletization industries in India, various impacts on environment and health in relation to the workplace will rise. Therefore, understanding the hazardous process is crucial in the development of effective control measures. Hazard Identification, Risk Assessment, and Control measures (HIRAC) acts as an effective tool of Occupational Health Assessment. Objective: The aim of the study was to identify all the possible hazards at different workplaces of an iron ore pelletizing industry, to conduct an occupational health risk assessment, to calculate the risk rating based on the risk matrix, and to compare the risk rating before and after the control measures. From the data sources analysis make a an average, risk reduction was about 6.33 points lower after taking control measures. The hazards having high-risk rating and above were reduced to a level considered As Low as Reasonably Practicable (ALARP) when the control measures were applied, thereby reducing the occurrence of injury or disease in the workplace.

Reducing Co2 Emissions with Optimized Logistics in Super Express Way Transportation
Authors:- Ashutosh Dwivedi, Shashikant Dhoble

Abstract- Carbon emissions from the logistics industry have been rising year after year. Correct handling of the relationship between economic development and environmental protection is of great significance to the implementation of green logistics, which is an important component of China’s strategy for strong transportation. This paper focuses on the evaluation of the carbon emissions efficiency of logistics industry from a new strong transportation strategy perspective. A super-efficiency slack-based measurement (Super-SBM) model and Malmquist index are combined to evaluate the static and dynamic carbon emissions efficiency of the logistics industry.

Enhancing Teacher Education Quality for Sustainable Educational Development
Authors:- Asst.Prof. Parama Kundu, Prof. (Dr.) Shauli Mukherjee, Asst.Prof.Pranay Pandey

Abstract- The quality of teachers is undeniably the cornerstone of any successful education system. This assertion is based on the premise that the effectiveness of teaching and learning processes hinges on the competence, skills, and dedication of educators. Teachers serve as the invaluable assets of an education system, playing a pivotal role not only in shaping the individual development of students but also in adapting to and driving societal changes. This paper explores the vital significance of teachers in the holistic development of society and the establishment and maintenance of higher education standards. Teaching is a dynamic, interactive, and intentional process. Teachers occupy the unique interface through which knowledge, skills, and values are transmitted to the next generation. Given this central role, teacher education emerges as a linchpin in the reform and fortification of any country’s education system. The National Council for Teacher Education (NCTE) assumes a pivotal responsibility in initiating measures to render teacher education at various levels adaptable to ongoing societal developments while addressing concerns about educational quality. To enrich educational quality at all levels, the Government of India has been steadfastly directing its focus toward the pursuit of excellence in higher education and teacher preparation. Numerous endeavors have been undertaken to elevate the status of teacher education in India. The central intent of this paper is to underscore the contemporary challenges in teacher education, offering insight into the pressing issues of the present era. Moreover, it suggests feasible measures aimed at enhancing the quality of teacher education in India. In doing so, it is expected that this paper will contribute to the collective endeavor of nurturing a cadre of educators who can effectively shape the future of the nation by providing students with the knowledge, skills, and values necessary for success in a rapidly changing world.

Forecasting S&P 500 Index Closing Price using LSTM and fin BERT
Authors:- Jibin Rajan Varghese, Divya Susan Thomas

Abstract- Stock market prediction is a complex task that is invaluable to economic activity across the globe. We are currently at the end of a decade-long bull run where the stock market experienced a relatively steady rise and lower volatility. As we enter an era with more stock price fluctuations, a good price predictive model is important, especially for participants in inverse and leveraged Exchange Traded Funds (ETFs) to reduce risks and make gains in the market. Since there was no study that used LSTM trained on both structured and unstructured data to predict the Standard & Poor’s 500 index, this study focused on training single and multi-layer LSTM models to predict the Standard & Poor’s 500 index closing price utilizing historical, macroeconomic and technical data as well as using sentiment analysis of financial news obtained using FinBERT. The goal of this study was to find the architecture of the LSTM model with the highest accuracy in forecasting tomorrow’s closing price of the Standard & Poor’s 500 index and investigate if the performance of the LSTM model could be improved by adding unstructured textual information such as sentiment extracted from financial news using FinBERT, which is a pre-trained NLP model that has been shown to outperform all current state-of-the-art models in analysing sentiment of financial text.

Review on the Design and Fatigue Analysis of a Wing Spar
Authors:- Assistant Prof. Mansha Kumari, Happiness Felix Kosamu, Ajay Kumar Mandal, Grace John Kisunge, Misagomaureen Peter Baligira

Abstract- An aircraft’s structure is quite complex and involves many intricate interactions between its parts. One of the reasons for its complexity is due to the fact that these said parts are liable to several loads. Among such loads are aerodynamic loads, fatigue loads, torsion loads and many others. An extremely important part of an aircraft which is subject to some of these loads is the wing structure, which is subject to loads like fatigue loads. In this review paper, we will be delving deeper into a wing spar, and analysing its design and how it is affected by the fatigue load acting on it. A wing spar is of great importance in a wing as it is where majority of the loads acting on the wing act on. So, finding an optimum design of the spar with high fatigue life is crucial. A fatigue failure in a structure can led to the deformation of the structure which can in turn jeopardize the entire structure thus the importance of fatigue analysis.

Parking Management System Using Cloud Computing
Authors:- Priyanka H. Kathar , Abhilasha Mishra, Rashmita Srinivasan , Amit Rawate

Abstract- This application is a special system for smart parking reservation and security maintenance commercial car parking area in an urban environment. Now a day’s congestion of traffic increases rapidly with the increasing growth of population. With respect to the number of population’s usage of cars also increased. Due to more usage of car the traffic congestion occurred on the road. The parking lot has experienced congestion in addition to the road. Because it takes longer to find a parking spot that is free to part the vehicle. Hence, we loss certain amount of time period and also made more than 80percent of fuel wastage of in the empty parking lot in parking area. To solve this problem, we need especial system in the parking area to measure empty space, which can able to deliver services and show the information to the users who are looking for the empty space for Parking lot with less time spend. Reservations are made solely by the user. Thus, the user discovers a vacant parking lot and makes a reservation using an Android application with the driver’s own knowledge of the parking lot. With the removal of the Standalone Parking Lot Application for the Enterprise, information or reports will be available everywhere with an Internet connection with only a single click.

Data Mining Techniques: A Review of Literature
Authors:- Prof. S. B. Bele, Vaishnavi G. Shinde, Yash S. Kalaskar, Dipali V. Mendhe

Abstract- Data mining is very important and useful. It involves using various algorithms to extract valuable knowledge and insights. It allows us to obtain diverse information from datasets and use it to perform various tasks.

Low Cost Industrial Automation in Education Sector
Authors:- Ashwaghosh Ramteke

Abstract- The current challenges in industrial automation education revolve around the constraints of traditional PLC programming instruction. The existing methods often fail to provide students with practical experiences due to limitations in budget, accessibility to hardware, and an emphasis on theoretical knowledge. Bridging the gap between theory and application is crucial for students to grasp complex concepts effectively. Moreover, the demands of Industry 4.0 require the integration of IoT components, calling for innovative solutions that adapt to the evolving industrial landscape. Accessible and hands-on training methodologies are key to preparing students for the practical demands of the industry, necessitating cost-effective and interactive educational approaches that combine theoretical knowledge with real-world application.

Review of DRA Based Micro Strip Antenna Design and its Performance Parameters Evaluation
Authors:- Niranjan Gujrati, Ashish Suryawanshi

Abstract- Present scenario of communication, all wired ones becoming wireless. So, to achieve efficient and affordable communication in wireless technology, compact and efficient radiators required. One of the efficient radiators is dielectric resonator antenna (DRA). Almost all the applied power will be lost in the radiated fields only, with this attractive feature DRAs become much popular in wireless communication field at microwave frequencies. In this project, new type of compact DRAs is designed for popular wireless applications of L, S, C and higher band application. This project covers the design of DRA which including all parametric studies of the return loss, radiation patterns, gain and directivity for specific wireless application. DRAs became very popular in the core sectors of a country like defense, military, radar and especially for millimeter wave applications.

Concept Note for Skills Based University Course Structure
Authors:-Dr. Lalit Narayan

Abstract- Indian education system is undergoing various revolutionary reforms for adopting value based and skill based higher education to contribute effectively in the demand supply of economic and social development. In the light of various guidelines and policies notified by higher and skill education regulators and government authorities, in which National Education Policy (NEP) 2020, National Credit Framework (NCrF), and National Skill Qualification Framework has provided key inputs to shape and plan the implementing direction for skill based higher education. In the present paper it is is attempted to address the need of how to design the course structure of a particularly skills University or any skill based university in the light of NEP 2020, NCrF & NSQF guidelines.

Stop the Israel Palestine War and Russia Ukraine War Its Time to Ban Atom Bomb and Hydrogen Bomb by World Countries or by United Nation Organization
Authors:-Asst. Prof. Dr. P. Deivanayagam, Dean Dr. Selvaraj,Vice Principal Rajarajan

Abstract- Over the past one year and six months Russia Ukraine war has been taking place. More number of people died, and migrated from their place to other place war is becoming danger and danger to the people more number of people died. By the help of jews America sent the battleship to Israel, china send the battle ship to Palestine.More number of people died in Palestine save the muslims, from 2023 its time to ban atom bomb and hydrogen bomb by world countries, save the muslims. In this article we discuss about to stop the war.

Inventory Control- Supply Chain Solution: Case Study
Authors:- Dr. S. Vasantha, Dr.M.Thaiyalnayaki, A.Yalini

Abstract- Supply chain management is a fundamental cornerstone of business operations, and effective inventory control plays a pivotal role in ensuring its success. This article presents a comparative analysis that sheds light on the critical role inventory management plays in enhancing supply chain efficiency. By analyzing the inventory control practices of TVS Supply Chain Solutions alongside industry giants like Amazon, Walmart, and FLIPKART, it becomes evident that precise demand forecasting, real-time inventory visibility essential in addressing the evolving needs of customers. These case studies collectively emphasize how investment in inventory control analysis and supply chain optimization can empower organizations to swiftly respond to changing market dynamics, trim operational costs, and, most notably, bolster profitability and customer satisfaction.

Inventory Control- Supply Chain Solution: Case Study
Authors:- Miss. Shivani D Gajjar

Abstract- There are approximately 315 million students in the world. Puzzles help them for brain development. But in the world full of stress, they might get frustrated if unable to solve the cube. This frustration increases as size of the cube increases. Apart from students there are many people who have dreams to become an expert in cube solving to set the records in live shows. My research aim is, to give shoulders to them dealing with their puzzle challenges more easily and efficiently. The product of current system which provides fix sized cube along with optimum solution to reach the solved state from the current one. The product an online system which provides user defined sized cube along with optimum solution to reach the solved state from the current one. Our system will be composed of three functions user can run successively. First function will allow user to play with cube rotating layers. Second function will be scanning the cube through camera. Third function will be to receive the solution in optimum steps. There will be no data processing on the middle device, rather it will be used for transmitting the data to the web server for each functions with the help of machine learning and optimum path finding.

Authors:- Dr. S. Vasantha, Dr.M.Thaiyalnayaki, A.Yalini

Abstract- Supply chain management is a fundamental cornerstone of business operations, and effective inventory control plays a pivotal role in ensuring its success. This article presents a comparative analysis that sheds light on the critical role inventory management plays in enhancing supply chain efficiency. By analyzing the inventory control practices of TVS Supply Chain Solutions alongside industry giants like Amazon, Walmart, and FLIPKART, it becomes evident that precise demand forecasting, real-time inventory visibility essential in addressing the evolving needs of customers. These case studies collectively emphasize how investment in inventory control analysis and supply chain optimization can empower organizations to swiftly respond to changing market dynamics, trim operational costs, and, most notably, bolster profitability and customer satisfaction.

A Critical Study of Wireless Power Transfer in Electric Vehicles: A Review
Authors:- Nuzhat Jahan, Dr. Mayank Mathur Professor

Abstract- The fields of magnetism and resonance are crucial to the operation of Electric Vehicle Wireless Communication (EVWC) devices. A magnetic field is produced when electricity flows through a coil of wire, just as it is in a transformer. For Wireless Power Transfer (WPT) to work, it’s necessary to position two coils in such a way that one’s magnetic field induces a current in the other. Unless the coils are very close to one another and aligned in a straight line, inductive power transfer is inefficient. In this paper work related to wireless charging system proposed by various researchers is explored. Concept of Static and dynamic charging, Inductive power transmission, wireless power transmission techniques including inductive and capacitive coupling, far field techniques like Radio, microwave and laser techniques are also presented.

Efficient Wireless Power Transfer Techniques for Electric Vehicle Charging
Authors:-Nuzhat Jahan, Dr Mayank Mathur Professor

Abstract- The increased availability of charging stations has made EVs more accessible. However, as technology progresses, the demand problem on the electrical infrastructure becomes more pressing. One of the cutting-edge methods being explored to deal with the issue of rising power usage is vehicle-to-grid (V2G) technology. With the development of vehicle-to-grid (V2G) technology, electric vehicles may one day be able to sell any excess energy back to the grid, recouping some of the cost of their charging infrastructure. The use of renewable energy as a direct replacement for fossil fuels in transportation has become feasible because to advancements in V2G vehicle-to-grid technology. Recent developments in automation have made it possible to wirelessly charge electric automobiles. Electric vehicles’ ability to connect to the grid is dependent on wireless networking due to transmission losses, misalignment, and security issues associated with electric power. In this paper a look can be taken at the pros and cons of several different wireless power transmission techniques.

Review of TVET Education in Afghanistan
Authors:-Fatema Haidari, Mortaza Kazemi

Abstract- Technical and Vocational Education and Training (TVET) is crucially vital in competitive, knowledge driven economy and rapidly changing job markets. Gap and mismatch of job requirements and what the education and training are providing leads to skills gaps, unemployment and less developed and broken economy. From global prospective, knowledge driven economy made the TVET significantly important for economic prosperity and sustainable development of each country. Hence, the primary objective of this study is to review the history, ups-and-downs, challenges, and future prospective of TVET in Afghanistan. Present study has been reviewed the TVET education based on three standpoints such as accessibility, quality and efficacy. The result shown that in spite of recent development in TVET education in Afghanistan, there is a lot needs to be done to make the system based on employers need and job market requirements. The high rate of unemployment and the practice of traditional methods in many industries demonstrate the mismatch of education system, particularly TVET with the job markets. Moreover, the study will help the TVET practitioners, teachers and students to have a clear vision about TVET in Afghanistan.

A Study on Hybrid Offices and Workforce
Authors:-Muskan Singh

Abstract- In the IT industry, the hybrid office and workforce model, which mixes remote work and in-office employment, has gained popularity. The following are some of the key effects this model may have on the industry, Employees have more freedom to balance their personal and work lives thanks to the hybrid approach. When necessary, they can work from home, which can cut down on travel time and boost output. Employers now have access to a wider talent pool because proximity to one another is no longer a barrier to employment. As a result, teams will likely be more diverse and may be better able to solve problems. Because employees may feel under pressure to be available and productive all the time, the hybrid approach can potentially increase the risk of burnout. Employers must be conscious of this risk and take precautions against burnout, such as fostering work-life balance and offering mental health support. In recent years, the IT industry has witnessed substantial changes relating to hybrid work. Due to the COVID-19 pandemic, which has resulted in a significant increase in remote work, many IT organizations have had to quickly adapt to hybrid work patterns.
The hybrid office is becoming more and more popular than ever. A hybrid office comprises of some employees who work in the office and others who work from home, giving workers more freedom over where and when work is done. The hybrid office is a flexible work setting where some employees must remain there to accomplish their jobs, some employees prefer to work there, and some employees may still need to stop by sometimes.
The development of a flexible workplace paradigm known as a hybrid workspace or hybrid office is necessary to serve a distributed workforce that includes both in-office and remote workers. The COVID-19 outbreak has significantly raised the need for hybrid workplaces. Businesses are taking their time to establish a more rigorous workplace even though other nations have reduced the nationwide lockdown. Many people already use the blended approach, while some people only work remotely. The main factors that affect work performance at the organizational and individual levels are covered in the study. Employees may opt to work in the office, remotely (most frequently from home), or in a hybrid workplace, depending on where they are most productive.
Our flexibility and support are the most important components of a hybrid workplace, in addition to a combination of in-office and remote workers. This study aims to provide light on workplace flexibility’s effects on productivity as well as its broader consequences on people and enterprises. A hybrid work paradigm for a particular employee is a timetable that combines in-office and remote work. deciding on a time to leave for work. Sometimes an employee will elect to work from home. There is no hybrid model that works everywhere. Based on the requirements of the company and the person, each organization creates a hybrid model. Employees can utilize the “hybrid work model,” a work style that combines working from home while traveling, and in the office. An effective hybrid work structure encourages independence, adaptability, high performance, collaboration, wholesome interpersonal interactions, and beneficial work practices.
Since the outbreak of the epidemic, businesses have had to adapt to stay in business. Most of this change involved going remote. When lockdown orders were issued, businesses were compelled to implement a WFH model, or at the very least, a largely WFH structure. However, many workers are returning to work now that restrictions have been eased. Nevertheless, some staff work in the office while others continue to work remotely due to capacity and location limits. Even though the concept is not new and was utilized by numerous companies before COVID, the hybrid office is quickly becoming the “Next Normal.” According to a Xerox poll, more than 50% of businesses intend to change their WFH policy in the future year.
The study’s objectives are to investigate:
• To determine how much hybrid employees believe that adopting a hybrid working pattern impacts their subjective health.
• To understand the effects of mixed remote work arrangements—both good and bad—on workers’ well-being.
• To understand the aid by the organization for the health of hybrid employees and the efficacy of these strategies.

ABCD Index RAMP

Blind Signature Scheme Based on MGES
Authors:-Demba Sow

Abstract- This paper presents a Modified Generalized ElGamal Signature Scheme (briefly called MGES) and introduces a new Blind Signature Scheme based on the MGES scheme. The security of our modified and blind schemes is based on the discrete logarithm problem (DLP). We also show that our new blind signature scheme verifies all the properties of blind signature.

ABCD Index RAMP

DOI: 10.61137/ijsret.vol.9.issue5.103

Car Accident Alert System via GPS Assistance
Authors:- Vaishnavi Desai, Shravani Dhamale, Divya Hinge , Prof. Shilpa Dhanorkar

Abstract- In this review paper, we explore a technology that helps improve road safety and accident response by using GPS and sensors. Imagine a system that can automatically alert emergency services when a car is involved in an accident. That’s what we are looking at. The idea of detecting car accidents is not new, and the automotive industry has made significant advancements in this technology. This paper aims to contribute to this field of technology. Here, we attempt to identify accidents using an Accelerometer, a device that helps us determine the vehicle’s orientation. If the values of the x, y, and z parameters exceed predefined thresholds, it triggers an alert. When this happens, our code is executed to send notifications and SMS alerts. This system makes it easy to detect the location of an accident. If the system detects a significant impact, it sends the accident’s location via GPS to emergency services for assistance.It promises to redefine road safety, offering a robust, automated, and efficient solution to save lives and reduce accident severity.

Automated Controlled Timetable Using Cloud & Gesture Recognition
Authors:- Pratik Bharambe, Asst.Prof. Neha Gaurav , Nivrutti Damdhar , Prof. Varsha Kshirsagar ,Dr. Nandini Dhole

Abstract- The digital notice board is an innovative solution that utilizes the latest technologies to facilitate paperless information transfer. This is a modern interactive gesture controlled digital notice board with a timetable management system. A timetable management system that can send reminders to faculty, reschedule lectures, update the notice board, and send notifications via Gmail and WhatsApp. This project includes a website that utilizes cloud storage and databases to manage all of these operations. The timetable management system was also accessed via the website, and a gesture-controlled mouse tracking system was developed on the admin side for easy access.

Enhancing Urban Mobility through Intelligent Parking Space Occupancy Management
Authors:- Palak Suhane, Shivam Tripathi, Shushank Gautam, Swastik Pandey, Yash Bisen, Assit. Prof. Shahida Khan

Abstract- This paper explores the use of machine learning techniques to analyze and predict parking space occupancy. The research involves collecting real-time data from urban parking lots and applying various machine learning algorithms to model historical occupancy patterns and forecast future availability. The study aims to address urban parking congestion, reduce search times for parking, and contribute to traffic management and environmental sustainability. The findings have the potential to revolutionize urban parking management and improve urban living.

Leveraging AWS Serverless Technologies to Modernize Legacy Applications and Enhance Operational Efficiency
Authors:- Sateesh Kumar Undrajavarapu

Abstract- The importance of AWS serverless technologies is their capacity to update and revamp applications providing effective solutions to address the issues of antiquated systems and improve operational productivity. This research delves in to exploring the utilization of AWS serverless technologies, like AWS Lambda and Amazon ECS Fargate to update applications and boost efficiency. By tackling the obstacles posed by legacy systems, such as upkeep expenses, scalability challenges and slow adaptability the study showcases how serverless architectures can streamline operations cut costs and enhance performance. Drawing insights from real world case studies it presents a roadmap for transitioning to serverless architectures encompassing evaluation, planning and execution phases. It also touches upon security and sustainability aspects by underlining the energy saving benefits improved compliance measures and reduced environmental footprint offered by serverless solutions. Furthermore it delves into creating tools for performance evaluation and models for cost optimization to ensure success in the run. The research outcomes indicate that AWS serverless technologies present a budget friendly method for revamping legacy systems with promising applicability, across diverse sectors.

DOI: 10.61137/ijsret.vol.9.issue5.200

Current Measures of Supplier Relationship Management Performance: Implications of Organisation Theories
Authors:-Lamin B Ceesay

Abstract- This conceptual review examines measures of supplier relationship performance through two main lenses: first, by exploring the current measures of supplier performance, and second, by assessing the impact of supply chain management (SCM) theories and total quality management (TQM) practices on this performance. The review suggests that strategic supplier relationship management (SRM) plays a crucial role in SCM by incorporating key elements such as supplier integration, information sharing, communication, and collaborative partnerships, all of which influence supplier performance quality. From a practical standpoint, the review stresses the importance of stakeholders in the SCM value chain fostering closer relationships with strategic suppliers. This approach encourages long-term, cooperative partnerships rather than purely transactional, arm’s-length arrangements, which can enhance the capabilities and performance of suppliers. In its conclusion, the review highlights that supplier relationship performance is measured across three phases: supplier selection, development, and termination. Each phase carries distinct implications for relational performance. While many SCM theories complement each other, some older theories have diminished in relevance, while TQM theories hold significant potential to enrich SCM practices and theory. However, the review notes that TQM principles are underutilized in contemporary SCM literature.

Dairy Waste Water – A Case Study
Authors:-Assistant Professor Vikrant Kumar, Assistant Professor Mohd Nayeem Ali, Assistant Professor Anjali Jakhar

Abstract- Environmental Engineering & Pollution control are the growing concerns of today. Rising population technological, economical and industrial revolution and changing life style has lead to various types of environmental problems, water pollution, land pollution, Air pollution, nuclear pollution, sound pollution including spiritual pollution are the aspects of pollution today. Out of which, water pollution is most concerned with civil engineering. Water treatment, supply and waste water treatment of domestics and industrial sources is very important aspect of civil engineering. Present work deals with the industrial waste water treatment. The major cause of water pollution was dairy effluent; Dairy waste water is diluted in milk. It contains BOD, COD, total solids dissolved solids and sometimes PH and oil-grease as highly biodegradable and COD/BOD is less than 1.5.

DOI: 10.61137/ijsret.vol.9.issue5.385

Soil Health and Agroecology: Techniques, Impacts on the Quality of Soil, and Carbon Segregation
Authors:-Darshika Sharma, Zehra Husaini, Shayma Saifi

Abstract- Soil health is critical to sustainable agriculture, ecosystem stability, and climate change mitigation. Regenerative agriculture, which includes a variety of activities targeted at enhancing soil health, has the potential to reduce deterioration and increase output. This research looks at several regenerative farming approaches, their effects on soil quality, and their function in carbon sequestration. We focus on case studies of effective implementation, the mechanisms by which these practices improve soil health, and the broader implications for food security and environmental sustainability.

DOI: 10.61137/ijsret.vol.9.issue5.386

Impact of Plant Growth Regulators on Bottle Gourd (Lagenaria Siceraria (Molina) Standl.)Yield
Authors:-Disha Sharma, Vipin Kumar Saini, Aayushi Pal

Abstract- The effects of three plant growth regulators (PGR)—ethrel, naphthalene acetic acid (NAA), and maleic hydrazide (MH)—on bottle gourd growth traits and fruit characteristics, were investigated in an experiment. Distilled water was foud to achieve the maximum fruit length, weight, and girth. MH @ 150 ppm was applied to the foliage to achieve the maximum vine length and total number of nodes per vine. Ethrel @100 ppm was found to be beneficial for the number of fruits per vine, fruit yield (kg/vine). These findings imply that the application of ethrel 100 ppm at 2 and 4 true leaves would result in a notable improvement in fruit characteristics and growth.

DOI: 10.61137/ijsret.vol.9.issue5.387

Correlation and Route Analysis of Linseed Under Uterine Conditions (Linum Usitatissimum L.)
Authors:-Ashu Chaudhary, Vikas Kumar, Vipin Kumar Saini, Ankit Kumar, Zehra Husaini, Saba Rana

Abstract- This study was carried out to assess the correlation and the paths of flax genotypes in the uterus. Eighteen gear genotypes were assessed in a complete randomized block with three rehearsals during Rabi 2021-22 in Muzaffarnagar. Analysis of variance revealed significant differences among genotypes for all traits, indicating the presence of a significant amount of genetic diversity. Phenotypic correlations showed that grain yield was significantly and positively related to number of primary branches per plant, number of bolls per plant, number of seeds per boll, and weight of 1000 seeds. Path coefficient analysis showed that the number of primary branches per plant had the largest positive direct phenotypic effect on seed yield per plant, followed by the number of capsules per plant and the number of seeds per capsule.

DOI: 10.61137/ijsret.vol.9.issue5.388

Reframing Organizational Intelligence: An AI-Based Interpretation Framework for Exit Interview Data in SAP Success Factors

Authors: Manoj Parasa

Abstract: Exit interviews are an underutilized but critical tool for capturing organizational feedback, yet traditional analysis methods often fail to generate meaningful insights. This study investigates the application of artificial intelligence—specifically natural language processing, sentiment analysis, and topic modeling—to interpret qualitative exit interview data within SAP SuccessFactors. Using a mixed-methods design and data extracted from a large multinational enterprise over an 18-month period, the research reveals latent patterns in attrition reasons, identifies hidden organizational issues, and proposes actionable insights for HR leadership. Results demonstrate that AI-enhanced exit analytics uncover unstructured feedback trends more reliably than manual reviews, with significantly higher accuracy in detecting dissatisfaction themes. This paper contributes to social science research by positioning exit interviews as institutional diagnostic tools, offering a predictive lens into workforce behavior. The study concludes by recommending an integrative model for AI-powered offboarding intelligence that can be replicated across enterprise HR platforms.

DOI: https://doi.org/10.5281/zenodo.15718618

Hardening Kernel Parameters for Compliance in Medical Research Servers

Authors: Zarina Safarova, Jamshid Rahmonov, Nargis Khudoyarova, Farhod Karimov

Abstract: In medical research environments, system-level security is paramount due to the highly sensitive nature of biomedical and genetic data. With regulatory frameworks like HIPAA, GDPR, and 21 CFR Part 11 requiring strong data protection and verifiable access controls, kernel parameter hardening has become a foundational strategy for achieving compliance. By tuning kernel parameters using tools such as sysctl on Linux and equivalent mechanisms on Solaris, administrators can restrict system behaviors related to networking, inter-process communication (IPC), and memory management. These configurations mitigate common vulnerabilities, including buffer overflows, shared memory leakage, and IP spoofing. When integrated into an Infrastructure-as-Code (IaC) model using tools like Puppet, Ansible, or Chef, kernel hardening becomes consistent, auditable, and reproducible across large-scale clinical or research server deployments. This review explores specific kernel parameters that enhance system integrity and reduce attack surfaces while maintaining application compatibility in complex biomedical environments. It also examines compliance-driven configuration baselines such as CIS Benchmarks and DISA STIGs. Operational challenges—including drift, rollback complexity, and conflicting application requirements—are addressed with best practices and automation frameworks. Finally, emerging trends such as AI-based anomaly detection, kernel lockdown mechanisms, and TPM-integrated validation are discussed as future directions. This comprehensive evaluation supports security professionals and biomedical IT architects in building hardened, compliant, and resilient research computing infrastructures.

DOI: https://doi.org/10.5281/zenodo.15852624

Supply Chain Disruptions And Consumer Loyalty: An Empirical Analysis Of Purchase Behavior Changes In The US FMCG Sector During Post-Pandemic Recovery (2021-2023)

Authors: Adesina Toheeb Damilola

Abstract: Customer Relationship Management (CRM) has become an essential strategy for large-scale organizations seeking to enhance their interactions with customers, improve satisfaction, and foster long-term loyalty. As competitive pressures increase and customer expectations evolve, enterprises recognize the vital role of CRM systems in managing vast amounts of customer data, streamlining communication, and facilitating personalized marketing strategies. This review explores the implementation of CRM in large-scale organizations, focusing on key strategies, challenges, benefits, and best practices. The integration of CRM systems involves technological, organizational, and human factors that must be comprehensively addressed to ensure successful deployment and adoption. Studies have shown that CRM implementation can lead to improved customer retention, increased revenue, and operational efficiencies, but these outcomes depend significantly on how organizations align CRM initiatives with their business goals and culture. This paper synthesizes findings from various research efforts and case studies, emphasizing the importance of strategic planning, employee involvement, and technological customization in CRM projects. Additionally, the review highlights the roles of data quality management, user training, and continuous performance evaluation as critical success factors. By offering a detailed understanding of CRM implementation dynamics, this paper provides valuable insights for practitioners and researchers interested in optimizing CRM applications within extensive organizational settings.

DOI: http://doi.org/10.5281/zenodo.16993788

Unified AI And IoT Architecture For SAP-Based Predictive Maintenance Operations

Authors: Ritvik Nandesh

Abstract: Predictive maintenance has emerged as a strategic capability for industrial and enterprise environments seeking to reduce unplanned downtime, optimize asset performance, and improve operational efficiency. Traditional SAP-based maintenance systems primarily rely on historical data and scheduled maintenance plans, limiting their ability to respond to real-time equipment conditions. The integration of Internet of Things technologies and artificial intelligence enables a data-driven approach that transforms maintenance operations from reactive to predictive. This article presents a unified AI and IoT architecture integrated with SAP platforms to support intelligent predictive maintenance operations. The proposed architecture leverages IoT sensors and edge computing for real-time data acquisition, AI models for failure prediction and anomaly detection, and SAP systems for orchestrating maintenance workflows and enterprise processes. Key architectural components, data flows, and predictive maintenance workflows are discussed, along with security, governance, and compliance considerations. The article also examines performance evaluation metrics, business impact, and implementation challenges. Finally, emerging trends such as edge AI, digital twins, and autonomous maintenance systems are explored, highlighting their potential to further enhance SAP-based predictive maintenance solutions. The insights provided aim to guide organizations in designing scalable, secure, and intelligent maintenance architectures aligned with enterprise objectives.

DOI: https://doi.org/10.5281/zenodo.18162331

Risk-Aware Cloud Architectures For SAP-Enabled Financial And Healthcare Systems

Authors: Bhavya Kaironit

Abstract: Risk-aware cloud architectures play a pivotal role in enhancing the security, compliance, and operational efficiency of SAP-enabled financial and healthcare systems. By integrating risk management principles, data protection mechanisms, and governance frameworks directly into cloud environments, organizations can proactively address threats while enabling innovation. In financial systems, these architectures support secure transaction processing, fraud detection, and regulatory reporting, ensuring reliability and compliance. In healthcare, they facilitate secure electronic health records, analytics, and telemedicine services while adhering to privacy regulations such as HIPAA and GDPR. Incorporating AI and automation further strengthens risk detection, response, and monitoring capabilities. This approach ensures that sensitive financial and patient data are safeguarded, regulatory requirements are met, and organizational trust is maintained. The paper highlights how risk-aware design principles in SAP cloud architectures can simultaneously enable innovation and resilience in highly regulated industries.

DOI: https://doi.org/10.5281/zenodo.18162423

 

Enterprise-Wide Financial Transparency In SAP Using Data-Centric AI Pipelines

Authors: Mrinal Daksheen

Abstract: Achieving enterprise-wide financial transparency is a critical challenge for large organizations due to fragmented data, manual reconciliation processes, and delayed reporting. SAP provides a robust platform for integrated financial management, yet traditional reporting methods often fall short in delivering real-time, accurate insights. This article explores the application of data-centric AI pipelines within SAP to enhance financial transparency across the enterprise. By emphasizing high-quality, validated data over purely model-centric approaches, these pipelines enable automated data extraction, cleaning, transformation, and validation, supporting real-time dashboards, predictive forecasting, anomaly detection, and compliance monitoring. The discussion covers pipeline architecture, integration strategies, implementation best practices, and potential benefits, including improved accuracy, operational efficiency, risk mitigation, and regulatory compliance. Challenges such as data inconsistency, integration complexity, and model maintenance are also addressed, along with future directions in adaptive AI and enterprise-wide intelligent financial systems. By adopting data-centric AI pipelines, organizations can transform financial reporting into a proactive, insight-driven function, enhancing decision-making, stakeholder trust, and organizational agility.

DOI: https://doi.org/10.5281/zenodo.18162511

Automated Incident Intelligence In Supply Chains Using Agentic AI And Root Cause Reasoning

Authors: Nirmal Kumar Jingar

Abstract: Supply chain operations frequently experience incidents such as delays, shortages, quality failures, and logistics breakdowns. Identifying root causes quickly is critical, yet current incident management processes are largely manual, reactive, and error-prone. Existing systems primarily use rule-based alerts or statistical anomaly detection. Although effective in detecting issues, they lack deep causal reasoning and fail to correlate multi-source data across suppliers, transportation, and operations. This results in delayed resolution and repeated incidents. This paper introduces an automated incident intelligence framework using agentic AI with root cause reasoning. Specialized agents monitor supply chain signals, detect anomalies, and collaboratively perform causal analysis using knowledge graphs and probabilistic reasoning. Generative AI supports hypothesis generation and explanation of root causes in natural language, enabling faster human understanding and response. The proposed system was evaluated on simulated and real operational datasets involving multi-tier supply chains. Results show a 30% reduction in mean time to root cause identification and 22% improvement in incident resolution accuracy compared to traditional approaches. Additionally, the system successfully identified hidden dependencies that were missed by baseline methods. This work demonstrates the effectiveness of agentic AI in transforming incident management from reactive monitoring to proactive intelligence.

DOI: http://doi.org/10.5281/zenodo.18628070

Enterprise System Design Using Automation And Cloud Technologies

Authors: Arjun Pillai

Abstract: Modern enterprises operate in highly dynamic digital ecosystems where applications must support large volumes of concurrent users, real-time processing, and continuous service availability. To meet these expectations, information systems are required to be scalable, resilient, and economically efficient while maintaining consistent performance across geographically distributed environments. Traditional monolithic architectures are increasingly unable to satisfy these requirements because they rely on tightly coupled components, rigid deployment cycles, and manual infrastructure management. These limitations result in slower innovation, increased downtime risk, and higher operational costs. The emergence of cloud computing combined with automation technologies has significantly transformed enterprise system design. Cloud platforms provide elastic resource provisioning and geographically distributed infrastructure, while automation enables repeatable configuration, rapid deployment, and continuous operational monitoring. Together, they enable organizations to transition from hardware-centric infrastructure management to software-defined operational environments capable of adapting to workload fluctuations in real time. This review examines the architectural evolution of enterprise systems from monolithic models to service-oriented and microservices-based architectures. Particular emphasis is placed on enabling technologies including Infrastructure as Code (IaC), DevOps methodologies, containerization, orchestration frameworks, and artificial intelligence–driven automation. The study also analyzes cloud service and deployment models, monitoring and observability mechanisms, and integrated security automation approaches that enhance reliability, availability, and operational efficiency in distributed enterprise platforms. Furthermore, the review discusses key implementation challenges such as vendor lock-in, data protection requirements, operational complexity, and financial governance associated with automated cloud environments. Emerging trends including autonomous operations, predictive scaling, and self-healing infrastructure are explored to illustrate the future direction of enterprise computing. Overall, the convergence of automation and cloud technologies establishes a foundational paradigm for next-generation enterprise digital infrastructure, enabling adaptive, intelligent, and continuously evolving software systems.

DOI: https://doi.org/10.5281/zenodo.18712211

Prompt-Driven Pipeline Synthesis Using LLMs With Context-Aware Auto-Configuration

Authors: Pawan Kalyan Jonnalagadda

Abstract: The development of the large language models (LLMs) has brought many new opportunities to automate the workflow involving complex computations. Nevertheless, current pipeline systems are still mostly fixed, needing to be configured manually and cannot adapt to dynamic settings. The paper suggests a new framework that is based on prompt-driven pipeline synthesis via context-aware auto-configuration of LLMs, which allows automatic synthesis and optimization of task-specific pipelines based on natural language input. The proposed approach involves a combination of timely engineering, contextually-based learning and sequence improvement to construct and adjust pipelines dynamically based on contextual information. An artificial performance model is used to determine the performance of the system relative to the current models that demonstrate that the accuracy, scalability and adaptability are improved without affecting the competitive latency. Such results demonstrate the utility of deploying LLMs as intelligent agents to optimally design pipelines as a scalable and adaptable solution to problems in the real world.

DOI: https://doi.org/10.5281/zenodo.19628685

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Single Blind Peer Review

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Academicians do research and publications from time to time. They complete their part as researchers by writing and submitting their research work at publishing platforms. After that, ensuring the reach of the research to the relevant audience is the most important part of the research publication journey which is mainly done by journals.  

There are mainly four types of reviewing processes accepted by journals. Which is:

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  • Single blind peer review
  • Double blind peer review
  • Open peer review
  • Peer review after publication

What is single blind peer review

Single Blind Peer Review

A single blind peer review is a traditional method of reviewing which is accepted by many publishing platforms. It is a process in which the reviewer knows the details of the authors while the author has no clue about who the reviewer is. 

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Double blind peer review

In this type of reviewing process, both author and reviewer don’t know each other. At present most of the journal conduct double blind peer review because of it 

Open peer review process

This type of peer reviewing system, author and reviewer know who the other side is. This information mainly get revealed during the reviewing or at any stage of reviewing. 

Reviewing after publication 

In this method of reviewing, the journal publishes the research paper or article with some checkings. Later on reviewers were invited for the assessment. Even individuals can comment on the published work.

Now move to the next segment of this article. Here one will be aware of the benefits they get by single blind peer reviewing. They are as follows:

  • Sometimes in a single blind peer review process, reviewers accept new research done by young scholars. They avoid little mistakes and suggest improvement in their research work, encourage them to continue in the research field  and do more fruitful research for the betterment of the research field and society. 
  • Less review time – It is observed that journals that follow a single blind peer review process have less reviewing time compared to other reviewing processes. Which indicates one can have fast  paper reviewing and less time it will get published.
  • In a single blind peer review process, the details of the authors would be shared with the reviewers. In a recent study it is found that the single peer review journals accept 50% of research papers which come to publish. Which is 29% more than the double blind peer review journals.
  • Sharing details with reviewers helps them in determining the level of suggestion they can share with the authors. For example a researcher who has completed his first project won’t be able to understand the terms and other research related things but if he has experienced co-authors then reviewers can share their thoughts without hesitation to improve the quality of the research paper or article.

 

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Open Access Peer Reviewed Journals

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Scholars and other academic research individuals seek journals having open access facilities along with peer reviewing processes for various reasons like- finding reliable resources to gain knowledge in a particular area, ideas for upcoming research projects,  finding solutions, learning from others work, publishing research papers or articles in related fields, etc. This blog will let you know what the open access peer reviewed journals are and how authors will benefit from their grounds by publishing their research work.

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What is open access ?

Open access is a term that is used for something available for everyone or accessible by everyone around the world. In a journal’s case open access means that database or other content like research papers or articles published by the journal would be freely available on their platform and it can be accessed and used by anyone. Open access facility of journals helps authors as well as readers to gain knowledge and transmit to others in a short amount of time.

What is a peer review journal ?

A peer review is a process in which scholars and researchers having expertise in the related subject or research area, evaluate the research paper or article to check the quality of the research work and its suitability to get published in the journal. 

Benefits of publishing in open access peer reviewed journals

Broader reach – Open access platforms have a large number of audiences from all over the world. Academicians, researchers and other individuals who publish their research work in open access peer reviewed journals ensure the reach of their work across the nations. 

Validity – A research paper or article goes through many levels to get accepted and published in a journal. Many steps help scholars in resolving the shortcomings of the research paper and present all the authentic and qualified work in front of readers. It validates the content and quality of research work.

Authenticity – The research paper or article published in a peer reviewed journal that also provides open access to its databases increases the authenticity of the published work. As it can be accessed by anyone, and every one can present their thoughts on it without restrictions. 

Reliability – Research content published and provided by open access peer reviewed journals are more reliable than the journals that are non peer review or non open access journals. 

Citations – As discussed, open access journals have a vast audience in a particular domain. People go through journal databases to find work related to their research and easily cite them or use them for reference in their research publications. Having in front of a vast audience helps them in increasing their citations. 
The overall article is to help scholars who are looking for open access peer reviewed journals as per their interests.

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Article Published in Research Journal

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Research is a part of academics so individuals who are opting for research oriented careers or want to get their degrees for better placements and opportunities do research on projects and write about their research to get it published in a journal or other publishing sites which authenticate the research publications. 

At present there are numerous platforms available that provide information regarding journals as per one’s research areas. Scholar and research individuals looking for journals to submit papers can find international journals to publish their journal manuscript. Article published in research journal have broader reach compare to other platforms.

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In the present time almost everything is online. Most of the journals that previously worked in print only mode also operate online so that transmission of knowledge remains unrestricted. This blog will let one know how to find journal to submit paper in a particular field of research and steps to submit papers in a journal for publication.

There are many platforms  which provides information regarding journals to submit papers. One can look for indexing websites like- Scopus, Web of Sci, ABCD Index to find journals as per research area.

How to submit paper in a journal for publication

For online submission of the research paper follow the points discussed below:

  1. Go to the journal’s manuscripts submission page. Or find the submit manuscripts menu then click on it. This action will lead you to the submission page of the journal.
  2. At the submission page, some fields are given that the author has to fill to submit their research paper or article.
  3. Some common fields that an author has to fill are name, contact details like- email address, contact number, address etc., area of research, type of manuscript (research paper, article, survey paper, review, etc.), title of the manuscript, abstract etc.
  4. Scholars must fill in all the details carefully because after submission of the manuscript all further communication would depend on the details submitted by the author. In case of any mistake, one would not be able to get notification about their papers.
  5. Upload manuscript in the format accepted or specified by the journal. It can be any pdf, docx, or others. Most of the journal accepts pdf so it would be wise to have a copy of your research paper in pdf format.
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Publish Article in Journal

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Academicians like professors, lecturers and researchers most of the time busy themselves in doing research and write it down on a paper to get it published in a reputed journal. Publishing paper in an academic journal opens a variety of opportunities in front of authors and gives them a new horizon that helps in their personal as well as professional growth. The main purpose behind publish article in journal is to share the information of research findings with the scholars, researchers and other individuals working in the same field of research. This blog will help academic and research scholars to know how to publish article in journal

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Following are the benefits one will get by publishing their article or research paper in an international journal:

Open accessibility – In the present time, most of the international journals gives free open access to the readers looking for scholarly articles. Journals open access system helps scholars research work in reaching to the vast audience working in the same field of research around the world and fulfill the aim of research publication. Freely accessible quality research databases encourage young research scholars to do more research and strengthen the research field.

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Reliability – Scholar’s research work goes through an intense peer review system in which quality of research work gets improved and journal published quality work on their portal. This increased the reliability of the research work among academic individuals.

Increase citations – Individuals publishing in an international journal would increase citations for their research work. Journals publishing sites have a large number of audiences related to the domain or research area the author is working in. Many users visits paper publishing sites on a daily basis to find research databases for different reasons like gaining in depth knowledge on a particular topic, looking for ideas for the next research, seeking methods, or looking for previously published articles on the same topic for reference etc. they will likely to read published work and cite them in their work.

Community membership – Many journals run a community platform at their portal in which scholars and researchers having the same field of research or working in the same research domain can have their own communities as per their regions. Journal offers membership of these communities to the authors so that they can connect to the people working in the same department or research areas across the world.

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Submitting Paper to Journal

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Scholars, researchers and other academic individuals who want to publish their research paper or articles but don’t have any idea what process is required in submitting paper to journal for research publication or what steps they should take so that their work gets published in a research journal. 

This blog will cover all the aspects that help young scholars as well as academic individuals who just begin their research journey and looking for portals for submitting article for publication. 

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Firstly cover the things one should know in advance if opting for an international journal for paper publications. Students should check the following before submitting a research article or paper in it.

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Research domain – Check the research domain of the journal. If you are opting for a journal which does not publish in the same domain as yours then eventually submitted paper would get rejected in the first phase of reviewing. So why go with the way that does not lead anywhere instead of checking the archive section of the journal to know the prospective research areas of that journal.

Reviewing process – reviewing plays an important role while publishing research work. An author learns a lot through peer reviewing and works to improve their research work through the suggestions given by reviewers. Journal’s offer different types of peer reviewing single blind, double blind, open peer review etc to ensure the quality of the research papers before publication.

Editorial board – Some research papers  need expertise in related subjects.  One should check the editorial board of that journal whether they have the required expertise in related domains to ensure quality reviewing and relevant paper publication in the journal.  

Citations – citations show an average number or rate of the research papers cited by individuals. It reflects the quality of research work published in the journal.

Process of submitting paper to journal

  • Go to the journal’s website and look for a submit paper portal. It can be named as manuscript submission, submit paper, submit manuscript etc. 
  • Fill the details asked by the journal for paper submission. Like- author name, research domain, department, title of the paper, abstract, corresponding authors (if required), contact details, email, etc.
  • Now upload the research document in the format accepted by the journal then click on the submit button.

You have successfully submitted your research paper to the journal. Now wait for the response from the other side. Generally it would take 10 to 15 days. So wait patiently. 

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Journal with DOI

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Academic and research individuals often look for journals in their related fields to publish research papers or articles, to find databases for ongoing or upcoming research, gain knowledge, etc. As we know research is a continuous process which requires both time and money at same time. 

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Why choose journal with doi

DOI or digital object identifier provides a process to identify the online published documents, articles, research  papers and other work.  An international Journal with doi provides many advantages to scholars and researchers who published a research paper or article in it. Journals offers DOI for the research paper helps authors in getting global identity through their research work.

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Most of the time when we explore journal’s websites it is found that some of them state one thing and do others. They write and show the logo of doi on their website but in reality they did not provide any. In this case the one who suffers loses is the author.  So it would be better to ensure whether the journal stating is correct or not. Because getting a DOI number is not that easy for everyone. One has to fulfill all the requirements along with paying a good amount for getting a DOI number for their published work. 

If a journal is published for free then the amount of DOI most of the time bear by the journal itself. In the case of a paid journal it is the author.

Journal with DOI

How to find out the DOI is authentic or fake:

To check whether the DOI provided by the journal is real or fake just go to DOI official website and put the reference doi number of the journal into the search box presented at the website. Then click on the search button. If the doi is correct then it will show the journal’s name or profile on the window. In other cases it would show none.

 

Advantages

There are many advantages one can have by associating journals with doi. They are discussed in the following points:

Separate URL – DOI provides a separate URL for each online published content. It gives a Unique identification number which reflects the source of the content and provides a global identity to the research paper individually.

Validity – DOI of a research paper increases the validity of that research paper or article. One can look for it source anytime which can not be possible if  if a research paper had a DOI then it 

Increase number of citations – a doi no provides a unique identity to research paper or article and helps scholars in locating the content they are looking for from the original sources. By using DOI one can easily use or arrange citations and references in their research papers / articles. 

Authenticity of the articles – Before DOI there was no platform available that helps in authenticating the citation and references. DOI helps in finding the original sources of the published content and indirectly controls the issue of plagiarism.

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A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets

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Authors:-Smita Waskale, Arjun singh Parihar , Manisha Kadam

Abstract- Heart related diseases presently pose one of the major threat worldwide. Heart abnormalities show a wide variation because of which accurate diagnosis becomes challenging. Phonocardigram (PCG) signals and their analysis has opened up a new paradigm in telemedicine. The abrupt fluctuations and the randomness of the PCG signals make them difficult to analyze and extract key parameters called features. Conventional Fourier techniques fail in this regard. In this paper, we have proposed a wavelet based technique wherein the discrete wavelet transform (DWT) have been used for the processing and feature extraction of the PCG signals has been done subsequently. The features extracted are energy, variance, entropy and standard deviation. The features extracted can be subsequently utilized for the classification of the PCG signals using the Conjugate Gradient Algorithm. The three categories of classified are: stenosis, regurgidation and normal. It has been shown that the proposed algorithm attains an accuracy of 93%.

DOI: 10.61137/ijsret.vol.9.issue4.101

Cite: Smita Waskale, Arjun singh Parihar , Manisha Kadam. “A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets”. IJSRET Volume 9 Issue 4, July-Aug-2023.

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Early Prediction Of Student Academic Performance Using Machine Learning

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Authors: Vanaja Kumari Degala

Abstract: Early prediction of student academic performance has become an essential research problem in higher education due to increasing dropout rates and declining academic outcomes. The ability to identify at-risk students at an early stage enables institutions to implement timely interventions and personalized academic support. With the rapid growth of educational data, machine learning (ML) techniques have shown significant potential in extracting meaningful patterns from student records. This paper presents a comprehensive machine learning-based framework for early prediction of student academic performance using pre-admission data and first-year academic attributes. Several supervised learning algorithms, including Logistic Regression, Support Vector Machine, Random Forest, K-Nearest Neighbors, and Extreme Gradient Boosting (XGBoost), are evaluated. Dimensionality reduction using t-distributed Stochastic Neighbor Embedding (t-SNE) is employed to visualize high-dimensional student data. Experimental results demonstrate that combining admission scores with first-year course performance significantly improves prediction accuracy. The proposed approach can assist academic institutions in proactive decision-making to enhance student success and retention.

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A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets

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A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets
Authors:- Smita Waskale, Arjun singh Parihar , Manisha Kadam

Abstract- Heart related diseases presently pose one of the major threat worldwide. Heart abnormalities show a wide variation because of which accurate diagnosis becomes challenging. Phonocardigram (PCG) signals and their analysis has opened up a new paradigm in telemedicine. The abrupt fluctuations and the randomness of the PCG signals make them difficult to analyze and extract key parameters called features. Conventional Fourier techniques fail in this regard. In this paper, we have proposed a wavelet based technique wherein the discrete wavelet transform (DWT) have been used for the processing and feature extraction of the PCG signals has been done subsequently. The features extracted are energy, variance, entropy and standard deviation. The features extracted can be subsequently utilized for the classification of the PCG signals using the Conjugate Gradient Algorithm. The three categories of classified are: stenosis, regurgidation and normal. It has been shown that the proposed algorithm attains an accuracy of 93%.

Cite: Smita Waskale, Arjun singh Parihar , Manisha Kadam. “A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets”. IJSRET Volume 9 Issue 4, July-Aug-2023.

 

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