bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALYSIS OF GATE LOCATION AND ITS EFFECT ON WARPAGE IN PLASTIC INJECTION MOLDING
Authors: k Chaithra , T K Lakshman Naik , Algur Veerabhadrappa , Thotappa C , Algur G Manjunath Swamy
Published: June 2024

This project emphasizes conveying a crucial message to mold designers, makers, and organizations. Moldex3D, with its powerful pre-processing tools like automatic mesh generator and intelligent modeling wizards, significantly enhances designer efficiency. Moldex3D Design's information, including material flow rate, filling rate, cooling rate, shrinkage graphs, and virtual mold, helps verify the permanent bending (warpage) in components due to non-uniform cooling rates. The analysis focused on gate location and points for an automotive tailgate lower trim plastic component. Three cases (A, B, and C) were studied, with estimated total warpage ranging from 0.15 to 15.77 mm. The minimum warpage is preferred during mold manufacturing for this component.
TEMPERATURE MEASUREMENT DURING DRILLING: SCENARIO AND TECHNOLOGIES FOR LABORATORY AND FIELD INVESTIGATIONS
Authors: S Dr. Vijay Kumar , B M Kunar Dr. , Vijee Kumar Dr.
Published: June 2024

Drilling stands out as one of the most energy-intensive technological processes employed in the realm of mining exploration. The act of drilling into rocks gives rise to heat, stemming from the friction that arises between the rock and the drill bit. This thermal generation leads to the development of stress within the rock, ultimately causing it to fail. An overwhelming 80% of the energy supplied to the drill bit is consumed by the release of heat, with a certain proportion of energy serving residual bit alterations and rock fragmentation (Dreus et al., 2016). Predominantly, abrasion wear emerges as the chief contributor to bit deterioration, as the drill bit undergoes substantial abrasion when encountering rock formations, primarily attributed to the silica content present in the rock samples (Abbas, K., 2018). This article gives an overview of various kinds of drilling operations in laboratory and field investigations with temperature measurement devices at various locations is discussed to understand the concept of operational parameters influence on various mechanical properties and its orientations.
IOT-BASED SMART LIQUID MOSQUITO KILLER FOR SMART HOMES: A PROSPECTIVE OF INDUSTRY 4.0 TECHNOLOGIES
Authors: Dhotare Mr. Sagar , Sandeep Soni Dr. , Bramhwanshi Mrs. Priya , Rohekar Mr. Chinamay
Published: June 2024

Mosquitoes kill at near about 2.7 million people each year. Currently, with over 100 million instances reviewed yearly, most reported cases will be verified. The mosquito population in India and other countries is rapidly expanding. The world's tropical and subtropical nations are susceptible to the mosquito-borne disease dengue fever. In recent decades, the global prevalence of dengue fever has skyrocketed. Purpose: We have conventional mosquito-killing equipment that is not influenced by this reason for insect killing. In this automated world, we require machines that will decrease human involvement with the machine and will automatically recognize and execute on the surroundings. For example, eradicating mosquitos and providing a safe environment for humans to live in. Findings: In the market, we are having Good Night, All Out such types of mosquitos killing machines. They are good but nowadays we need something better. This concept going to advance the mosquito-killing strategy and give us maximum output from mosquito-killing machines. Impact on Technology: We are living in an exciting era of technical and digital change. We now have AI assistance, smart assistants, autonomous cars, cobots, sophisticated cancer detection systems, and of course the Internet of Things (IoT) at our fingertips because of recent advancements in data science. As a result, a smart mosquito killer based on the Internet of Things idea is being proposed as an addition to home automation. Impact on society and environment: With the aid of IoT, we may create a machine that can be operated automatically by mobile phones, and 11timers, and will adapt to its surroundings. The proposed machine is designed to provide a safe atmosphere for humans while also utilising the utmost capacity of the machine to kill mosquitos.
HIGH POWER MICROWAVE SOURCES AND APPLICATIONS
Authors: Mukesh Kumar Alaria Dr.
Published: June 2024

The applications of conventional microwave tubes are limited due to basic nature of interaction structures used herein. However, the range of applications of microwave tubes is growing to the millimeter wave range where there are several important applications present. Some of these applications are high efficiency radar, data communication and specialized satellite communication, advanced high gradient linear accelerators, superconducting colliders and fusion plasma.
REVOLUTIONIZING TAX COMPLIANCE: SCRUTINY OF ITRS USING ADVANCED AI-DRIVEN TOOLS
Authors: Reshma Banu Dr. , H. R Mahanthesh , J. V Gowtham , B. N Mohith , Durrani Nadir
Published: June 2024

Scrutiny of ITRs using Advanced AI Tools" refers to the process of examining Income Tax Returns (ITRs) submitted by taxpayers with the aid of sophisticated Artificial Intelligence (AI) technology. The traditional method of manual scrutiny involves human tax officers manually checking and verifying the information provided in tax returns. However, with the advent of advanced AI tools, this process has been significantly enhanced and automated. The process starts with taxpayers filing their ITRs as usual. Once the returns are submitted, the AI-driven software takes over. The AI program is specially designed and self-automated, which means it can perform various tasks without direct human intervention.
THE IMPORTANCE OF INTERNET TECHNOLOGIES IN MODERN ERA
Authors: Rubini M. , Somasundaram K.
Published: June 2024

By using the web, individuals can advance in practically all circles of life. As it's an overall association of the PC organization, it can connect individuals from everywhere and make networks. It's an extraordinary approach to giving and getting to data and is accessible practically everywhere. Being quick, effectively accessible and modest, it's an extraordinary approach to trading data across the globe, saving time all the while. You never again need to sit around idly running for data - it's accessible on your PC screens currently, making the world more modest. Innovation keeps on being a basic power for change on the planet. Innovation leap forwards give undertakings more prospects to lift their efficiency and create contributions. And keeping in mind that it stays challenging to conjecture how innovation patterns will work out, business pioneers can prepare better by watching the improvement of new advances, guessing how organizations could use them, and grasping the variables that influence development and reception.
SOFTWARE DEFINED NETWORKS-A WORKING PRINCIPLES, OPERATIONS BY USING BOTTOM-UP APPROACH AND ALTERNATE METHODS
Authors: Ninu SB Dr. , V. Devi Dr.
Published: June 2024

SDN is a developing architecture that is dynamic, manageable, cost effective and adaptable making it ideal for the high bandwidth, nature of today’s applications.SDN that aims to improve the control of network and flexibility. The architecture of SDN decouples the network control to become directly programmable and the underlying infrastructure to be abstracted for applications and network services. The chapter concentrates the working of SDN, requirements of SDN, the responsibilities of SDN and the components interaction. The techniques bottom-up was utilized in the SDN device, controller and the Applications. The device is constructed by the API structure for the interaction with the layer protocol and it constitutes with the data packets to inculcate the function. The flow tables are the fundamental data structures in an SDN device, which allow the device to evaluate incoming packets and take the action based on the content of the packet that has been received.The section I contributes the functions availability of the open SDN. Section II focus the working and the alternate principles of the SDN. The Section III demonstrate the accomplishment of the SDN for the better replacement with 2 classification SDN via API’s and SDN via Hypervisor-Based Overlay Networks.This chapter defines the basement characteristics in which the SDN works in various platform. It is emergence to notice that there is no basic alternative choices to implement between the hypervisor-based overlay network approach to SDN and open SDN. The final conclusion added in this chapter are the SDN act as complete assurance strategy solution given for the physical and virtual addressing issues.
A NOVEL SLOTTED MIMO ANTENNA FOR 5 G MM-WAVES COMMUNICATION
Authors: Jetti Chandrasekhar Rao , U Srinivasa Rao , Kolavennu Kamala Devi , Yangala Karthikesh , Sanaka Sai Teja
Published: June 2024

A novel tiny two-element MIMO (multiple-input multiple-output) antenna is presented for 5G mm-wave communication. The antenna has dimensions of 4.8 × 12 × 0.508 mm3 and is composed of the Rogers RT/duroid 5880 (tm) substrate, which has a loss tangent of 0.0009 and a dielectric of 2.2. The proposed antenna features a slotted ground at the base and two U-shape patches on top of the substrate. To excite the patches, a 50-ohm microstrip line feed is used. For better impedance performance, each radiating patch has a 1.3 × 0.2 mm2 rectangular strip and a couple of rectangular slots. A U-shaped element enables the first operating band at 26.8GHz from 26.3 to 27.50GHz. Cutting hexagonal slots into the ground creates the next operating band at 48.7GHz, which spans 48.1 to 49.45GHz. The suggested MIMO antenna's isolation is improved by slots on the ground and radiating elements that are orthogonally positioned. The results manifests that the suggested antenna is appropriate candidate for 5G mm-wave communications.
THE NEXT GENERATION WIRELESS NETWORK PROTOCOL
Authors: Upadhyay Sourav Kumar , Prakash Kumar Dr.
Published: June 2024

The second-largest population in the world is found in India. Thus, as everyone wants to stay connected to modern technology, more bandwidth is required to meet their requirements, like online gaming, songs, smart messaging, and call over IP protocol. The IEEE introduced WiFi-6 technology, referred to as 802.11ax. comparing to 802.11ac (WiFi5), 802.11ax (WiFi6) has four times the network bandwidth. It has various benefits, including a network with stable connection and sustained bandwidth, no halt, data delivery reliability while traveling, and application in a range of industries, including smart governance, smart health care, and digital calculation. WiFi6 is the sixth version of Wi-Fi, which maintains the network latency at 20ms and also provide the all benefit of fifth generation's tech. like 1024 QAM, OFDMA and MU-MIMO.
PERFORMANCE OF DUAL-BRANCH EGC RECEIVER OVER GENERALIZED-K FADING CHANNELS
Authors: Mudoi Rajkishur
Published: June 2024

The equal gain combining (EGC) receiver performs better as well as the complexity of the EGC receiver is less.In this article, the outage probability and the average bit error rate (ABER) of dual-branch EGC receiver over generalized- fading channel are presented. The ABER expressions are derived for coherent and non-coherent modulation schemes. The channel between the transmitter and the receiver is assumed to experience generalized- fading. The probability density function (PDF) of the output SNR for the dual branch EGC receiver is derived based on the generalized- distribution amplitude PDF. The effect of fading parameters and on the performance of the dual-branch EGC receiver has been observed analytically. Computer simulations are performed to assess the accuracy of the proposed mathematical analysis.
POWER GENERATION THROUGH HUMAN LOCOMOTION USING PIEZOELECTRIC SENSORS
Authors: Manoj Sumitha
Published: June 2024

The primary focus of this essay is on how humans can generate electricity from their movements when they walk and the pressure they apply on the ground. The term "Footstep power generation system" refers to the process by which mechanical energy is converted into electrical energy utilizing transducers and the pressure applied by a footstep. By converting kinetic energy into electrical energy, the power generating floor essentially creates power. The major goal is to end the global power crisis, even though it won't be adequate to meet the excessive demand for electricity. However, it will be able to change and reduce reliance on outdated methods of producing electricity. It can be deployed on footpaths by the side of the road, in parks and jogging trails, as well as many other public locations, such as airports, and will significantly alter the way electrical power is produced. In order to use it later, we can create energy that can be stored in a rechargeable battery, which can also be installed in public areas like streetlights and mobile charging stations.
FOOD QUALITY AND SPOILAGE USING IOT
Authors: Aruna R. , C Kothai Andal. , R Bhavana. , Chandin Ms.
Published: June 2024

The Internet of Things (IoT) is transforming how we interact with the world around us, and its impact on the food industry is no exception. In this project, we present a novel approach to food quality supervision using IoT technology. The project involves using sensors and cloud-based data analytics to monitor various parameters related to food quality, such as temperature, humidity, and spoilage indicators. The data collected from the sensors is then processed in real time using machine learning algorithms, enabling us to detect any anomalies or potential issues with food quality. This approach to food quality supervision has several benefits, including early detection of issues, reduced waste, and improved overall food safety. We demonstrate the effectiveness of our approach through a proof-of-concept implementation, which shows promising results. Overall, our project provides a valuable contribution to the food quality supervision field, highlighting the potential of IoT technology in improving food safety and quality.
DESIGN AND SIMULATION OF REAL-TIME SHORT MESSAGE SERVICE-BASED VOTING SYSTEM
Authors: Elechi P. , Orike S. , Okowa E. , Amangieka A.
Published: June 2024

Voting is an important aspect of the democratic process in which the electorates select those that will represent them at all levels of government as well as in organizations using various technologies. The efficiency, reliability and security of the technologies involved in such a voting system become of paramount importance. In the bid to curb all the anomalies involved in the traditional voting systems, the design and simulation of a real-time Short Message Service-based voting system in Nigeria was developed. This was achieved by first carrying out a comprehensive review of the already existing e-voting systems to ascertain any limitations associated with them. Inefficiency in preventing electoral fraud and keeping the electorate informed of the real-time results of the ongoing election as well as the result immediately after the election is over were the major drawbacks identified with the existing systems. These were attributed to its architectural design and security algorithm making them unreliable. The inclusion of a real-time Short Message Service in the already existing architecture among others is therefore proposed as a solution to the identified drawbacks. The proposed system was implemented using Hypertext Preprocessor (PHP), Hypertext Markup Language (HTML), Structured Query Language (SQL), SMS enabler, Android studio and Apache Web server technologies. The result showed that the SMS features, security, as well as intelligence incorporated in this work, had zero impact on the success rate of the system. There was an increase in the latency of the existing system by 16.8%, though still has a tolerance of 30.5% to reach saturation point while preventing electoral fraud, since the maximum latency for successful vote casting is 60 seconds. This work confirmed that with this proposed e-voting system with a re-engineered architectural model, electoral fraud can be totally eradicated.
INTELLIGENT NETWORKING UNLEASHED: EXPLORING AI AND ML FOR ENHANCED 6G WIRELESS COMMUNICATION SYSTEMS
Authors: R. Deepa Dr. , A. Sivasamy Dr. , S. Selvam Dr.
Published: June 2024

The advent of 6G wireless communication systems presents new opportunities for leveraging artificial intelligence (AI) and machine learning (ML) techniques to enable intelligent networking. This paper explores the application of AI and ML in intelligent networking for 6G, aiming to enhance network performance, optimize resource management, and improve user experience. However, the application of AI and ML in 6G networks also presents significant challenges. The design and implementation of intelligent networking algorithms must address issues such as scalability, real-time decision-making, energy efficiency, privacy, and the need for robust learning in dynamic and heterogeneous network environments. The paper provides a brief understanding of the potential benefits and challenges of integrating AI and ML in 6G networks and provides valuable insights for researchers in shaping the future of intelligent networking for 6G wireless communication systems.
ENERGY HOLE PROBLEM IN WIRELESS SENSOR NETWORKS: A RESEARCH REVIEW
Authors: C Ezhilazhagan , K Lakshmi Prabha
Published: June 2024

Wireless Sensor Networks (WSNs) have emerged as a promising technology for various applications, including environmental monitoring, surveillance, and healthcare. However, the limited energy resources of individual sensor nodes pose a significant challenge in the design and operation of WSNs. One critical issue that affects network lifetime is the energy hole problem, where nodes near the sink node experience faster energy depletion than nodes farther away. This research review aims to provide a comprehensive overview of the energy hole problem in WSNs, highlighting its causes, impact, and existing solutions proposed by the research community. By analyzing and synthesizing the state-of-the-art research, this article intends to shed light on the current understanding and future directions for mitigating the energy hole problem in WSNs.
RELATIONSHIP BETWEEN SOCIAL DESIRABILITY, SOCIAL ANXIETY AND SOCIAL MEDIA USAGE OF SECONDARY AND HIGHER SECONDARY SCHOOL STUDENTS OF PURULIA TOWN
Authors: Sinha Swati , Suchismita Sinha Dr.
Published: June 2024

Background: This study discovers the possibility of an association between social media usage using social anxiety and social desirability in students of Purulia town. Social media usage is a distinctly visible trend nowadays especially in teenagers. The unmanageable urge to use social media and impairment of other life domains results in its addiction and a disruption of normal life. Social desirability is the tendency to act in socially sanctioned ways. Social anxiety is being fearful/apprehensive about being criticised by others. So, when social anxiety and social desirability is higher, there is a tendency for the student to have high social media usage as his/her tendency to conform to societal trends will be high as well. Objective: This study investigates the relationship between social desirability, social anxiety and social media usage of a sample consisting of secondary and higher secondary school students of Purulia town. Methodology: The study has been conducted on 130 secondary and higher secondary students studying in Purulia town which included 81 males and 49 females. All the students were administered a social media addiction scale, social anxiety scale and social desirability scale. Statistical techniques like t-test and correlation were used to find out the mean differences and association between the variables. Result: This study finds no significant difference between social media usage, social anxiety and social desirability of secondary and higher secondary school students of Purulia town but it does find a significant positive correlation of social media usage with social anxiety, social desirability and age of secondary and higher secondary school students of Purulia town. The study also found a significant positive relationship between social anxiety and social desirability of secondary and higher secondary school students of Purulia town.
THE EFFECT OF DURATION OF TIME SPENT ON PLAYING VIDEO GAMES ON COGNITIVE ABILITIES AND IMPULSIVITY AMONG ADOLESCENTS
Authors: Ghosh Ankita , Anwesha Chakrabarti Dr.
Published: June 2024

Background: People had to isolate themselves due to the abrupt COVID-19 outbreak, which caused worry and anxiety. As a result, people turned to video games for enjoyment as a way to reduce stress. Prior research emphasized the detrimental consequences of video games on teen behaviours. But recently study has focused on the possibility that video games can improve neurocognitive abilities. The purpose of the study is to evaluate the effect of duration of time spent on playing video games on cognitive abilities, and impulsivity among adolescents. Methodology: Data was collected form 101 participants belonging to age group 15-18 years; those who play games for 2 hours and for 30 minutes. Non-probability convenient sampling was used. Cognitive abilities were assessed using Mackworth clock test, Corsi block Tapping Test and Tower of Hanoi test while impulsivity was assessed using Barratt impulsiveness scale-short form. Data was entered and analysed in SPSS version 20. Result: There were 50 gamers (49.50%) who play games for 2 hours and 51 gamers (50.50%) those who play games for 30 minutes. Result suggests that there is a significant difference in motor impulsivity, non-planning impulsivity, attentional impulsivity, correct responses, false alarm, mean reaction time, number of correct trials, memory span, total score, shortest and steps but no significant difference was found between time/steps. Findings also reveal that those who play games for longer period of time has scored high in impulsivity than those who play for limited amount of time. Conclusion: Gamers exhibit a wider range of cognitive abilities, particularly in the areas of vigilance, visual-spatial working memory, and problem-solving. In this study, people who played video games for two hours had higher impulsivity and better cognitive ability than those who played for only a brief time. It indicates that playing video games enhances cognitive abilities but playing them for a long-time foster impulsivity.
ANXIETY AND DEPRESSION AMONG UNMARRIED WOMEN (YOUNG ADULTS) WITH PCOS AND THOSE WITHOUT PCOS
Authors: Sarkar Shreya
Published: June 2024

Polycystic ovarian syndrome, abbreviated as PCOS, is the most prevalent disorder among women, affecting approximately 5 to 10% of women in the Western world (Franks 1995). In India, the Indian Fertility Society has reported a prevalence rate ranging from 3.7% to 22.5% for PCOS. PCOS is a genetic condition characterized by various phenotypes and appearances. Women afflicted by this condition experience hormonal imbalances leading to issues such as infertility, obesity, and excessive facial hair growth. Furthermore, it can result in significant mental health challenges, including anxiety, depression, eating disorders, and social isolation. Among the complications associated with PCOS, acne, obesity, hirsutism, infertility, and menstrual irregularities have the most detrimental impact on women's lives. Mental health issues are more commonly observed in younger women who suffer from PCOS.
EMBRACING THE DIGITAL ERA: TRANSFORMING CORPORATE GOVERNANCE
Authors: Vuppuluri Ramakrishna , Pandey Abhishek
Published: June 2024

The digital transformation of corporate governance, driven by technologies like blockchain and AI, has significant implications for business models, organizational structures, and regulatory frameworks. Blockchain technology and smart contracts offer the potential for enhancing shareholder engagement, proxy voting, and reducing insider trading. However, challenges like cyber threats, data breaches, regulatory compliance, and environmental sustainability must be considered. The article highlights the need for thoughtful digital implementation to maximize benefits while addressing risks.
EMPOWERING EDUCATION IN THE DIGITAL AGE: MANAGING THE TEACHING AND LEARNING PROCESS
Authors: Arpana Tripathi Dr. , Gorai Jitendranath
Published: June 2024

The dynamic environment of education in the digital age is examined in this paper, which focuses on methods for empowering both students and teachers. The present research explores how teaching and learning might help students enhance their creativity, critical thinking, and problem-solving abilities by moving away from rote memorization and toward holistic learning. By investigating the fusion of technology, pedagogy, and learning processes, this study aims to navigate the evolving educational paradigm while ensuring meaningful and effective teaching and learning experiences. And connecting with navigating the teaching and learning process, presenting a comprehensive overview of key strategies that educators can employ to create meaningful and engaging learning experiences. By exploring the realms of learning theories, clear learning objectives, engaging content, classroom management, active learning, assessment and feedback, technology integration, culturally responsive teaching, lifelong learning skills, and reflection, this paper aims to provide educators with a holistic framework to enhance their teaching practices. NEP 2020, an ingenious policy framework to intensify the education sector and as a catalyst for amalgamation of technology in learning and teaching process. In conclusion the study provides perceptivity into the evolving landscape of education with the importance of harmonious blend of pedagogy with technology to foster the teaching learning process. In this paper author discuss various teaching-learning platform which is use in Indian and global perspectives.
EXTENSION OF PSYCHOLOGICAL MEMORY MODEL OF HUMANS TO INCLUDE CONCEPT OF CHIDAKASHA
Authors: Mathur Gaurav
Published: June 2024

The human mind is a complex part of the body that scientists and psychologists are still trying to understand. The Atkinson-Shiffrin model of human memory is a well-known approach to decoding memory, but it has been refined over time. However, when we consider the concept of chidakasha and the karma theory in Sant Mat and Hinduism, we see that scientists tend to focus only on the physical body and neglect the subtle and causal bodies, which continue to exist even after death and may explain the persistence of memory from past lives. There is a similarity to the modern concept of Cloud storage. This study aims to expand the Atkinson- Shiffrin model to include the effects stored in the chidakasha, which guide our actions in our present lives.
A COMPARATIVE STUDY OF ANXIETY AND SELF-CONFIDENCE BETWEEN UNDER-GRADUATE AND POST-GRADUATE PHYSICAL EDUCATION STUDENTS
Authors: Lamlun Buhril Dr. , Paukhankhup Mr.
Published: June 2024

The purpose of the study was to measure and compare the level of anxiety and self-confidence between under-graduate and post-graduate students of physical education. A total of 200 subjects were selected consisting of 100 subjects from under-graduate physical education students and 100 subjects from post-graduate physical education students across different universities and colleges in India. Anxiety and self-confidence were selected as the variables and Competitive State Anxiety Inventory-2 (CSAI-2) developed by Martens, Vealey, and Bruton (1990) was used as the tool for collecting the data. The inventory consists of Cognitive state anxiety, Somatic state anxiety and self-confidence comprising 27 questions. Descriptive statistics and independent ‘t’ test were applied to analyse and compare the degree of anxiety and self-confidence between under-graduate and post-graduate physical education students. The level of significance was set at 0.05. Results indicated that the calculate ‘t’ value 2.13> 1.96 at alpha 0.05. So, there was significant difference on cognitive state anxiety between under-graduate and post-graduate physical education students. While, there were no significant difference on somatic state anxiety and self-confidence between under-graduate and post-graduate physical education students as the calculated ‘t’ value 0.707<1.96 and calculated ‘t’ value 1.91<1.96 at alpha 0.05 respectively.
A STUDY OF INDIAN GOVERNMENT POLICIES AND PLANNING IN IMPLEMENTING IN-SERVICE TEACHER TRAINING PROGRAMS
Authors: Alka Mr. , Rinkal Sharma Dr.
Published: June 2024

The Pre-Service and In-Service Teacher Education curricula and laws, that interact with present-day teachers as well as future teachers of society, have undergone an important change over the past few years. To attain quality, programs, and policies have been developed. Nowadays teacher education programs need to be examined, revised, reconsidered, and refocused as a result of society's shifts and increased attention to learning as a fundamental human right. Reforms have been made to better the process of training teachers. Everyone who believes in discusses excellent instruction, but it is impossible without instructors who have received the necessary training. Therefore, the development and growth of teacher preparation programs are crucial. In India, training teachers have long been seen as one of the most important strategies for advancing society and the country. The Indian government occasionally established a number of committees and commissions to deal with various teacher education-related concerns and to address the growing issue of the teacher education program's accessibility, quality, and applicability. The Kothari Commission Report (1964–1966), Acharya Rammurti Samiti Report (1990), NCTE regulations 2009, NCTEF (2010), NCF (2005), the National Knowledge Commission Report, Right to Education Act 2009, SSA, Samaghra Shiksha, NEP 2020, etc. are just a few of the policy papers and documents that have been considered in India throughout the process of searching for reform and reorganization. This article elaborates its objectives on the discussion of how our govt. has gradually made changes in the direction of making progressive education and also in the advancement and development of teacher education, specifically In-Service Teachers which this discussion focuses on.
UP APPROACH TO EXTENSION –FARMERSINTEREST GROUP (FIG)
Authors: S Sahana , M. H Shankara
Published: June 2024

Due to demographic pressure and the diversion of land to non-farm uses, the average holding size in India is declining very fast, making many farm households dependent on economically unviable agriculture. Small and marginal farmers constitute about 86.00 per cent of farming households in the country (Agricultural Census Report, 2015-16). It has made proper and timely delivery of inputs and technical services very difficult. Moreover, these are supply driven with little care for demands from the field. Due to inadequate research-extension-farmers linkages, there has been low adoption of innovations and improved technologies in the farmers' area. In India, most farmers have only small marketable surpluses; therefore, they have to sell their produce in the local markets at low prices immediately after harvest. The costs of procurement/purchase of inputs and availing of technical services are high for small and marginal farmers. Thus, a strategy was needed to increase their bargaining power in purchasing inputs and selling produce. This was the basic idea behind organizing cooperative marketing societies in the country. Still, their success is limited to only a few cases (Acharya and Agarwal, 2004). Under these circumstances, there is a need to organize the farmers to avail the benefits of better technology for agricultural production. On the other hand, the market for farm products is highly competitive, which limits the farmers as price takers. In this regard, the group approach can act as a panacea for improvement in the production and marketing of agricultural produce.
DIGITAL HERITAGE OF ASIAN BUDDHIST CAVES USING CULTURAL COMPUTING AND AI: SPECIAL REFERENCE TO AJANTA CAVES
Authors: Tribhuvan Amrapali Prakash
Published: June 2024

Digital heritage refers to the collection of cultural, historical, and artistic resources that are preserved in digital form. It encompasses a wide range of materials such as images, videos, audio recordings, documents, and even virtual reality experiences. The digitization of heritage objects allows for wider accessibility and enables people from all around the world to explore and engage with these artifacts without physically visiting museums or archives. Cultural Computing is emerging field for translation of culture. It uses scientific methods to represent essential aspects of culture. It includes computation of emotion, story, and culture. It is more than integrating cultural aspects into the interaction. Artificial Intelligence is another useful tool for preventing cultural heritage. Ajanta caves are universally regarded as masterpieces of Buddhist religious art. In this proposed research work author is trying to help to preserve, use and experience Ajanta Caves vast heritage in digital form. In this paper author presented the 3D reconstructed model of Cave 1 and restoration of damaged image of Bodhisattva Padmapani from cave 1 at Ajanta monastery.
ROBUST FEATURE BASED CANCER CLASSIFICATION
Authors: Banerjee Indranil , Mandal Dr. Bijoy Kumar
Published: June 2024

Brain cancer has a very short life expectancy. Accurately diagnosing brain cancer is an important step in developing an appropriate treatment plan for brain cancer treatment and rehabilitation. Computer-based cancer detection systems and convolutional neural networks have created success stories and machine learning-based disease detection has made significant progress. The present work fills this gap. Here, we used a statistics-based feature-extraction method and machine learning-based extraction method to distinguish cancer genes from non-cancer genes. Deep learning algorithms have also been used to develop automated cancer cell prediction systems. Unlike available methods, three function output modules were developed. The focus of this paper is to identify genetic hallmarks of cancer. In this proposed work, convolutional neural networks are established to predict cancer cells. Histopathological images are initially splitted into train, validation and test data in the ratio 75:15:10. Next, we ran all training on TensorFlow using Python's Keras library. The developed method proved its effectiveness on the derived function by achieving 99% accuracy. The CNN model was compared with existing work and achieved 99% accuracy. The process of binary classification as bad or good is relatively short. Here, we present an automatic binary classification method using deep learning for brain cancer classification. A deep neural network model is developed and applied as a feature extractor to learn the histopathological images and their convolutional layer structures on the histopathological image dataset. Then, the fully connected layers are replaced and the entire deep network is trained as a classifier to distinguish the two cancer classes. Our proposed model has about 4.2 million training parameters, which is less than VGG19, ResNet50 and InceptionV3, which have 20.1 million, 23.9 million and 21.8 million, respectively.
A SURVEY ON MACHINE AND DEEP LEARNING FOR FINGER KNUCKLE PRINT AUTHENTICATION
Authors: Lakshmanan Sathiya , Velliyan Palanisamy , Attia Abdelouahab
Published: June 2024

Beneficially, biometric personal authentication is very important for the research community due to its broad applicability to several security applications. In terms of precision and computational complexity, manual biometric frameworks are considered to be more fruitful. In hand-based biometrics, finger knuckle prints are one of the biometric surface features that can be used to ensure personal authentication. The result is the fact that the external surface of the finger back knuckle region shows fluctuating and exclusive patterns. The existing analysis of FKP authentication system such as Geometrical, statistical, transform and texture-based methods are usually a time-consuming and difficult task. With advanced machine learning techniques and profound learning concepts, it can be made easy and fast and can be very useful for society. So, the essential place of this paper is to consider a survey of the different machine learning and deep learning-based Finger Knuckle Print verification system. This survey will assist aspiring researchers in the area of finger knuckle print authentication systems.
A TECHNIQUE FOR DETERMINING THE RISK OF ACQUIRING CARCINOMA OF THE LUNGS
Authors: Rahman Ms. MH. Vahitha , Vanitha Dr. M.
Published: June 2024

Medical imaging takes photos of a patient's body or illness for diagnosis and research. Diagnostic radiography describes medical imaging techniques, and the radiographer must take high-quality images to diagnose diseases. Medical imaging may fall under biomedical engineering, medical physics, or medicine, depending on the scenario. Therefore, many medical imaging approaches enhance other disciplines of research and industry. Medical imaging has become a prominent scientific imaging subject due to advances in computerised medical image reconstruction, analytic methods, and computer-aided diagnostic systems. Computed tomography imaging has advanced, helping radiologists diagnose a broad variety of illnesses by examining images in detail. A CT scan is an X-ray imaging technology used to study a patient's anatomy and physiology. The CT image is rebuilt using the X-ray absorption profile. CT scans are often used to assess and diagnose the brain, liver, chest, abdomen, pelvis, spine, and CT-based angiography. Lung cancer is caused by cell growth in lung tissues. Untreated, this cancer may metastasize and infect nearby tissue or organs. Lung cancer is one of the most common. Cigarette smoking causes most lung cancers. Screening and early detection may boost lung cancer survival. Competent lung cancer detection systems can identify tumours accurately. CT scan images are usually used to diagnose "Enhancement," "Segmentation," and "Feature extraction" comprise computer-aided lung cancer diagnosis. These stages may be done in many ways. Pre-processing, segmenting, feature extraction, and classification are involved. This research reveals a way to accurately identify lung cancer cells in CT images.
ANALYSIS ON VIDEO STABILIZATION TECHNIQUES – A SURVEY
Authors: Mehala R. , Mahesh Dr. K.
Published: June 2024

Video stabilization is an important component of a visual quality improvement. It restores feature extraction and tracking in unstable videos. Video stabilization is to enhance the quality of consumer-level recordings, such as running, cycling, or driving. Video stabilization contains basic steps viz., Motion Estimation, Outlier Removal, Camera Motion Modeling, Camera Motion Correction, and Video Synthesis. A significant number of machine learning approaches are used to support computer vision techniques for stabilizing videos. Several computer vision difficulties, including super resolution, picture deblurring, style transfer, classification and recognition, among others have been successfully addressed using deep learning techniques. In recent years efficient 3D video stabilization currently demands the use of new deep learning techniques. Provide an analysis of video stabilization techniques in this work.
APPLICATION OF THE DIVIDE AND CONQUER AND SIMPLE ADDITIVE WEIGHTING TO DETERMINE THE BEST EMPLOYEE
Authors: Wahyuni Sri , Zulham Mr.
Published: June 2024

The research proposes the application of the divide and conquer algorithm to select the best employees at Dharmawangsa University based on the value points each employee gets based on several assessment criteria. Each employee is assessed based on responsibility, discipline, cleanliness, initiative, cooperation, and skill. In ranking employees, the simple additive weighted (SAW) method is used. The basic method of SAW is to make a sum as a consideration of the performance rating of each alternative on all attributes. It is necessary to normalize the decision matrix (X) in the SAW method into a scale that can later be compared with all existing alternative ratings. The selection of the best employees is one of the Simple Additive Weighting method implementations. The purpose of this research is to determine the choice of the best employees at Dharmawangsa University. by doing this research what you want to achieve is to create a system that can assist in making optimal decisions.
PYTHON-BASED IMAGE CAPTIONING USING CNN AND LSTM
Authors: Suneetha Dr. A. , Babu Dr. K. Ratna
Published: June 2024

Our most important sense is vision. The capacity to see has been used by software engineers to create more dynamic, intelligent, and easily accessible software through visuals. There are circumstances, nevertheless, in which an image might not be enough. Alternative text may be provided to avoid bandwidth limits and offer a more accessible experience if further context is required. The manual explanation falls short in an age where there is simply a great deal of photographs to describe. Deep learning can integrate image processing and natural language processing, allowing computers to independently provide explanations for images. This service can be provided through a user-friendly web interface, where customers can simply upload the photos, they want to be described. This makes it possible for anybody to easily take advantage of the capabilities of this deep learning technique and adaptive image descriptor capability through a simple API, with the computationally demanding chores being abstracted away.
MACHINE LEARNING FOR BRAIN TUMOR IDENTIFICATION: PROGRESS AND BOTTLENECKS
Authors: Kumar Mr. D. Anil , Kumar Mr. A. Sandeep , Niveditha Mrs. K. , Veesam Mr. Venkata Srinivasu
Published: June 2024

The integration of Artificial Intelligence (AI) in the field of medical imaging has shown promising potential for revolutionizing the detection and diagnosis of brain tumors. Recent years have witnessed significant strides in the application of AI algorithms, particularly convolutional neural networks (CNNs), for the auto-mated analysis of neuroimaging data. These algorithms demonstrate remarkable proficiency in recognizing subtle anomalies within MRI, CT, and PET scans, enabling earlier and more accurate identification of brain tumors. Furthermore, AI-powered systems can classify tumors into distinct categories, aiding clinicians in treatment planning and prognosis assessment. This paper explores the advancements and challenges of AI-driven approaches to the detection and classification of brain tumors. The study investigates advanced AI methods, such as deep learning, and shows how effective they are when compared to traditional methods. The potential impact of AI on neuro-oncology is underlined, along with the ethical and governmental repercussions of its use in therapeutic settings.
BIOINFORMATICS:PROTEIN BIOLOGY CONCEPTS ON ITS STABILITY AND APPLICATIONS
Authors: Sugil A.Jasmine , Merriliance Dr. K.
Published: June 2024

This chapter focuses on the interdisciplinary area, bioinformatics. It introduces the field of bioinformatics as well as adescription of bioinformatics methodologies, its implications in protein stability and how they are used in the study of proteins. For any living thing to operate properly, proteins and amino acids are a crucial biomolecule. Experimental study on protein stability prediction is cumbersome and in accurate. Hence drug design for protein-based diseases has look tedious. In this context, Bio informatics is playing a critical role in predicting the thermodynamics stability of proteins upon point mutations viz., single, and multi-point mutations. In the previous year,various computational techniques are presented by many researchers to aid stability prediction of protein. The bioinformatics analysis includes aspects of DNA, RNA, and protein sequence analysis, gene and protein expression, genetics of diseases including neuro and special phenotypes, analysis of gene regulation, chemical interaction regulation, enzymatic regulation, other types of regulation, analysis of flowing signals in cells, networks of genetic, protein, and other molecular interactions, and comparable analysis of the diversity of genomes between individuals or organisms. Technology is essential for management of these kind of data in modern digital world. Bioinformatics is a computational and analysis tool to capture and interpret biological data like protein sequencing, molecular structure, DNA sequences, etc. Estimate of protein stability is vital and challenges to bioinformatics engineers.
IDENTIFICATION OF MENINGIOMA TUMOR USING RECURRENT NEURAL NETWORKS
Authors: Chandra Dr. G. Rajesh , Kumar Rejeti Dr. Venkata Kishore , Mohan Dr. K. Jagan , Krishna Hari
Published: June 2024

From Covid 19 Pandemic, Number of Meningioma Tumor patients are Increasing in world. Identifying the Meningioma Tumor and its position in brain is not easy task by using Deep Neural Networking based medical imaging. But it is needed to identify meningioma tumors in brain by using AI based medical imaging for the purpose of Medical Artificial intelligence technology innovation. Comparing to neural network results with recurrent neural network results can give accurate results. For identifying the patients’ present condition and prediction of future behavior by using recurrent neural network is need for us. Increase the accurate results for Neural networking based medical imaging in health care is very expensive. By using Recurrent Neural Networks (RNN) Algorithm with many hidden layers for identification of tumor(s) in human brain with high accuracy by comparison of existing images in our data base with new unknown medical image with low cost. In this study first we are collecting the masks of skull from MRI Image and dividing the masks to different types of datasets depending on age criteria like a child age ,middle age and old age with two types male and female. Then we can get totally 6 types of datasets. All these masks of mri images to binary imaging by using morphological erosion concept after that storing that masks in data sets then collect the new MRI Image and comparingits mask part of skull with existing dataset in Recurrent Neural Networks.
AN EFFICIENT FEATURE REPRESENTATION USING CHLOMO AND CNN FOR PERSON RE-IDENTIFICATION
Authors: Janci Rani Dr. J Stella , Augasta Dr. M Gethsiyal , Bai Dr. S Princy Suganthi
Published: June 2024

The re-identification of a person is defined as determining whether a person has previously been in front of a network of cameras. Efficient features always make perfect learning towards individual re-identification. In this research, a new deep feature learning model called CHLFDLF has been proposed with the mixture of handcrafted features and profound features, extracted using CHannel Integrated LOMO (CHLOMO) and Convolutional Neural Network (CNN) respectively to attain an improved person re-identification system. The extracted features are integrated efficiently and learned using the Cross-view Quadratic Discriminant Analysis (XQDA) similarity metric approach for efficient person re- identification. The performance of this proposed approach is demonstrated by applying it to the different benchmark datasets for re-identification such as VIPeR, CUHK03, and Market1501