Study the Effect of Smart Class and Lecture Method on the Achievement in Artificial Intelligence of Higher Secondary School Students of Indore city
Authors:-Research Scholar Aaquib Multani, Asst. Prof. Pallavi Kumari
Abstract- This study examines the effect of Smart classroom teaching on the academic achievement of Higher Secondary School students in the subject of ‘Artificial Intelligence’. A sample of 64 students from the Central Board of Secondary Education School in Indore City, participated was grade XI in the study and converted into two groups such as Control and experimental group, quantitative data was collected using an achievement test administered to both an Experimental group taught in Smart Class and a Control group taught using lecture methods. The findings revealed that students exposed to Smart classroom teaching exhibited higher levels of achievement in ‘Artificial Intelligence’ compared to those taught through lecture methods.
Pixel Pro: Exploring Image Analytics for Enhanced Visual Insight
Authors:-Sanchary Nandy, Shreyas Pandey,Vineet Mehan
Abstract- The “PixelPro: Exploring Image Analytics for Enhanced Visual Insights” project is a comprehensive endeavor at the crossroads of cutting-edge technology and visual data interpretation. In a world inundated with images, the challenge of extracting meaningful insights has spurred the amalgamation of machine learning, computer vision, and user interface design. This project seeks to decode the complexity of visual data by developing advanced algorithms for image classification and object detection, while simultaneously crafting an intuitive interface for user-friendly exploration. The core problem addressed is the gap between the intricacies of image analysis techniques and their practical usability. Traditional manual methods of image interpretation are time-consuming and prone to errors, hindering the extraction of valuable insights. Leveraging the power of convolution neural networks (CNNs), this project aims to create models that autonomously unravel intricate patterns and objects within images, thus enhancing accuracy and efficiency. This technical prowess is harmonized with an intuitive interface, which empowers users from diverse backgrounds to seamlessly upload images, initiate analyses, and delve into results. The project unfolds through well-defined objectives that encompass accurate image classification, precise object detection, streamlined feature extraction, and user-friendly interface design. These objectives culminate in a solution that bridges the gap between technical sophistication and practical accessibility, thereby enabling users to gain profound insights from images without grappling with technical complexities.
Study Of Personality Of Higher Secondary School students In Relation To Their Usage Of Social Media, Gender And Board Of School
Authors:-Research Scholar Mansi Khandelwal , Assistant Professor Pallavi Nagar
Abstract- This study examines the personality of higher secondary school students in relation to their usage of Social Media, Gender and Board of Schools. A sample of 100 students of class XI was taken, 50 students from Central Board of Secondary Education and 50 students from MP Board of Dhar District. Result suggests that there is no effect on personality of students regarding the usage of social media, gender and board of schools. This study also says that the extraversion students may use social media more as compared to ambivert and introversion students.
The Evaluation of The Feasibility of Using Palm Pressed Fiber and Palm Kernel Shell to Generate Electricity.
Authors:- Ikenna. N and Ogueke N.V , Okoronkwo C. A
Abstract- This study evaluates the feasibility of using palm pressed fiber (PPF) and palm kernel shell (PKS) as boiler fuels to generate electricity for 1500 domestic households in a rural community. The methods adopted for data acquisition include field trips, consultation with relevant government agencies like NERC, and consultation with notable equipment manufacturers. The field trip conducted involves regular site visits to smallholder palm oil mills in Imo and Abia states, Nigeria. Consultations with relevant government agencies were carried out to get the accurate data needed for analysis and compilation. Technical consultations with reputable equipment manufacturers were taken to get an accurate cost estimation in line with power-generating capacity. The data obtained were used to determine the energy demands of the community where the biomass system is situated using relevant governing equations. The results obtained from the feasibility study showed that 1,500 households in the chosen community require approximately 3 MW of electricity per hour, while the average PPF and PKS production rate from the procurement states is 66480 kg/hour. It is estimated that 34.5 MW of electricity could be obtained using 15,000 kg of fuel. In addition, the study showed that an average specific investment cost of ₦87 per KWhr could be obtained when PPF and PKS are used to generate electricity. When compared to the present average electricity consumption rate of ₦88.3 per KWhr to ₦112 per KWhr of three (3) different electricity distribution companies in Nigeria using fossil fuel for power generation and its environmental impact, it is worthwhile and exigent to harness and integrate these energy resources (biomass) into the national energy mix for electricity sustainability and development. In view of the above, it is therefore feasible to generate electricity for more than 1,500 domestic community households using PPF and PKS at a reasonable cost when compared to the existing fossil fuels presently used.
Prajna: Empowering CXOs with Conversational AI for Data-Driven Insights
Authors:-Shivam Dutt Sharma
Abstract- This paper describes the scope of a Conversational AI for the CXOs and how it can empower them in their daily data to insights to actions journey. In today’s data-driven business environment, Chief Executive Officers (CXOs) are increasingly expected to engage with data-related matters. While they have access to Business Analysts and Data Scientists, they often find themselves immersed in data, dealing with complex spreadsheets, filters, and formulas. This can be overwhelming, even for tech-savvy CXOs, and consumes a substantial amount of time. Enter Prajna, a Conversational AI solution aimed at providing CXOs with data insights at their fingertips. Prajna, built on the open-source RASA framework, enables CXOs to interact with data, ask questions in plain English, and access a wealth of insights. It also benefits Business Analysts and Data Scientists by facilitating natural language querying of data. Prajna aligns with an organization’s broader business objectives and strategy. The advantages of Prajna include the extraction of faster and deeper insights from complex data, personalized messaging in the era of IoT and e-commerce, cost reduction through automation of routine customer interactions, and the generation of customer insights from interactions and reviews. The system utilizes an open-source dataset from Auckland Airport for a proof of concept. Prajna’s architecture is easy to understand and implement, with deployment options including Kubernetes, Docker, and CMD applications. Prajna’s success is measured by its ability to save time, automate processes, enhance customer experiences, and augment analytics. Notably, it can handle confidential and protected data, bridging the gap between Conversational AI and sensitive organizational information. In conclusion, Prajna represents a revolutionary tool for CXOs, Business Analysts, and Data Scientists, ushering in a new era of conversational data-driven insights and personalization.
Speech Emotion through Voice & Accent
Authors:-Kundan Sai Kotta, Sai Nikhil Samineni, Asst. Prof.G. Kavitha
Abstract- Detecting emotions through voice represents the next evolutionary leap in human-computer interaction, propelling us toward a more intuitive interface and enabling the development of superior recommendation systems.Voice, encompassing pitch, tone, and cadence, and accent, involving pronunciation patterns and linguistic nuances, play crucial roles in this context. Emotions, fundamental to human interaction, greatly influence communication and understanding. This research aims to investigate how variations in voice and accent contribute to expressing and interpreting emotions in speech. The study explores deep learning architectures and methodologies for this purpose, addressing associated challenges, limitations, and ethical considerations. Understanding the interplay of voice, accent, and emotions is pivotal for advancing technology in a beneficial manner.
A Survey on Wireless Sensor Network of Acoustic Environment Types & Techniques
Authors:-M.Tech.Scholar Vikash Malviya, Sumit Sharma
Abstract- Underground Acoustic Networks (UAN) are made up of sensors that are placed in a certain sound area to work together to collect data and keep an eye on things. These networks are used so that different nodes and ground stations can talk to each other. The paper gives an outline of the problems with UAN communication. This paper is an overview of the work that other experts have done to improve WSN network standards, hardware, and other aspects. This article talks about different kinds of UAN networks and route methods that use less energy to send packets. The last part of this piece is a list of assessment criteria for comparing techniques.
Performance on Polypropylene Fibre Concrete Using Silica Fume as Partial Replacement of Cement
Authors:-Dr.K.Chandramouli, J.Sree Naga Chaitanya, Sk.Sahera, B.Ravi Teja
Abstract- The world is developing quickly as a result of the creation of residential and commercial structures. The usage of concrete results in a depletion of natural resources. Silica fume is applied as an addition at different percentages of 5%, 7.5%, and 12.5% to partially replace cement. Polypropylene fibres are used to increase the strength qualities of concrete. Concrete is mixed with 0.5%, 1.5%, and 2.0% of polypropylene fibres added. The test results for split and compressive tensile strength were obtained at 28, 56 and 90 days.
Strengthening on Polypropylene Fibre Concrete Using Silica Fume as Partial Replacement of Cement
Authors:-Asst.Prof. J.Sree Naga Chaitanya, Prof. &HOD Dr.K.Chandramouli, Asst.Prof. K.Divya,
B.Tech. Student Shaik Sarfaraj
Abstract- The construction of residential and commercial buildings is causing the world to develop rapidly. A shortage of natural resources is caused by the use of concrete. In order to partially replace cement, silica fume is added as an additive at varying percentages of 5%, 7.5%, and 12.5%. Concrete’s strength properties are improved with the use of polypropylene fibres. 0.5%, 1.5%, and 2.0% of polypropylene fibres are added to concrete. At 7 and 28 days, the test results were obtained in relation to split and compressive tensile strength.
Experimental Investigation on Concrete by Using Partial Replacement of Groundshell ash With FineAggregate and Zeolite Powder with Cement
Authors:- sst.Prof. J.Sree Naga Chaitanya, Prof. Dr.K. Chandramouli, Asst.Prof. Sk.Sahera,
B.Tech. Student Shaik Abbad
Abstract- Aggregate is a hard, chemically inert particle material used in building that forms bonding with structural materials through the use of cement and water. Typically, aggregate consists of sand and gravel. The effects of partially substituting cement in concrete with zeolite powder on its characteristics were investigated through experimental research. Zeolite powder can be used to replace cement in different percentages 5%, 10%,15%, 20%, 25%, and 30%. The viability of using groundnut shell ash partially replace of fine aggregate was assessed in this experimental investigation.Instead of using 2.5%, 5%, 7.5%, or 12.5% fine aggregate for M40 concretewith distinct concrete compositions with powder and ash were used.In both fresh and hardened concrete settings, the characteristics of these concrete combinations were examined. In order to ascertain the cube samples’ compressive strength, they were moulded, cured, and evaluated after 7 and 28 days.
Knowledge on Health Effects and Current Practice towards Areca-nut
use Among Secondary School Children Living in Male’ City, Maldives
Authors:- Abdul Azeez Hameed, Ali Najeeb
Abstract- Objective: To identify knowledge on health effects and current practice towards arecanut use among secondary school children living in Male’ city, Maldives. Methods: A cross sectional survey using a pre-coded questionnaire was conducted at 4 different schools in Male’ city, Maldives. The schools were selected through clustering sampling, while students were selected using simple random sampling. SPSS 21 was used for data analysis. Results:Out of 674 secondary school children 337 (50%) were boys, while 337 (50%) were girls. Secondary school children in Male’ city have inadequate knowledge on harmful effects of arecanut use. The knowledge among secondary school children varies based on their gender, grade, school and residence, but does not varies based on their age. It was identified 353 (52.4%) school children started arecanut use at age between 11-15 years, while it was introduced into 362 (53.7%) school children by family members. Moreover 423 (62.8%) school children used Supari as a main form of arecanut and 370 (54.9%) school children used Rasily Supari as their favorite brand. Conclusion: Secondary school children in Male’ city have inadequate knowledge regarding harmful effects of arecanut use. Supari is the main form of arecanut use and most of the school children initiated arecanut chewing at a younger age.
Wi-Fi Controlled Multi-sensor Robotic Car
Authors:- Prof. Ashwini Barkade, Tanaya Pawar, Manisha Shinde
Abstract-Robotics Automation is a field that’s growing really fast. Industrial robots are being used a lot in different parts of the world recently. They are becoming more and more popular because they help make things faster, work well in many situations, and make money. In factories and industries, robots are changing how things are done. So, it’s important to pay attention to what new things are happening in robotics because it’s a big field and robots are helping us in many ways, like in the military, for watching things, and in factories for moving stuff around. Robots are good because they save money, make things safer, do work faster, and people get hurt less. Robots are much faster and more careful than people, and they can work all the time. People really like robots because they are good at lots of things. In this project, we want to make a special robot car that you can control with your smartphone. It can do many different tasks and is strong and flexible, but we want to make it simple. We use something called Node MCU, which is the most important part, to connect everything. You can use your phone to tell the car what to do, and it can even tell you if there’s something in its way. We also use special sensors to help the car sense things like temperature, gas, and fire to keep you safe. This can be helpful in places that are dangerous for people, like where there are dangerous chemicals or things that can explode. The future trajectory of this project aims to further enhance the intelligence and autonomy of the robot, all while maintaining the simplicity of user interaction and control. The objective is to continue advancing the capabilities of this robot car, making it smarter and more self-reliant, thereby expanding its potential applications and impact.
A Review on Performance of Shell and Tube Heat Exchanger
Authors:-M.Tech. Scholar Mohammad Shad Khan, Prof.Dr. Manoj Mohbe
Abstract-A heat exchanger may be defined as a device that transmits thermal energy between two or more fluids of varying temperatures. Several industrial processes would indeed be impossible to complete without this equipment. Refrigeration, air conditioning, and chemical plants all use heat exchangers. It’s utilised for a variety of things, including transferring heat from a hot to a cold fluid. They’re commonly employed in a variety of industrial settings. Researchers had worked on a variety of projects in attempt to increase performance. The velocity and temperature contour fields upon that shell side, on the other hand, are much more complicated, and their performance is influenced by baffle elements such as their arrangement the spacing scheme.
Planets of the Solar System – The Misinterpreted Objects of the Sky
Authors:- Subhasis Sen, Retired Scientist
Abstract- A critical study reveals that the previous explanations on planets of the Solar System need thorough scrutiny. Here, I have pointed out that all planets of the Solar System are basically composed of similar objects and no planet can be mainly constituted of gases. The study reveals that Earth is an expanded planet and matching thickness of its outer core with the extent of expansion reveals that due to expansion, the former geosphere has opened up as a void zone. The prevalent concept conceives that the outer core is a fluid geosphere comprised of liquid iron. Here I envisage that because of occurrence of a void geosphere between the solid mantle and the solid inner core, in addition to the normal downward force of gravitation, a reversely directed gravitational force would be manifested in the Earth’s deep interior. Accordingly, temperature and pressure at the Earth’s deep interior would be sufficiently low, thereby, keeping the inner core a dipolar permanent magnet. Since all planets of the Solar System are similar in nature, the information gained here in regard to planet Earth can be applied for unravelling the features of all other planets of the Solar System as well.
Strength Studies on Concrete by Partial Replacement of Fine Aggregate With M-Sand Cement With Graphene Oxide- Using M20 grade of concrete
Authors:- Prof. Dr. K. Chandramouli, Asst. Prof. J. Sree Naga Chaitanya, Asst. Prof. K.Divya, B.Tech. Student M Hepsibha
Abstract- To form concrete, a composite material, aggregate is bound together with a fluid cement that cures over time. the qualities of freshly mixed concrete that hardens when M-Sand is used as the fine aggregate. Graphene oxide (GO) is graphene that has undergone oxidation. Because graphene oxide dissolves in water and other solvents, processing it is simple. This study aims to investigate the use of graphene oxide in place of some cement and M-Sand in place of some fine aggregate. 28 and 7 days were tested during the cure period. However, when we included graphene oxide in the cement mixture, the compressive strength rose. A proportion of M-Sand 10% ,20%,30% and 40% is used in place of the fineaggregate and cement is replaced with an 0.03%, 0.06%, 0.09%, 0.12%, and 0.15% by graphene oxide. Compressive and split tensile strengths have been determined in this experiment.
Mechanical Properties on Concrete by Partial Replacement of Fine Aggregate with M-Sand and Cement with Graphene Oxide
Authors:-Prof.Dr.K.Chandramouli, Asst.Prof. J.Sree Naga Chaitanya, Asst.Prof.Sk.Sahera,B.Tech. Student M Jagadeesh
Abstract- A fluid cement that cures over time is used to bind aggregate together to create concrete, a composite material. The fresh and hardening properties of concrete built with M-Sand as the Fine Aggregate. Graphene oxide (GO) is the oxidized form of graphene. Graphene oxide is easy to process since it is dispersible in water and other solvents. The aim of this study is on the usage of M-Sand as a partial replacement of fine aggregate and graphene oxide as partial replacement of cement. The cure period tested for 7 and 28 days. But the compressive strength increased when we added graphene oxide to the cement mix. The M-Sand replaces with an percentage of 10%,20%.30% and 40% and graphene oxide replaces with an percentage 0.03%,0.06%,0.09%,0.12% and 0.15%. In this experiment, compressive and split tensile strengths are determined.
Thermal Analysis of Single Effect Vapour Absorption System Integrated with Vapour Compression System
Authors:- Pradeep Kumar, Sujeet Kumar Singh
Abstract-This study provides a thermal analysis of a hybrid system integrating a single-effect vapour absorption system with a vapour compression system. This integration represents a synergistic approach to enhance overall system efficiency and performance. Various operating parameters are scrutinized to identify key factors influencing the integrated system’s thermal behavior. Further, thermodynamic modelling of cycle has been done in EES software. The synthesis of vapour absorption and compression technologies in a single-effect configuration presents a promising avenue for advancing the efficiency of refrigeration and air conditioning systems, making this review valuable for researchers, engineers, and practitioners seeking insights into the thermal dynamics and optimization potential of such integrated systems.
A Review on Improving Productivity in Flexible Manufacturing Environment
Authors:- M.Tech. Scholar Piyush Savkare, Yogesh P Ladhe, Prof. Vipul Upadhayay
Abstract-Improving productivity in a flexible manufacturing environment involves optimizing processes, utilizing technology, and fostering a culture of continuous improvement. Implement automated systems and robotic solutions to handle repetitive tasks, allowing human workers to focus on more complex and value-added activities. Use robotics for material handling, assembly, and quality control to increase efficiency and reduce cycle times. Utilize APS systems to optimize production schedules, considering factors like machine availability, workforce capacity, and customer demand. Real-time scheduling can help adapt quickly to changes in demand or unexpected disruptions. The key to success lies in a holistic approach that combines technological advancements, process optimization, and a commitment to continuous improvement across all levels of the organization.
Wage Equity Impact on Customer Service in the Indian Hotel Sector
Authors:- Sanchita Sengupta Tuli, Dr. Farhat Mohsin
Abstract-In recent times, salary parity has surfaced as a prominent element impacting the dynamics of the Indian hospitality industry, especially concerning customer assistance. This research examines the complex connection between salary fairness and the excellence of customer assistance, considering the current shortage of manpower in the sector. Notwithstanding the escalating figures graduating from hotel academies, the industry persists in grappling with recruitment and retention predicaments. One prominent underlying factor is the current remuneration practises which frequently exhibit notable discrepancies. This disparity not only discourages employees but also indirectly affects the service provided to customers. Possible resolutions involve the reorganisation of remuneration bundles to cultivate a perception of equity and the implementation of periodic educational initiatives to bridge proficiency disparities. By giving precedence to salary parity, the hotel industry can not just improve employee welfare but also greatly elevate the quality of customer assistance, paving the path for enduring expansion and competitiveness in the field.
Investigation on Bamboo Fibre Concrete by Using Partial Replacement of Dolomite Powder in Cement
Authors:- Asst. Prof. J.Sree Naga Chaitanya, Prof. & HOD Dr.K.Chandramouli, Asst. Prof. Sk.Sahera, B.Tech. Student K V Suresh
Abstract-The most common material used in construction is concrete. Concrete is a composite material made of fine and coarse aggregate held together by a flowable cement paste. In order investigate the characteristics of bamboo fiber reinforced concrete; a brief experiment is carried out in this work employing 1% bamboo fibers while keeping a consistent. An amount of dolomite powder to replace some part of the cement, at varying percentages of 5%, 10%, 15% and 20%,. to evaluate the concrete’s split tensile and compressive strengths after 28, 56 and 90 days.
An Experimental Investigation on Concrete Using Titanium dioxide and Metakaolin as Partial Replacement of Cement
Authors:- Prof. & HOD Dr.K.Chandramouli, Asst.Prof. J.Sree Naga Chaitanya, Asst.Prof. SK.Sahera,
Abstract-Building construction plays a crucial role in the world’s rapid development, as is well acknowledged. We considered replacing part of the concrete’s proportions with the following methods in order to preserve our natural resources. This study has focused on the blended concrete’s compressive strength and split tensile strength. The clay mineral kaolinite is transformed into a different form called metakaolin. In addition to being used frequently in the creation of ceramics, metakaolin can also be substituted for cement in concrete.Titanium dioxide is a cementation material that can partially substitute cement in concrete.Metakaolin is replaces wth cement by 15% maintaing constant and added titaniumdioxide with different percentages of 0.6%,0.8%,1% and 1.2% with cement.To determine the compressive and split tensile strength of concrete.
A Review Paper on RF Controlled Spy Robot with Night Vision Camera
Authors:-Suchitra Jagtap ,Sakshi Mate, Shamal Shrikhande, Suyog Adate,
Abstract- In today’s era of advanced technology and surveillance needs, the development of a remotely operated spy robot equipped with a night vision camera has become increasingly relevant. This abstract provides a concise overview of a project aimed at designing and building an RF (Radio Frequency) controlled spy robot integrated with a night vision camera system. The RF Controlled Spy Robot with Night Vision Camera is a multifunctional robotic system designed to navigate and explore remote or hazardous environments covertly. The robot is equipped with an array of features to ensure efficient operation and surveillance capabilities
Mechanical Properties on Bamboo Fibre Concrete by Using Partial Replacement of Dolomite Powder in Cement
Authors:- Asst. Prof. J.Sree Naga Chaitanya, Prof.& HOD Dr.K.Chandramouli, Asst. Prof. K.Divya, B.Tech.Student M S Aswanth Naidu
Abstract-The material most commonly utilized in building is concrete. A flowable cement paste holds the composite material known as concrete together. It is made up of both fine and coarse aggregate. In this work, a brief experiment is carried out to modify the mechanical characteristics of reinforced concrete using bamboo fibers of 1% maintaining constant a and dolomite powder as partial replacement of cement with different percentages .
Strength Studies on Concrete by Using Partial Replacement of Groundshell Ash With FineAggregate and Zeolite Powder With Cement
Authors:- Prof.& HOD Dr.K.Chandramouli, Asst.Prof. J.Sree Naga Chaitanya, 3Asst.Prof K.Divya, B.Tech. Student Shaik Khadeer
Abstract-When cement and water are combined, aggregate a hard, chemically inert particle material—forms a link with structural materials. Sand and gravel are the two most common types of aggregate. Through experimental research, the consequences of partially replacing cement in concrete with zeolite powder on its properties were examined. In varying proportions, zeolite powder can be used in place of cement: 5%, 10%, 15%, 20%, 25%, and 30%. In this experimental study, the feasibility of partially replacing fine aggregate with groundnut shell ash was evaluated.For M40 concrete, powder and ash were used in place of 2.5%, 5%, 7.5%, or 12.5% fine aggregate in different concrete compositions.The properties of these concrete mixes were investigated in both fresh and hardened concrete environments.After 28,56, and 90 days, the cube samples were moulded, cured, and assessed to determine their compressive strength.
Strengthening on Concrete Using Titaniumdioxide and Metakaolin as Partial Replacement of Cement
Authors:-Asst. Prof. J.Sree Naga Chaitanya, Prof.& HOD Dr.K.Chandramouli, Asst. Prof. K.Divya, B.Tech.Student V.Vijay kumar
Abstract- Building construction is widely considered to have a critical role in the world’s rapid development. In order to preserve our natural resources, we investigated replacing some of the concrete proportions with the methods listed below. This research concentrated on the compressive strength and split tensile strength of mixed concrete. The clay mineral kaolinite undergoes transformation into metakaolin. Metakaolin, in addition to being often used in the production of ceramics, can also be used to replace cement in concrete.Titanium dioxide is a cementing ingredient that can be used to partially replace cement in concrete.Metakaolin replaces cement by 15% while remaining constant, and titaniumdioxide is added in percentages of 0.6%, 0.8%, 1%, and 1.2% with cement.The compressive and split tensile strength of concrete must be determined.
Review on Industrial Internet of Things Furnace Control
Authors:- Shaikh Huzaifa,Shaikh Azim, Nimesh Chauhan, Asst.Prof. Prachiti Deshpande, Nutan Dhande, Abhishek Singh
Abstract- Number of disasters happens in the industry are increase ding reatextent.These disasters are mostlytriggereddue to system failure or due to carelessness monitoring and controlling of the system. Such accidents become Hazardous for human life working with that environment. To avoid such accidents happened due to system error we have to control the system parameter automatically. To automate all of the above operations using the forklift mechanism which will be useful in automation of operations. Also the quenching process is carried out automatically with the help of rack and pinion system. We’re using the ESP8266 node MCU Wi-Fi model and the Arduino board to keep the Internet of Things afloat if the furnace is off at night. After this we can control the furnace via mobile. In this we are monitoring and controlling the furnace directly via mobile using various sensors like thermocouple, proximity, thermistor and IR sensors. With this we have been able to overcome the cause of the furnace malfunction, all this we have done with the help of the Internet of Things (IOT).
Payback Analysis of Automatic Room Light Control Using Ultrasonic Sensor
Authors:-Gandhar Sidhaye, Aditi Datekar, Prem Suryavanshi, Aryaman Jain, Anushka Rawat, Ishan Upadhyay, Ishani Kushwaha
Abstract- Nowadays, there is an increasing demand for energy saving techniques in residential, industrial, institutional, clinical and other multipurpose indoor and outdoor applications.This project is an attempt to implement a small system to save the energy used in lighting and reduce wasted energy by trying to control the lighting for the design of a miniature house by turning off the lighting of the empty places of people, as well as by controlling the intensity of lighting during the hours of the day (in the case of sunlight availability and during the absence of sunlight). Hence, the authors propose a universal lighting control device—named Automatic Light Control and Human Count Device—accomplished mainly using Arduino UNO R3. In this present paper, a speculative analysis has been done to study the psychology behind sensors.
A Comprehensive Strength Influence Effect Observation in Modified Road Construction Process by Using Geosynthetics
Authors:-Kalyani, Prof. Shashikant B. Dhobale
Abstract- This study covers a literature search and review to obtain information on geotextile applications related to pavement construction. Applicable information-from this study, if sufficient, would then be used to prepare guidelines on design application, material specifications, performance criteria, and construction procedures for improving subgrade support with geotextiles in general aviation airport pavements. The study revealed that there are numerous design procedures available for using geotextiles in aggregate surfaced pavements and flexible pavement road construction. However, there is no generally accepted procedure for either type construction. The state-of-the-art has not advanced to the point where design procedures for using geotextiles in paved airport construction are available. Construction/installation procedures are available for using geotextiles in aggregate surfaced pavements and flexible pavements for roads, and these may be used as an aid in recommending procedures for airport construction. Results of comprehensive tests by researchers indicate that geogrids have more potential than geotextiles for reinforcement of flexible pavements. Until design procedures for flexible pavements for airports incorporating geotextiles are developed, current standard airport pavement design procedures should continue to be used, and if geotextiles are included in the structure, no structural support should be attributed, .to geotextiles. Further research on the use of geotextiles to improve subgrade support for general aviation airports should be delayed until the laboratory grid study and field grid tests are completed.
Reactive Power Compensation Assessment By Integrating Solar Power Into The Grid, Considering: Technological Advancement, Current Challenges, And Future Direction. A Review
Authors:-Aliyu Sabo, Abdul aziz Abubakar
Abstract- This paper deeply presents a comprehensive review on assessment of reactive power compensation on grid-connected wind farms, considering technological advances, current challenges, and proposed future directions. Renewable energy (RE) sources particularly wind energy, have garnered increasing interest in electricity generation. Researchers have undertaken multiple efforts to discover effective solutions for harnessing wind energy, through comprehensive studies and extensive research. The interaction between the power grid and individual units of wind power producers has the potential to disrupt stable operations due to power system instability Among these challenges, the issue of voltage instability within the power system is particularly significant, as it can lead to voltage collapse in the absence of appropriate stability control. To mitigate the challenge, Reactive power compensation is vital ensuring that the system stability is maintained, there are always challenges ranging from technical and environmental challenges among others, but these can always be adequately curbed through technological advancements explorations.
Network Session Intrusion Detection by EBPNN Forest and Modified BGO
Authors:- Arpita Das, Prof. Sumit Sharma
Abstract- Communication Network of devices resolves different major minor problems. Secure communication increase the reliability and authenticity of the network. Many of researchers proposed different models for network security. This paper has proposed a model for intrusion detection in network. Network nodes behaviour was used for the training of neural network. In order to reduce the training feature vector modified Bio Geographic optimization algorithm was proposed. In this modified BBO emigration was done by the influence of other. Experiment was done on real network dataset. Results shows that proposed modle has improved various evaluation parameters.
E-Commerce Based Chat Bot System Using Text Mining Algorithm
Authors: – Asst. Prof.Mr.M.Anand, Asst. Prof.Mr.M.Saravanan, Atla Sasikanth Reddy, Bathini Sai Bharath Kumar, Chigicherla Dhanunjaya
Abstract- Internet purchasing is booming in the current e-commerce landscape. As a result, there is room for advancement in product recommendation systems. Because users need a connection to the system. The user experiences personalised attraction as a relationship progresses. The technology encourages customers to return and spend more money in addition to monitoring and analysing their purchasing behaviour. The tiresome task of people looking through endless categories for what they want is eliminated by the suggestion system. Instead, they use the conversation to weed out superfluous information and provide the consumer what they want. Online shopping provides many benefits, but there are also restrictions and disadvantages that need to be taken into account. The consumer can be upset if the requested product and the one actually received do not always match. Enhancing the current functioning of these systems has become essential since customer requirements change on a regular basis. The history of internet shopping indicates that there will soon be a big need for recommendation systems. A conversational bot that recommends things to customers based on their requirements is being introduced by research. With little user input, the chat bot effectively processes orders and suggests the best item. The product database is utilised in this instance, however this may be done on a much larger scale. The consumer communicates details about the scent to the chatbot. Based on the user’s description, it will also suggest relevant items.
Wind and Seismic Analysis of RCC Building Using ETAB
Authors:-M.Tech Scholar, Manoj Chopdey, Professor Dr. Rajeev Chandak
Abstract- The structural integrity and performance of Reinforced Concrete (RCC) buildings are paramount considerations in the face of natural disasters such as earthquakes and severe wind events. As the global population continues to concentrate in urban areas, the vulnerability of infrastructure to these dynamic forces becomes a pressing concern. Wind and seismic analyses are integral components of the design and evaluation process for structures, especially in regions prone to these hazards. This research is focused towards presenting the comparative analysis of a G+25 story structure to understand the effect of wind and seismic load on RCC structure. The modelling and analysis are performed using ETAB software. The G+25 RC multi storey framed building is considered for analysis to know the realistic behaviour during wind and seismic load with the general plan and elevation.
Driver Dizziness Monitoring and Alert System
Authors:-Prateek Raj, Kinshuk Aneja , Seema Kalonia , Ajay Kumar Kaushik , Sunil Maggu
Abstract- The majority of accidents that have been reported in our nation are the result of drivers becoming distracted or feeling sleepy. Major accidents are often the result of driver fatigue that often results in the driver becoming drowsy and falling asleep. Nevertheless, there are early signs of exhaustion that can be identified before a serious situation arises, therefore identifying and detecting driver fatigue remains a research problem. Most traditional tiredness detection techniques rely on behavioral characteristics; others require expensive sensors, and others are intrusive and could distract drivers. In this research, we have developed a Dlib model and Python Driver Drowsiness Detection System. This approach can lower the amount of traffic accidents, and it is also simple to adopt because it doesn't call for direct interaction between the driver and the vehicle. The system uses adaptive thres holding to determine the driver's level of tiredness and recognizes facial landmarks. It also computes the Eye Aspect Ratio (EAR). The suggested strategy has been put to the test using machine learning techniques.
A Study on Impact of Carbon Credits on Financial Performance of Tesla Incorporation
Authors:- Yash Jain, Srishti Mishra, Sparsh Jain, Pritish Kumar
Abstract- Carbon credits have had a significant positive impact on the financial performance of Tesla Inc. In 2021, carbon credit sales generated $1.58 billion in revenue, representing 3.3% of Tesla’s total revenue. In 2022, carbon credit sales generated $1.78 billion in revenue, representing 5% of Tesla’s total revenue. This revenue has helped to offset the rising costs of raw materials and other expenses and has contributed to Tesla’s record-breaking profitability in recent years. Carbon credit sales have also helped to improve Tesla’s profitability. In 2021, Tesla’s net income margin was 12.6%, significantly higher than the average net income margin for automakers. In 2022, Tesla’s net income margin was 14.7%, the highest in the company’s history. The impact of carbon credits on Tesla’s financial performance is expected to continue to grow in the coming years. Governments around the world are implementing carbon pricing policies to reduce greenhouse gas emissions. Carbon pricing policies can increase the cost of production for automakers. However, Tesla can offset these costs by selling carbon credits. Overall, carbon credits have had a positive impact on Tesla’s financial performance. They have helped to increase revenue, improve profitability, and reduce risk.
Balancing Multilingual Model Training Data Using Exponential Smoothing
Authors:- Deepanjan Kundu
Abstract-Initially, NLP models were language-specific, addressing each language in isolation due to distinct linguistic characteristics. However, with the advent of transformer-based architectures, multilingual models have emerged as a more efficient approach. These models demonstrate superior performance, particularly in classification tasks for low-resource languages, by leveraging joint pre-training across multiple languages. A key focus of this article is the challenge of handling low-resource languages within multilingual models. We discuss the issue of data imbalance, where languages with abundant resources overshadow those with less data, impacting overall model performance. To address this, the article examines the use of exponential smoothing in training data sampling. This technique adjusts the probability of language selection, enhancing the representation of low-resource languages while maintaining the quality for high-resource languages. We provide mathematical formulations and practical scenarios illustrating the effectiveness of this approach. The article concludes by underscoring the significance of exponential smoothing in both NLP and multi-locale models, highlighting its role in ensuring balanced training data and improving the performance of multilingual models. This article contributes to the understanding and development of more equitable and efficient multilingual NLP models.
Invoice Processing Using Robotic Process Automation
Authors:-M. Tech. Scholar Srishti Kaushik, Asst. Prof. Sushil Sharma
Abstract- This paper describes our recent effort to develop an automatic application to transform invoice processing in Finance operations. As a prime example of the technology’s potential for driving efficiency, Robotic Process Automation (RPA) can be applied to a number of finance and accounting operations, invoice processing. RPA Data Bot can automate data input, error reconciliation, and some of the decision-making required by finance staff when processing invoices. At the same time, automation is able to limit errors in such processes and reduce the need for manual exception handling. UiPath’s RPA Data Bot are able to constantly monitor a dedicated folder where invoices are saved by employees (or other Data Bot) in PDF format. Once robots detect the presence of an invoice in the folder, they begin to extract information from the document. Using intelligent Optical Character Recognition i.e., FOTT and natural language processing capabilities, Data Bot are able to read out the information that is visible on the invoice. After robots extract the key information from each invoice, they use their credentials to open the company’s database or enterprise resource planning system, if not already open. The robots then start processing the invoices one-by-one by transferring over the relevant invoice information. During this whole process, the Data Bot are also running background activities such as monitoring the dedicated invoice folder or its email address, performing basic checks to see if the company’s database is open, and verifying whether vendor information (e.g. VAT number) on the invoice matches what is already in the database.
Are Virtual Interviews Better than In-Person Interviews
Authors:-Vishal Gangwani, Sumit Kumar Singh, Prathmesh Jadhav, Ayush Singh
Abstract- Virtual interviews have become a well-liked replacement for conventional in-person interviews in the ever-changing world of recruitment. This study explores the issue of whether virtual interviews are more effective than in-person ones. This study seeks to thoroughly examine the advantages and disadvantages of both interview formats by looking at various aspects, including candidate experience, hiring results, cost-efficiency, and environmental impact. The results of this study provide useful information for businesses looking to improve their hiring procedures and choose the interviewing technique that best suits their objectives. This research contributes to a comprehensive understanding of each format’s benefits by analyzing the distinct advantages and disadvantages of virtual and in-person interviews, eventually assisting organisations in making wise decisions about their interview tactics.
A Study on the Impact of Finance and Technology towards the Rapid Evolution of Open Banking
Authors:-Nripendra Singh, Himanshi Sankhla, Lalit Singh, Vartika Mudgal
Abstract- In the contemporary landscape of financial services, the convergence of finance and technology has ushered in a transformative era, prominently manifested in the phenomenon of Open Banking. This study seeks to unravel the intricate dynamics between finance and technology and their collective influence on the swift evolution of Open Banking.
The research engages in a comprehensive exploration of the symbiotic relationship between finance and technology, examining how technological innovations act as catalysts for financial sector advancements. Emphasizing the pivotal role of digitalization, artificial intelligence, block chain, and other cutting-edge technologies, our investigation delves into their collaborative impact, fuelling the rapid expansion and adoption of Open Banking models across the global financial ecosystem.
Furthermore, the study critically analyses the implications of Open Banking on traditional financial institutions, fintech disruptors, and, most importantly, the end-users. Through empirical evidence and case studies, we aim to illuminate the tangible benefits and challenges posed by this paradigm shift, shedding light on how Open Banking fosters competition, enhances financial inclusion, and redefines customer-centric financial services.
The findings of this research not only contribute to the academic understanding of the subject but also offer valuable insights for industry stakeholders, policymakers, and practitioners. By elucidating the synergistic dynamics of finance and technology in the context of Open Banking, this study provides a roadmap for navigating the evolving financial landscape, fostering innovation, and ensuring a resilient and inclusive financial future.
Neural-Market Dynamics: Unveiling Future Trends with CNN-LSTM Ensemble for Stock Price Forecasting
Authors:-Madhur Narang, Kushagra Sahani,Asso. Prof. Dr. Neha Agrawal, Asst. Prof. Ms. Meenu Garg
Abstract- The stock market is the platform where anyone can buy and sell or trade shares of public companies, and for that predicting the stock price helps us to forecast the future value of the company shares, derivatives, and mutual funds. So, while doing predictions of the stock market we have to keep some key points in our mind such as No one can accurately predict the future movement of the stock market because the stock market is a composite and volatile system, and many factors can affect its performance.
To evaluate a company’s financial stability and performance, fundamental analysis is used. On the other hand, for reviewing historical price and bulk data, technical analysis has been carried out to recognize tendencies and patterns. Risk management, while investing in the stock market carries inherent risks, and to mitigate those risks, it is crucial to spread out investments and establish stop-market orders, and other techniques.
The aim of this paper is to suggest deep learning techniques in order to predict the stock prices of different companies such as AAPL(Apple), BAM (Brookfield Asset Management), and UBER and using two different models such CNN (Convolutional Neural Network) in CNN the paper uses One -Dimensional CNN (1D CNN) and LSTM (Long Short-Term Memory) uses Bidirectional LSTM.
Synthesis Characterization CNS and Analgesic Studies of methyl 4-[(1E)-3-(Cyclopropylamino)-2-(2-Fluorophenyl)-3-Oxoprop-1-en-1-yl]Benzoate
Authors:-Asst. prof. Dr. P. Deivanayagam, Dean Dr. Selvaraj, Vice principal Rajarajan
Abstract- Organic synthesis is applicable in everyday life. Organic synthesis is very important in medicinal chemistry. A literature review of the medicinal chemistry approach is briefly carried out. In this article, 4-formylbenzoic acid is treated with thionyl chloride to form methanol-4-formylbenzoate. The product obtained is treated with 2-flurophenylacetic acid to give product 2. Product 2 is treated with cyclopropylamine to give the final product. The final product is treated with CNS and analgesic studies and the result is obtained.
Relationship between Electronic Banking and Customer Satisfaction
Authors:-Shaun Mendonsa, Akash Shukla, Akash, Venkata Veda Vyas Dega
Abstract- This research paper explores the relationship between electronic banking and customer satisfaction in the banking sector of India. The main objective of this study is to investigate the impact of e-service quality on customer satisfaction in the banking sector. The study uses a mixed research approach, comprising both descriptive and analytical research. A survey consisting of 12 questions was conducted, and the responses were collected from 59 respondents. The study found that e-service quality is the most significant factor impacting customer satisfaction in the banking sector. The study concludes that banks can gain a competitive advantage by focusing on the quality of electronic banking services, which helps attract and retain a strong customer base. Limitations of the study are also discussed, and suggestions for future research are provided.
Prevention of URL Attacks by Analyzing Browser Extension
Authors:-Amit Choudhary, Anusha. M. R, Devika. L.R, Manushree M, A.M. Prasad
Abstract- Rapid growth of internet usage has led to cyber-attacks. Malicious cyber criminals exploit vulnerabilities in a browser to initiate cyber-attacks which affects user data, privacy and system integrity. Nowadays many technical solutions on URL attacks were developed, but these approaches were either unsuccessful or unable to identify URL attacks and detect malicious code efficiently. One of the draw-back is due to poor detection strategy and less adaptability to new URL attacks. This work outlines research initiative focused on the prevention of URL attacks through the analyses of browser extension. Thus, the main objective of our project is to design and develop a python-based web browser extension that focuses on identifying URL attacks by extracting features from URL and integrating with various anti-virus tools. The extension combines rule-based analyses of feature extraction technique with external anti-virus services and tools to enhance the accuracy of URL attacks identification.
The Internet and Social Media Contribution to Inclusivity and Exclusivity in Society
Authors:-Geofrey Mwamba Nyabuto
Abstract- The Internet as loosely defined, is a network of networks (Kumar & Deepa, 2015). Behind these networks are many social and economic opportunities that have become key enablers on many fronts. It is through the Internet that social media has become a possibility and whose use has directly or indirectly led to either the inclusion or exclusion of individuals from one or more aspects of social life. With inclusion, the use of social media has ensured that individuals have equal opportunities, access to resources and chances of participation regardless of their background and location. On the other hand, in exclusivity, social media or the Internet denies some of its users a chance to be part of the bigger picture due to one or more reasons.
This paper does a systematic review of the literature on the Internet, what it is and the different theories that seek to explain its originality or existence. The paper also reviews social media as a product of the Internet and how it has been used to enhance inclusivity and exclusivity in the same measure. It further discusses some of the contributions social media has made to societies as well as how it has been used to enhance inclusion and exclusion. With examples, the paper shows how social media has been incorporated and become part of our normal life. Lastly, it summarizes some of the strategies that can be implemented to minimize exclusion and how society plays a pivotal role in achieving this.
Impact of Digital Marketing and AI in FMCG (E-commerce) Consumer Purchase Patterns
Authors:-Bhavesh Gattani, Shamik Saha, Komal Gill
Abstract- In FMCG e-commerce, digital tactics are crucial in changing customer purchasing trends and behaviours. This study emphasises advertising strategies and the tactical application of consumer data as it investigates the significant effects of digital marketing and AI-driven tools on consumer patterns. By utilising cutting-edge technologies like chatbots, complex algorithms, and user behaviour analysis, businesses may gain profound insights into their clientele, facilitating customised and customer- focused online shopping experiences. This shift mostly depends on customised digital tactics that use customer data to design distinctive e-commerce experiences. This strategy also applies to advertising, using data-driven techniques to provide pertinent and compelling advertisements that are tailored to the unique requirements and tastes of FMCG customers. When it comes to FMCG e-commerce advertising, the use of digital and AI techniques has a big impact on customer engagement and purchasing behaviours. Businesses may maximise the impact of their ads by optimising the selection and delivery of their ads with the help of these tools’ insights. This study examines the impact of digital strategies on FMCG e-commerce customer behaviours by combining consumer data with insights from these strategies. Interestingly, these tactics—which are especially noticeable in social media postings and pop-up advertisements—stimulate instant wants, enable interactive interfaces, and encourage higher spending in the FMCG e-commerce space.
Determinants of Food grains Production in India
Authors:-Dr. Juhi Shamim
Abstract- Present paper discusses the determinants of food grains production in India. The Indian economy has changed fundamentally over time with the foreseen decrease in agriculture’s share in gross domestic product (GDP). There is high burden on agriculture to produce more and to raise the income of farmers. India’s manufacturing sector saw unpredictable growth and its share in GDP has nearly stayed steady at 15 percent over the most recent three decades. Under these conditions, it is valuable to investigate the determinants of agriculture growth. There are countless determinants that influence food grains production. Some of them are discussed in this paper.
A Study to Know “Impact of AI on Sustainable Agriculture in India”
Authors:- Rahil Shah, Nikhil Kumar Menaria, M. Pradyumna, Rajdeep Singh Thakur Lodhi
Abstract- Artificial intelligence (AI) has the potential to revolutionize sustainable agriculture practices by enhancing building performance, energy efficiency, and reducing carbon emissions. In India, where the demand for sustainable building design is growing due to increasing energy costs and environmental concerns, AI can play a significant role in optimizing building performance. This study examines the impact of AI on sustainable agriculture in India and explores the potential benefits and challenges associated with the integration of AI in building design. Using a qualitative research approach, the study analyzes the existing literature on AI and sustainable agriculture in India. The findings reveal that AI can optimize building performance by providing real-time feedback on energy consumption, predicting future energy demand, and optimizing building systems. However, the integration of AI in sustainable agriculture also presents challenges, such as the need for specialized skills and knowledge, and potential privacy concerns associated with the collection of data. The study concludes that AI has the potential to significantly impact sustainable agriculture in India and recommends further research to explore the feasibility of AI integration in sustainable building design.
A Critical Analysis of an Application for the Donation Ecosystem
Authors:-Gurunath Waghale, Lavanya Goyal, Pratham Agarwal, Varun Ved, Ananya Shukla, Ayush Walekar
Abstract- This research works explores the effectiveness of donation applications in facilitating charitable giving. The paper investigates the features and design of popular donation applications, their impact on donor behavior, and the benefits and drawbacks of using donation application. The research methodology includes a literature review, survey data analysis, and case studies of organizations that have successfully used donation applications to increase donations. The findings of the study suggest that donation applications are effective in increasing charitable giving by making the donation process convenient, accessible, and secure. However, the success of donation applications is also dependent on factors such as the user experience, the credibility of the organization, and the effectiveness. The paper concludes with recommendations for non-profits on how to leverage donation applications to maximize their potential and improve donor engagement.
Demand Forecasting Using MLR-ARIMA Hybrid Model
Authors:-Vaibhav R. A. Prasad, Anunita Bhattacharya
Abstract- Data analytics (DA) is becoming increasingly important in supply chain management (SCM) due to its ability to provide valuable insights that can improve efficiency and decision-making. One of the key applications of DA in SCM is demand forecasting, which involves predicting future demand for products or services. Accurate demand forecasting is crucial for ensuring that the right amount of inventory is maintained, reducing the risk of stock outs, and optimizing production and logistics processes. There are several algorithms that can be used for demand forecasting in SCM, and they can be broadly classified into two categories: time-series forecasting and causal forecasting. Time-series forecasting algorithms rely on historical data to make predictions. This study will Evaluate both time-series and casual algorithms and study their efficacy and uses.
To What Extent Does Consumer Awareness Influence the Preferences of Individuals Towards Neo Banks in The Indian Banking Sector?
Authors:- Ansuman Ray, Ashish Singh, Nishtha Rastogi, Aanchal Agrawal
Abstract- This study investigates the landscape of neo banks in India, focusing on consumer awareness and preferences within the evolving digital banking sector. Acknowledging the global significance of neo banks and the transformative impact they pose to traditional banking, the research addresses a notable gap by examining their adoption in the Indian context. The study explores factors influencing consumer behavior, including convenience, efficiency, trust, and the integration of financial technologies. Employing a comprehensive research methodology, encompassing surveys, interviews, and demographic considerations, the research aims to provide nuanced insights into how neo banks are reshaping the banking experience for Indian consumers. By bridging global insights with specific Indian market nuances, the study contributes to both academic and practical understanding, informing strategies in the banking and fintech industry to better align with the preferences of Indian consumers in the digital era.
Crediguard Sentinel Using Machine Learning and Data Science
Authors:- Ms. Shelake R.M., Ms. Magar A.S., Mrs. Bhalerao D.N., Ms. Thorat P.T.
Abstract-The abstract outlines the importance of credit card fraud detection, emphasizing the role of Data Science and Machine Learning in addressing this issue. The project aims to demonstrate the application of machine learning to model a dataset for Credit Card Fraud Detection. The problem involves creating a model based on historical credit card transactions, distinguishing between legitimate and fraudulent ones. The primary objective is to detect all fraudulent transactions while minimizing false positives. The approach includes analyzing and pre-processing datasets, as well as deploying anomaly detection algorithms like Local Outlier Factor and Isolation Forest on PCA-transformed credit card transaction data. Overall, the project focuses on leveraging machine learning techniques for accurate and efficient credit card fraud detection.
Green Cloud Computing: A Framework for Sustainable and Efficient Cloud Infrastructure
Authors:- Professor Dr. Angajala Srinivasa Rao, Professor Dr. Sudheer Pullagura
Abstract-As the demand for cloud computing services continues to soar, concerns about its environmental impact have become more pronounced. This research-oriented descriptive article aims to address this issue by proposing a comprehensive framework for Green Cloud Computing. The framework focuses on minimizing the environmental footprint of cloud computing by optimizing energy consumption and resource usage. Through an exploration of key principles, challenges, and real-world applications, this article provides insights into building a sustainable and efficient cloud infrastructure. Keywords, relevant studies, and references are included to serve as a valuable resource for researchers and practitioners in the field.
A Review On Improved Quality Of Roadway In Highway Construction And Maintenance Using Soil Mechanics
Authors:- Tushar Parashar, Assistant Professor Jitendra Chouhan
Abstract-Soil is an integral part of the road pavement structure as it provides the support to the pavement from beneath. If the stability of the soil is not adequate for supporting the wheel loads, the properties of soil should be improved by soil stabilization technique. Soil stabilization is the alteration of one or more soil properties by mechanical or chemical means to create an improved strength of existing soil. In the present situation as the industrialization and urbanization is taking place has generated many wastes. This leads to depleting landfill space, soil contamination and many other hazardous effects, hence in this review of study utilization for improving the soil properties is made.
A Study to Know – Use of AI For Personalized Recommendation, Streaming Optimization, and Original Content Production at Netflix
Authors:-Komal Khandelwal, Sarvanaman Patel, Jarni Patel, Monika Pnachal
Abstract-Netflix has become a household name in the entertainment industry due to its innovative use of data science and artificial intelligence (AI) in its business strategy. This paper provides a comprehensive overview of how Netflix has leveraged data science to gain a competitive edge in the industry. The paper explores how Netflix uses personalized recommendations to enhance the user experience. Netflix’s recommendation system is powered by a collaborative filtering algorithm that analyses user data, such as viewing history and ratings, to suggest content that is likely to be of interest to the user. The recommendation system is continuously improved through machine learning algorithms, which learn from user behaviour and preferences to provide more accurate recommendations. The paper also discusses how Netflix uses streaming optimization to deliver high-quality video content to its users. Netflix’s AI-powered encoding system analyses each video and optimizes the encoding process to reduce file size without compromising video quality. This enables Netflix to deliver high-quality video content with minimal buffering time, even in areas with slow internet connectivity.Another aspect of Netflix’s success is its production of original content. Netflix uses data science to identify gaps in the market and understand audience preferences, enabling it to produce highly engaging original content. The company uses machine learning algorithms to analyse viewer data and identify trends and patterns that inform its content creation strategy.However, implementing data science in the entertainment industry comes with its challenges and limitations. Netflix faces issues such as bias in the recommendation system, privacy concerns, and the high cost of producing original content. Nevertheless, Netflix continues to invest in data science and AI to improve its services and stay ahead of its competitors. This paper provides a comprehensive understanding of how Netflix has implemented creative data science and AI in its business strategy to become a leader in the entertainment industry. The paper highlights the importance of personalized recommendations, streaming optimization, and original content production in Netflix’s success. It also emphasizes the challenges and limitations of using data science in the entertainment industry and the need for continuous improvement and innovation.
A Study to Know – Accounting Concepts and Conventions
Authors:-Amanjeet kaur, Ritika khungar
Abstract-Financial statements are required by a wide variety of users for their decision- making and they also affect economic decisions of enterprises. In order to fulfill this purpose, some accounting professionals have developed a framework of ideas (accounting concepts and conventions) that is generally accepted as a foundation for preparing financial statements. This paper throws light on various accounting postulates and how these are important to different users of financial statements.
A Review Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques
Authors:-Prabhat Patel, Dr. Sunil Sugandhi
Abstract-To create a Machine Learning-based Intelligent Traffic System that can monitor and regulate traffic flow efficiently. This system involves the use of cameras and sensors placed on roadways to collect real-time data on traffic flow and identify congestion points. The collected data is then processed and analyzed using machine learning algorithms to generate actionable insights that can be used to optimize traffic flow. One of the key benefits of this system is its ability to automatically adjust traffic signals to prioritize emergency vehicles such as ambulances during times of heavy traffic. This can significantly reduce response times and improve the chances of saving lives in emergency situations. Additionally, the system can provide real-time traffic updates to drivers via mobile apps or digital displays, allowing them to avoid congested areas and take alternative routes. The implementation of this system can also lead to a reduction in carbon emissions and fuel consumption by reducing the amount of time vehicles spend idling in traffic. Moreover, it can help to minimize road accidents caused by congestion and improve overall road safety.
The Omnichannel Inventory Puzzle
Abstract-In the dynamic landscape of modern retail, any business focusing on providing seamless and integrated shopping experience across various channels to its customers cannot overlook implementing omnichannel strategies. This article explores the imperative role of effective inventory management in achieving success and providing a positive customer experience within the omnichannel paradigm. The article walks you through the ordering approach, the flow of inventory from node to node, the challenges faced and effective strategies for resolution as well as proactive risk mitigation. The article provides insights on identifying customer preferences and planning inventory at the right network node to support the best possible customer experience. Inbounding inventory in the right levels at the appropriate nodes the first time (instead of executing inventory transfers to balance the network), managing capacity and labor to cope up with the fluctuating inventory levels, building strong partnerships with suppliers to enable reliability, managing shrink and finally unlocking a mechanism to effectively track and monitor in-network and in-transit inventory levels will form the strong foundational pillars for managing omnichannel inventory.
Intrusion Detection System Using Machine Learning: An Algorithm Study
Authors:-Yadgude Samrudhi Ravindra
Abstract-Machine Learning is an evolving domain in the field of technology. Its algorithms are capable of detecting various patterns, making decisions based on them and adapting to an environment that is dynamic. In today’s digitally interconnected landscape, the surge in cyber threats necessitates innovative approaches to fortify network security. Cyber security demands an Intrusion detection system to safeguard networks from evolving threats. This research delves into an advanced exploration of four intrusion detection methods—Autoencoders, Support Vector Machines (SVM), XG Boost, and Principal Component Analysis (PCA) coupled with a classifier. Going beyond the conventional analysis, this study not only explains the specific scenarios conducive to each method but also unveils the intricacies of their applicability, providing a deep understanding of when to deploy these techniques based on their advanced advantages and potential limitations.
Improving Financial Sentiment Classification on ELECTRA Using Adversarial Attacks
Authors:-Jibin Rajan Varghese, Divya Susan Thomas
Abstract-This paper focused on the task of sentiment analysis within the financial domain, aiming to classify text into positive, negative, or neutral sentiments. Employing an ELECTRA-small model initially pre-trained as a general sentiment classifier, a baseline model was trained on financial sentiment data, achieving an accuracy of 0.8547 on the Financial Phrasebank dataset. Misclassification of data between positive and neutral sentiment classes was the most pronounced cause of error. While attempts to augment the model’s financial vocabulary using the Fin RAD dataset led to decreased model accuracy, the introduction of adversarial attacks proved to be successful in improving the performance of the baseline model. Particularly, the model trained on data augmented with Text Fooler-generated adversarial examples exhibited a 4.68% increase in accuracy to 0.9015. This approach also reduced misclassifications between positive-neutral classes, thus mitigating the major challenge observed in the baseline model. This result is significant considering how well the model generalized to a challenging problem on a dataset that it never encountered before and sets this result apart from other contemporary work in literature which uses a subset of Financial Phrase bank as training data for fine-tuning.
Review on Experimental Study on Mechanical and Durable Properties of Self Curing Concrete by Using Polyethylene Glycol 600 and Light Weight Fine Aggregate
Authors:-Aditya Joshi, Assistant Professor Kishore Patil
Abstract– In the present day’s concrete is one of the most rapidly used construction materials in civil engineering due to its high-quality durability and its strength. The durability and strength of concrete will be fulfilled only if it is properly cured. For curing of the concrete large amount of water is required so, in recent year’s new technique developed known as self-curing in which cure of concrete done by itself by retaining moisture content in the concrete. This paper represents the methods of self-curing concrete and past work done so far in this area. It was found that various chemical admixtures such as (PEG), (PEA), (PVA), (SAP), etc and naturally available material like lightweight aggregate, light expanded clay, wood powder, etc. were used as a self-curing agent. Hence this paper focuses on chemicals used, physical and mechanical properties such as (Compression strength; Tensile strength; workability; durability) of self-curing concrete. Literature reviewed shows the different techniques used for self-curing concrete. Keywords— self-curing concrete; mechanical properties; physical properties; lightweight aggregate (LWA), (PEG), (PEA), (PVA), (SAP).
Review on Matlab Fuzzy Logic Based and Predictive (Radial Basis Function, Rbf) Hvac Controllers
Authors:-Manmohan Wadia, Assistant Professor Khemraj Beragi
Abstract– The use of fuzzy logic controllers in refrigeration and air conditioning systems, RACs, has as main objective to maintain certain thermal and comfort conditions. In this sense, fuzzy controllers have proven to be a viable option for use in RACs due to their ease of implementation and their ability to integrate with other control systems and control improvements, as well as their ability to achieve potential energy savings. In this document, we present a review of the application of fuzzy controls in RACs based on vapor compression technology. Application information is discussed for each type of controller, according to its application in chillers, air conditioning systems, refrigerators, and heat pumps. In addition, this review provides detailed information on controller design, focusing on the potential to achieve energy savings; this design discusses input and output variables, number and type of membership functions, and inference rules. The future perspectives on the use of fuzzy control systems applied to RACs are shown as well. In other words, the information in this document is intended to serve as a guide for the creation of controller designs to be applied to RACs.
Development of Production Layout Model to Improve Production Efficiency
Authors:-M.Tech. Scholar Shubham Gondey, Professor Shyam Barode
Abstract- With rapid increasing of demand in production, industrial factories need to increase their potentials in production and effectiveness to compete against their market rivals. At the same time, the production process needs to be equipped with the ability to have lower cost with higher effectiveness. Therefore, the way to solve the problem about the production is very important. There are many ways i.e. quality control, total quality management, standard time, plant layout to solve the problems concerning productivity. Companies which currently intend to remain competitive should always seek improvements to achieve excellence in quality through the improvement of its processes and products, and also always target the reduction of production costs by improving production efficiency and rationalization of production resources. Thus, the development of production makes that organizations have to evolve and develop organizational and operational improvements, constantly reviewing procedures and management approach as well as the processes and products in an attempt to tailor them to the needs of market.
Increasing Sale, Profit Rate and Productivity Improvement Using Supply Chain Management
Authors:-M.Tech. Scholar Jitendra Nagar, Professor Shyam Barode
Abstract– Supply chain management performs by integrating procurement, suppliers, and facilities of manufacturers, distributors, retailers, and customers while they work together by the production, buying, and sales cycles. This supply chain needs active management since it is impacted by several aspects of the control of the business-like environmental conditions, fuel prices, and so on. While a company is more aware of these aspects, it can effectively manage them. With efficient management of supply chain, production, inventory, distribution, vendor, and sale records are in strict control. The SCM shows the management of expenses at each step and offers products to customers in a quick manner. The aim of this thesis is to explore the possibility of implementing Six Sigma in SCM of Indian SMEs. The Six Sigma application in SCM of SMEs is a new paradigm for improving quality which is practiced by many academics. This thesis is an attempt to provide road map application of Six Sigma in SMEs which are normally presumed to be in the section of large industries. This case study will help the Indian SMEs to carry out such projects which can lead them towards business improvement.
Noise Filtering and Contrast Enhancement for Chest X-Ray Images
Authors:-Mukesh Patel, Prashanth Reddy Simhadri, Assistant Professor Mr. B Sateesh
Abstract– Lungs, one of the main organs responsible for the human respiratory system, are vulnerable to dangerous diseases. Hence, early detection and diagnosis of lung disease is needed; one of these is Chest X-ray (CXR) imaging. Reviewing CXR results is still done manually by doctors and radiologists, which takes time and manual effort. In order to facilitate diagnosis, the quality of the images must be increased, better image quality results must be obtained, and therefore a more accurate diagnosis must be established. In this study, various noise filters and different techniques are examined.
Leading the World towards the 4th Industrial Revolution through Virtual Reality
Authors:- Geofrey Mwamba Nyabuto, Professor Franklin Wabwoba
Abstract- The fourth industrial revolution is characterized by the convergence of various technologies including the Internet of Things, Artificial intelligence, virtual reality, and augmented reality among others. This revolution is shaping how people live, interact, and share information. Virtual Reality (VR) is one of these technologies that are revolutionizing the world. VR technology enables individuals to immerse themselves in a virtual world using special headsets, gloves and computers and has seen its application in several sectors hence improving productivity and do things that could have proven difficult or impossible. This paper explores the evolution of VR technology, its current state, and its application in real life. Through its application, the paper reviews how it has already been applied in industries like entertainment, medicine, education, automotive and others to change how things are done. By using VR, organizations can increase their productivity and give customers a better user experience, increasing sales and profits. Health and safety issues, ethical considerations and costs are also reviewed in this paper. There is a need for collaboration between content creators, developers, policymakers, and researchers to come together and utilize the full potential of this technology while addressing the current challenges.
A p2p Computing Based Load Balancing Approach in Fog Computing
Authors:-M.Tech. Scholar Hansraj Sah, Assistant Professor Jayshree Boaddh, Assistant Professor Ashutosh Dixit
Abstract- Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. Fog computing essentially extends cloud computing and services to the edge of the network, bringing the advantages and power of the cloud closer to where data is created and acted upon. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc. Central to these issues lies the establishment of an effective load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. This technique can be sender initiated, receiver initiated or symmetric type (combination of sender initiated and receiver-initiated types. Objective of this project is to develop an effective load balancing algorithm using various parameters to distribute the load efficiently among various processors.
Energy Efficient or Energy Consuming: Recycling of Solar Panels in India
Authors:-Assistant Professor Anjali
Abstract– This paper uses a more holistic approach to provide comprehensive information and up-to date knowledge on solar energy development in India and scientific and technological advancement. The paper describes the types of solar photovoltaic (PV) systems, existing solar technologies, and the structure of PV systems. Substantial emphasis has been given to understanding the potential impacts of COVID-19 on the solar energy installed capacity. In addition, we evaluated the prospects of solar energy and the revival of growth in solar energy installation post-COVID-19. Further, we described the challenges caused by transitions and cloud enhancement on smaller and larger PV systems on the solar power amended grid-system. While the review is focused on evaluating the solar energy growth in India, we used a broader approach to compare the existing solar technologies available across the world. The need for recycling waste from solar energy systems has been emphasized. Improved PV cell efficiencies and trends in cost reductions have been provided to understand the overall growth of solar-based energy production. Further, to understand the existing technologies used in PV cell production, we have reviewed mono crystalline and polycrystalline cell structures and their limitations. In terms of solar energy production and the application of various solar technologies, we have used the latest available literature to cover stand-alone PV and on-grid PV systems. More than 5000 trillion kWh/year solar energy incidents over India are estimated, with most parts receiving 4–7 kWh/m2. Currently, energy consumption in India is about 1.13 trillion kWh/year, and production is about 1.38 trillion kWh/year, which indicates production capacities are slightly higher than actual demand. Out of a total of 100 GW of installed renewable energy capacity, the existing solar capacity in India is about 40 GW. Over the past ten years, the solar energy production capacity has increased by over 24,000%. By 2030, the total renewable energy capacity is expected to be 450 GW, and solar energy is likely to play a crucial role (over 60%). In the wake of the increased emphasis on solar energy and the substantial impacts of COVID-19 on solar energy installations, this review provides the most updated and comprehensive information on the current solar energy systems, available technologies, growth potential, prospect of solar energy, and need for growth in the solar waste recycling industry. We expect the analysis and evaluation of technologies provided here will add to the existing literature to benefit stakeholders, scientists, and policymakers.
A p2p Computing Based Load Balancing Approach in Fog Computing
Authors:-M.Tech Scholar Hansraj Sah, Assistant Professor Jayshree Boaddh, Assistant Professor Ashutosh Dixit
Abstract– Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. Fog computing essentially extends cloud computing and services to the edge of the network, bringing the advantages and power of the cloud closer to where data is created and acted upon. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc. Central to these issues lies the establishment of an effective load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. This technique can be sender initiated, receiver initiated or symmetric type (combination of sender initiated and receiver-initiated types. Objective of this project is to develop an effective load balancing algorithm using various parameters to distribute the load efficiently among various processors.