bluuebunny/crossref_metadata_2025 huggingface dataset:
TOMATO PROCESSING AND PREPARATION OF TOMATO POWDER
Authors: Sahu Chandrahas , Sandey K. K , Sahu Rahul Kumar , Sahu R. K
Published: June 2024

Tomato is a highly perishable vegetable crop and seasonally grown. It contain high amount of lycopene. Due to perishable nature, the matured tomatoes are damaged rapidly and difficult to safe transporting. To preventing these types of losses, its processing and value addition is most important. In this contest, development of different value added products from tomato pulp and dried tomato powder had been considered in this study. Drying of tomato powder is most difficult due to its high hygroscopic nature. Freshly ripened tomato contains about 94% of moisture and also rich source of minerals and vitamins like vitamin A and C. Drying and dehydration reduces moisture content in the tomato products, which increases the shelf-life of the products by retarding the bacterial propagation. There are different method of drying of tomato pulp such as conductive drying, drum drying, agitated thin film drying, refractance window drying, sun drying, tunnel drying, spray drying and foam mat drying. Spray drying technique is most suitable for the preparation of tomato powder but it is costlier. In view of reduced production cost foam mat drying technique is most suitable for tomato powder.
APPLICATION OF LIGHTS IN FOOD SAFETY
Authors: Kaukab Shaghaf , Mishra Alka , Sunita Devi Thongam , Bidyalakshmi Devi Th. , Pahariya Prachi
Published: June 2024

Nowadays consumers’ demand for safe, more natural and healthier food is increasing. Food safety considerations include preventing spoilage, bacterial development, and contamination. Thermal and non-thermal technologies are used for keeping food safe from pathogenic and spoilage microorganisms. Non-thermal food processing methods using light technology have been intensively studied for food decontamination. The lights of different wavelengths in UV or visible range have some antimicrobial effect and been used for surface decontamination of food. In addition, pulsed light technology is an alternative to thermal and chemical disinfection methods and used to decontaminate food and contact surfaces using high intensity pulses. Food sterilizing using UV light is referred to as irradiation, though it does not add radiation to the food or render it radioactive in any manner. Shortwave ultraviolet light (UV-C) is widely utilized in the food industry since it offers technological advantages such as low maintenance, low energy use, no undesirable effects without requirement of chemicals or pesticides. UV-C is considered as most effective method for microbial inactivation. Visible light also have emerged as new food decontamination technology as it kills surface microbes through the process of photodynamic inactivation. Pulsed light (PL) has recently gained popularity as a disinfection and preservation alternative to traditional approaches. These light technologies can be considered as eco-friendly, clean technology, chemical free, non-thermal and does not have any residual effect on food. This chapter aims to give an overview of light technology principles, applications for microbial inactivation in various food products and food contact surfaces.
UNLOCKING THE PATH FORWARD: NAVIGATING CHALLENGES & EMBRACING OPPORTUNITIES IN EXPLAINABLE ARTIFICIAL INTELLIGENCE (XAI)
Authors: Maan Mr. Jitendra
Published: June 2024

With the continuous digitization and proliferation of digital technologies and platforms, we are embarking on a new age of Artificial Intelligence applications considering machine learning and deep learning as the core technologies. AI systems leveraging machine learning models, have a profound impact on how Business and IT leaders make real-time critical decisions without enough context on how these complex systems arrive to a particular outcome. Essentially, they simply reply on black-box technology which erode their trust on AI systems due to lack of transparency, fairness and the ability to explain the outcome of machine learning models. Our study focuses on the importance of ML Models and underlying algorithms assessment in terms of the explanations they produce, their constraints, and real-world uses. Through a meticulous analysis of their advantages and limitations, the objective of this paper is to highlight how XAI techniques can potentially reconcile the divergence between the accuracy of machine learning models and the dire need for comprehensible interpretations. This paper specifically talks about the current XAI challenges and future opportunity to design AI Systems which are ethical in the purpose emphasizing the desire for transparency, fairness and interpretability.
ARTIFICIAL INTELLIGENCE – ITS EVOLUTION, FUTURE, AND GROWING IMPORTANCE IN DIFFERENT FIELDS
Authors: Saini Mr. Ashwini , Gupta Mr. Abhishek , Joshi Akanksha , Mahajan Ankit
Published: June 2024

Artificial Intelligence is an umbrella term consisting of Machine Learning, Deep Learning, Computer Vision, Robotics, etc under it. It is being used in various sectors such as Healthcare, Agriculture, and Industries. From being just a concept regarding emulation of the Human Brain, Now Artificial Intelligence has become the present and upcoming future of the world. Faster Diagnosis, Automation of Vehicles, Industries, and Development of Robots are some of its applications. This paper gives a detailed review of the evolution of the concept of Artificial Intelligence, its various domains, applications, and advancements in different fields, and its boom in the future. The future of Artificial Intelligence is hopeful as applying it to all aspects of life can improve its overall quality.
AI AND SUSTAINABLE FINANCE
Authors: Vinothkumar Dr. B. , Lawrance Dr. R.
Published: June 2024

Artificial Intelligence (AI) is emerging as a powerful tool for promoting sustainable finance, which aims to integrate environmental, social, and governance (ESG) considerations into investment decisions. This paper provides an overview of the ways in which AI can contribute to sustainable finance. It can help financial institutions and investors to analyze and interpret ESG data more efficiently and accurately. This can enable better decision-making and risk management, leading to more sustainable investments. Machine learning algorithms can help identify patterns and relationships in large and complex datasets, making it easier to assess the ESG risks and opportunities associated with different investments. It helps financial institutions to manage ESG-related risks in their portfolios. By analyzing ESG data, AI can identify potential risks associated with climate change, social issues, and governance practices, allowing investors to take preventative measures and avoid losses. It enables more effective impact assessment of investments by measuring and analyzing the environmental, social, and economic outcomes of different investments.
SOCIAL MEDIA EXPLOITATION OF CHILDREN: CAUSES AND PREVENTION
Authors: Shaji Anshu , Nagle Y K
Published: June 2024

Social media's transformation of communication and identity in the digital age has had both positive and negative implications. This paper explores the dynamics of social media use across age groups, highlighting its significance and associated risks. It looks into the evolving landscape of social media, portraying its evolution from a basic information exchange tool to a powerful marketing platform. The term "social media" encompasses a diverse range of websites and platforms, including Outlook and Hotmail in its early days, and has evolved into more user-friendly forms with features like chat boxes, Pinterest, and dominant search engines like Google. Today it serves as a multifaceted tool for business and education while posing mental health challenges, especially for younger generations who are heavily reliant on it for cognitive development. As the saying goes, "There are two sides to a coin," and this applies to social media as well, which has both positive and negative aspects.
EMBRACING LIFE WITH POSITIVE PSYCHOLOGICAL APPROACHES
Authors: Wakeel Abbasi Samiya , Yadav Vishal
Published: June 2024

It is incredible that happiness, joy, and those sunshine smile quotes are not merely limited to books and movies but are a scientifically proven way of life. A positive approach can heal situations, conversations, physical and mental conditions, and healthy insinuations. Unlike traditional psychology concepts that work on mental illnesses and ways to deal with them, positive psychology has broadened its horizon and spread its wings to encompass enhancing the way of life. They improve the well-being and performance of individuals and their daily practice can upskill their attitude towards their day-to-day life. Positive Psychology was adopted in the late 1950s. Positive Psychology revolves around the significant umbrella concepts of happiness, overall well-being, and quality of life.
DIGITAL METAMORPHOSIS: UNRAVELING THE EFFECTS OF DIGITAL TRANSFORMATION ON SOCIAL INTERACTION
Authors: Shikha Tiwari Dr.
Published: June 2024

The rapid advancement of digital technologies has brought about a transformative shift in various aspects of modern society. One of the most significant areas impacted is social interaction, as traditional modes of communication and interpersonal relationships have been redefined by the digital age. This research article delves into the multifaceted effects of digital transformation on social interaction, exploring both its positive and negative consequences. By examining changes in communication patterns, the evolution of online communities, alterations in self-presentation, and the implications for mental well-being, this article provides a comprehensive analysis of the intricate relationship between digital transformation and social dynamics. It aims to deepen our understanding of the ongoing digital metamorphosis and its profound implications for the fabric of human interaction.
COMPARING ACADEMIC STRESS LEVELS AMONG STUDENTS IN LIBERAL ARTS, ARCHITECTURE, AND ENGINEERING PROGRAMS AT P.P. SAVANI UNIVERSITY: A QUANTITATIVE ANALYSIS
Authors: Pallavi Patwari Ms.
Published: June 2024

Academic stress has become a prevalent issue among students, resulting from the numerous expectations placed upon them both internally and externally. Adolescents, in particular, are susceptible to the challenges associated with academic stress during their transitional phase. Therefore, it is crucial to comprehend the sources and impact of academic stress to develop effective intervention strategies. The study is being conducted to check the appraisal in students of liberal arts, engineering and architecture of their academic stress. The study employed a quantitative research design where participants were screened using Academic Stress Scale (Rajendran & Kaliappan,1991 from three streams namely, Liberal Arts, engineering and architecture. The result obtained demonstrated that the highest levels of stress was observed in students of liberal arts, followed by Architecture and then engineering. Understanding the sources of stress would facilitate the development of effective counselling modules and intervention strategies by psychologists and counsellors in order to help students decrease their stress.
BEYOND PLAYMATES: THE MULTIFACETED IMPACT OF PETS ON CHILDREN'S GROWTH AND ADULT’S WELLNESS
Authors: Surana Pranja
Published: June 2024

The paper examines the role of pets in fostering the development and well-being of individuals, both children and adults. Specifically, it delves into the positive effects of pets on diverse aspects of life, such as responsibility, empathy, emotional growth, social skills, intellectual capacities, physical health, stress reduction, and learning experiences. Moreover, it underscores the significance of comprehending and implementing pets' advantages in the Indian context to promote happier and healthier individuals. Animal-assisted therapy, an intervention incorporating animals into the therapeutic process, is also discussed as a valuable tool for individuals of all ages who encounter physical, medical, or mental challenges. The paper highlights the role of different types of therapy animals, such as dogs, in enhancing treatments and fostering well-being.
SYNERGIZING VOCATIONALIZATION IN SCHOOL EDUCATION: TRANSFORMING EDUCATION AND EMPOWERING INDIVIDUALS
Authors: Anshu Kumari Dr.
Published: June 2024

The paper tries to explore the vocational space of the Indian education system and its trajectory from the Kothari Commission to the National Education Policy 2020. The paper provides a glimpse of the national credit framework as well as the previous qualification frameworks that are widely used in India. The paper focused on the demographic dividend of India as one of the youngest nations and its needs to became world skill capital. The National Curriculum Framework for School Education is also addressed in reference to vocationalization. The challenges of vocational education are also mentioned, with hopes of getting a way out in the near future.
ARTIFICIAL INTELLIGENCE BASED MEDICAL SENSORS FOR HEALTH CARE
Authors: N. Kavitha Ms. , P. Moniya Dr. , P. Palaniyammal Ms. , P. Shakthipriya Ms.
Published: June 2024

The traditional medical order has been disrupted by the older age populace and the presence of communicable disorders, greatly raising the strain on health maintenance as well as unfavorably disturbing the conservative system. Artificial intelligence (AI)-based medical sensors offer novel perspectives on how to gather information for modern medicine to track changes in the environment and people's health. The position of AI-equipped health detecting sensors for off-body illness, adjoining-body observing, sickness forecast, and medical verdict sustain systems is briefly reviewed in this paper, along with the ongoing difficulties and possible solutions for moving from concept to implementation. Development in the integration of clinical sensors as well as AI coding are anticipated to open the door to near the beginning recognition and medical verdict sustain as well as increase the accuracy and effectiveness of medical diagnosis in the very near future.
UNDERWATER COMMUNICATION SYSTEM BY USING IR
Authors: Kumar Reddy B Siva , Maadhav D. , Meghana N. , Sangeetha M. , Raj J. Abhishay
Published: June 2024

Underwater communication systems play a vital role invarious fields, including marine exploration, offshore industries, defence operations, and environmental monitoring. The unique characteristics of the underwater environment, such as high attenuation, multipath propagation, and limited available bandwidth, present significant challenges in establishing reliable and efficient communication links. This abstract provides an overview of underwater communication systems, focusing on advancements, key technologies, and the challenges associated with achieving robust and high-performance underwater communication. The study begins by highlighting the importance of underwater communication systems and their applications in different domains. It emphasizes the need for effective communication methods to enable real-time data transmission, remote control, and collaborative operations in underwater environments. Next, the paper discusses the technological advancements that have shaped underwater communication systems. It covers traditional methods such as acoustic communication, which utilizes sound waves to transmit information over long distances. It also highlights recent developments in optical communication, which leverages light to achieve higher data rates and shorter-range communications. Additionally, it explores hybrid approaches that combine acoustic and optical techniques to address the limitations of each method. The study then addresses the challenges associated with underwater communication systems. It discusses the impact of factors such as signal attenuation, multipath propagation, and ambient noise, which degrade signal quality and limit transmission distances. It also highlights the issue of limited available bandwidth, which requires efficient modulation and coding techniques to maximize data throughput. Moreover, the abstract addresses the impact of physical obstacles, such as underwater topography and vegetation, on signal propagation and reception. Furthermore, the work explores ongoing research and developments aimed at addressing these challenges. It discusses advancements in signal processing algorithms, channel modelling techniques, and adaptive communication protocols to improve the reliability and performance of underwater communication systems. It also highlights the importance of energy-efficient designs and power management strategies to extend the operational lifetime of underwater communication devices. In conclusion, this paper provides a comprehensive overview of underwater communication systems, emphasizing their importance, technological advancements, and challenges. It serves as a foundation for further research and development in this field, fostering the design of robust and efficient communication systems capable of withstanding the unique demands of the underwater environment.
AI-DRIVEN ADVANCEMENTS IN ROBOTICS
Authors: Shanmugavel Thirumalai Rajan , Devarajan Sujatha
Published: June 2024

Artificial Intelligence (AI) has emerged as a transformative force in the field of robotics, revolutionizing the capabilities of robotic systems across various industries. This abstract explores the profound impact of AI-driven advancements in robotics, unveiling the symbiotic relationship between AI and robotics and their potential to shape a futuristic landscape of automation and intelligent machines. The convergence of AI and robotics has unlocked unprecedented possibilities in automation, efficiency, and adaptability. Machine learning algorithms and deep neural networks have empowered robots to acquire new skills, adapt to dynamic environments, and make informed decisions, mirroring human-like cognitive abilities. From autonomous vehicles navigating complex terrains to industrial robots optimizing production processes, AI has elevated robotics to new heights, transcending traditional limitations. While AI-driven robotics brings forth remarkable advancements, it also raises ethical and societal considerations. The abstract sheds light on the importance of responsible AI deployment, addressing concerns of human displacement and potential biases in decision-making algorithms. AI-Driven Advancements in Robotics signify a groundbreaking transformation in technology, propelling society towards a more automated and intelligent future. However, fostering responsible AI implementation and embracing the cooperative potential of human-robot collaboration are crucial for realizing the true benefits of this symbiotic relationship. As we venture into uncharted territories of AI-empowered robotics, continuous research and thoughtful integration of these technologies will shape a promising and harmonious coexistence between humans and machines.
A CYBER–PHYSICAL SYSTEMS PERSPECTIVE ON SMART GRIDS
Authors: S J Rudresha , R Gopinath Harsha , G R Kiran kumar , S Shruthi , S Kalpana
Published: June 2024

Cyber physical system is a type of system that combines computation, networking, and physical processes in a single system. The CPS technique to system design has been widely applied in numerous sectors, but it is relatively new in the design of power systems. The special characteristics of CPS are projected to considerably improve future smart power networks. Smart grids are electric systems that use modern control, monitor and communication technologies to ensure a continuous and stable power supply. Smart Grid technology will transform modern industry by offering significant solutions for improving the efficiency of traditional electric grids. It improves generator and distributor operation efficiency and provides prosumers with a variety of options. Smart grids are a hybrid of complicated physical network systems and cyber systems that face a number of technological difficulties. This chapter outlines these issues in view of cyber–physical systems along with possible contributions of cyber–physical systems to smart grids and the problems that smart grids provide to cyber–physical systems. Lastly, the impacts of recent advanced technologies on smart grids are discussed.
MACHINE LEARNING AND DEEP LEARNING REAL TIME APPLICATIONS
Authors: Karpagavalli C. , M. Kaliappan Dr.
Published: June 2024

Machine learning is a current hot topic in the modern computer world and is a branch of artificial intelligence. Many researchers have contributed their work in this field to enhancing the accuracy and intelligence of machine learning approaches. Learning is a process to create a new concept, which is used in machines too. In addition, another deep learning notion begins to play a significant role. A branch of machine learning called deep learning (DL) uses neural networks and is utilized for many real-time applications owing to its automatic learning strategy. This chapter presents an overview of machine and deep learning approaches and their real-time applications.
ARTIFICIAL INTELLIGENCE EMPOWERING THE DIGITAL WORLD
Authors: Manaswi Dhanda , Sharma Dr. Meenu
Published: June 2024

The present time have seen a significant impact of AI in vivid fields such as industry, healthcare, industry, software development, cybernetics, arts, law, etc. however, the main idea behind integrating AI among all remained the same, one was to remove individual bias and the other is automation. In the pandemic times of Coronavirus Disease (COVID-19), the digitalization has taken a new turn not only in detection and diagnosis of the virus, but also towards economy management via several employment channels. Moving forward AI has improved the capabilities of cloud computing for handling enormously evolving data owing to vivid cloud services. This not only empowers the urban smart designs such as smart homes, intelligent transport system, healthcare wearables, but also remote health diagnosis. Despite of the fact that more than a decade has been celebrated by AI, it still lacks a single platform that provides all this information at one go. To address this research gap, the author has presented a concise review of current applications and futuristic possibilities offered and empowered by AI in revolutionizing the digital world.
LOW LIGHT VIDEO PROCESSING FOR ENGINEERS: AN OVERVIEW
Authors: Anitha C.
Published: June 2024

"Low Light Video Processing for Engineers: An Overview", offers a comprehensive exploration of the challenges and advancements in the domain of low-light video processing. As the demand for high-quality video in low-light conditions continues to rise across various applications, this paper presents a valuable overview of image quality in challenging lighting scenarios. From understanding the underlying principles of image sensing in low light to exploring state-of-the-art denoising, illumination correction, and image fusion techniques, this abstract aims to equip engineers with a foundational understanding of low-light video processing. Moreover, it highlights the key considerations and trade-offs involved in implementing such processing methods, emphasizing real-world applications in surveillance, automotive vision, and night-time photography. By grasping the fundamental concepts presented in this overview, engineers can embark on a journey to create cutting-edge solutions that significantly improve video quality and reliability under adverse lighting conditions.
A NOVEL PREDICTION MODEL FOR PSORIASIS SKIN DISEASE DETECTION USING COMPUTER VISION APPROACH
Authors: Chiranjeevi Iyli , S Raksha , Rishitha K Sai , Kumar Neelapala Anil
Published: June 2024

According to the advanced overview, more than 125 million people are suffering from Psoriasis and skin cancer. The skin cancer rate has quickly increased over the last few decades, especially Melanoma is the foremost differentiating skin cancer. Dermatophytosis moreover incorporates a tall rate, particularly within the country zones. If skin infections are not treated promptly, they can cause internal consequences, including the transfer of the disease from one person to the next. Skin diseases can be avoided by inspecting the polluted area as soon as possible. The qualities of the skin images have expanded, making it difficult task to design proficient and strong calculations for the planned identification of skin illness in its severity. Skin tone and colour are critical in detecting skin illnesses. Outwardly, skin colour and coarseness are unique. To differentiate various infections, programmed treatment of such images for skin investigation requires a quantitative discriminator. The proposed system is a combination demonstration for the detection and early detection of skin cancer, psoriasis, and Dermatophytosis [1]. Skin disease diagnosis is mostly based on several features such as shape, colour, surface, and so on. Skin infections have no medically recognised therapies. Different doctors will handle the same side effects in surprising ways. Early detection and treatment of skin diseases is a critical factor in their therapy. The proposed framework is used for the diagnosis of a variety of skin diseases using measurable parameter analysis. Measurable examination is at odds with irregular information examination. Irregular information is intended for skin diseases. [2]. A standard database is utilized for this information does not have any scientific expression; it has a few measurable properties. To examine irregular information, we must analyze factual properties of it.
BREAST CANCER PROGNOSIS PREDICTION USING NOVEL SHRUNK KERNEL KNN METHOD WITH MLO AND CC FEATURES
Authors: V. Sridevi Dr.
Published: June 2024

The most continual malignancy found in women is breast cancer. The good news is that if detected early, it is one of the most treatable forms of cancer. High-dimensional data results in large number of computation redundancy but also advances diagnostic techniques. As a result significant information must be extracted and the feature dimension must be reduced for good prediction and a precise treatment decision. However, past studies for diagnosing breast cancer have relied mostly on labelled data that is difficult to get. To solve this problem, two different sorts of perspectives, such as CC and MLO are employed to improve diagnostic effectiveness. This chapter comprises segmentation, feature extraction and classification of images. The two perspectives from a mammography picture are segmented using the adaptive K-means clustering approach. The Gabor filter is used in conjunction with the traditional k-means clustering method during the feature extraction stage to extract the features of the CC and MLO perspectives. The mammography image is finally classified into benign and malignant using a unique Shrunk Kernel K-Nearest Neighbor (SKKNN) classifier.
CHAUFFEUR BEHAVIOR RECOGNITION USING FACE RECOGNITION AND DEEP LEARNING
Authors: C Lohith , A M Amaresh , Chavan Pundalik , N Triveni
Published: June 2024

High levels of focus are necessary for safe driving, but these behaviors are frequently overridden by distractions like tiredness, eating, drinking, talking, and phone calls. Sadly, these distractions play a significant role in the worrying increase in traffic accidents nowadays. The creation of software that can proactively inform drivers is essential to resolving this pressing problem. This study suggests a novel, lightweight architecture for convolutional neural networks that is intended to recognize different driving styles, enabling warning systems to provide accurate information and dramatically lowering traffic collisions. This network effectively recognizes and categorizes driver behaviors by fusing feature extraction and classifier modules. By combining these elements, in the neural network, feature extraction is intended to be more effective and efficient. The model may lower computing costs and enhance information flow through the network by utilizing depth-wise separable convolutions and adaptive connections. Furthermore, the Convolution Block Attention Module can assist the network in prioritizing crucial features, improving performance across a range of computer vision applications. Using a global average pooling layer and a soft max layer, the classifier module successfully calculates class probabilities. This carefully thought-out architecture makes sure that the network parameterization is optimized while yet maintaining good classification accuracy. On three benchmark datasets, the entire network is painstakingly trained and carefully assessed, confirming its dependability and robustness.
SAVITHRI MATH FOR MOTHERS: DEVELOPMENT AND GLOBALIZATION USING AI
Authors: Venkatesan Dr. S. , B. E Ms. C. Maheshwari , Misra Ms. Surbhi , Srinivasan Mrs. Saraswathi
Published: June 2024

Mathematics has an important role in the development of science and technology. Making mothers confident in mathematics(math) will contribute to national growth and well being. Here we conceive a course which presents mathematics within a spiritual background since mathematical competence is to be considered as a spiritual value.The spiritual background is to be provided by Savithri, a legendary work by Aruobindo. Mathematical content are based on Lilavati (an ancient Indian text presenting math in puzzle-poems) and books of Skantula Devi (an Indian mental calculator and writer of popular books on math for the public).We show how brief introduction about these works can be got through chatGPT. Course lesson plans are generated using AI tools. The course is to be offered in other languages in Hindi,Tamil and French. We highlight how AI tools help rapid development and globalization of such a course.
CORPORATE SOCIAL RESPONSIBILITY: A COMPREHENSIVE ANALYSIS OF CONTEMPORARY PRACTICES AND IMPLICATIONS
Authors: J Dhivya Dr. , P Rajan Prof. , J Mary Saranya Dr. , S Aishwariya Mrs.
Published: June 2024

This research paper provides a comprehensive and original analysis of Corporate Social Responsibility (CSR) in the context of contemporary business practices. The paper explores the multifaceted nature of CSR by examining its definition, conceptual framework, benefits, challenges, stakeholder engagement strategies, measurement approaches, and notable examples of successful CSR initiatives. The objective of this paper is to contribute to the existing body of knowledge on CSR and offer insights for organizations aiming to enhance their social and environmental impact while maintaining long-term profitability and sustainability. Drawing upon extensive research and literature, the paper highlights the future scope of CSR, outlining potential areas of exploration such as the integration of CSR into business strategy, effective measurement and reporting of CSR impact, alignment with sustainable development goals, ethical supply chain management, considerations in the digital era, and understanding CSR in emerging economies. By presenting a comprehensive analysis, this research paper serves as a valuable resource for academics, practitioners, and organizations seeking to understand, implement, and advance CSR initiatives within their respective contexts. Proper paraphrasing and appropriate citation have been employed to ensure the absence of plagiarism in the paper's content.
AI-ENABLED DEVICE FOR KNOWLEDGE ACCESS IN RURAL INDIAN COMMUNITIES
Authors: Maria A.
Published: June 2024

A voice-activated, AI-powered device that bridges the knowledge gap and empowers rural individuals. This device uses the power of artificial intelligence (AI) to provide rural individuals with access to essential knowledge and services. It can help them with a variety of tasks, including: • Managing their government-issued identification documents, such as Aadhaar cards, PAN cards, Ration Card and voter IDs. • Opening and managing bank accounts. • Scheduling agricultural work. • Paying electricity bills. The device uses AI, neural networks, and machine learning algorithms to personalize content and provide tailored recommendations. It can also be used to collect data on user behavior, which can be used to improve the device's performance and effectiveness. The device is designed to be simple, intuitive, and user-friendly. It can be used by people with limited literacy skills, and it can function offline, making it accessible in remote areas with limited internet connectivity. The device is a powerful tool for empowerment. It has the potential to narrow the digital divide between rural and urban areas, and it can help rural individuals reach their full potential. This device is a voice for the voiceless. It is a bridge to a brighter future.
ITERATIONS, STRINGS AND FILES IN PYTHON APPLICATION PROGRAMMING
Authors: Renuka Sagar Dr.
Published: June 2024

In Python application programming, iterations, strings, and files play crucial roles. Iterations, achieved through loops, allow efficient repetitive tasks. Strings, sequences of characters, facilitate text manipulation and processing. File operations enable reading from and writing to external storage, enabling data persistence. These concepts collectively empower developers to create versatile and powerful applications.
A GAZE INTO IDENTITY: AGE AND GENDER RECOGNITION WITH DEEP CNNS
Authors: S Vishnu Vilashini , P. Baby Maruthi Dr.
Published: June 2024

Age and gender recognition, integral to modern computer vision, holds transformative potential across industries and applications. At the heart of this progression lies the power of Convolutional Neural Networks (CNNs), which have revolutionized the accuracy and efficiency of age and gender recognition tasks. This chapter embarks on an insightful journey, navigating the evolution of CNN architectures, intricate challenges posed by facial variations, ethical implications in handling sensitive data, and real-world applications across diverse domains. It delves into the profound implications of collaborative intelligence, where AI and human experts coalesce to elevate decision-making. As the chapter culminates, it sets its gaze on the horizon of possibilities, embracing emergent technologies, ethical considerations, and the synergy between technological advancement and the fundamental essence of human characteristics. The ability to extract age and gender information from visual data holds immense potential for personalized healthcare, marketing strategies, security systems, and user experience enhancement in technology interfaces. By exploring the intricate interplay between deep learning architectures and human attributes, this chapter unravels the dynamic journey from foundational CNN concepts to cutting-edge innovations, while addressing challenges, ethical considerations, real-world applications, and the exciting horizons of future possibilities. Through this exploration, the chapter underscores the symbiotic relationship between technological advancement and the nuanced understanding of human characteristics.
SEARCHING TECHNIQUES IN AI
Authors: Tawali Deepak
Published: June 2024

In artificial intelligence (AI), searching techniques refer to algorithms and strategies used to explore and navigate through problem spaces in order to find solutions or make decisions. These techniques are often applied in various AI applications, such as problem-solving, planning, game playing, path finding, and more. In the field of artificial intelligence, various types of search algorithms are used to explore and find solutions in different problem-solving scenarios. These search algorithms can be categorized into three main types: uninformed search (blind search) and informed search (heuristic search) and adversarial search.
A CASE STUDY: GURUKRUPA RESIDENTIAL SCHOOL FOR SPECIAL CHILDREN
Authors: Sharadkumar Chauhan Dr. Sweta
Published: June 2024

Education is important for the development and progress of any society. Teacher and student, in this education process, are the two important poles. Teacher is a mature and students are immature personalities. Indian Classrooms are full of diversity. This diversity is in the context of IQ, achievement, caste, religion, backwardness, able and specially able learners etc. There ways of learning differs. For the overall development of students the school should provide student-friendly atmosphere in the context of educational, social and physical abilities. Cognitive and affective development of students occurs when it is based on social and emotional potential. Students with special needs are mainly not enrolled in a normal school. They are admitted to a special school that keeps them away from the society. In order to develop their personality quality education needs to be provided along with special care on school education and Methodology of teaching, so that they can get proper education and meet their needs appropriately. In this case study researcher study the school education of special children.
FUTURISTIC TRENDS IN PSYCHOLOGY
Authors: Srivastava Dr. Nehashree , Shukla Dr. Jagriti
Published: June 2024

Psychology is a very diverse subject. As a social science, it has a very broad scope. Psychology is the scientific study of human mind and behaviour; therefore, it is gaining importance day by day. In my opinion, if anything is linked to human behaviour, it will never be outworn, and most importantly, its importance will grow with the passage of time. This multidimensional subject can be converged with almost all the schools of subject, and hence the future of Psychology has a steady base worldwide. Psychology is no longer limited to a certain traditional job; researchers in the future may be responsible for carving out some new combinations that will provide a wide spectrum of career opportunities. The new age will witness the coming together of various streams to provide solutions to the world's problems. The beauty of Psychology lies in the fact that every aspect of human life is dependent on behaviour; thus, by conducting research and using the findings innovatively and creatively, one can work on certain new sub-departments. The new World opens Psychology to the gates of counselling, Forensic Psychology, Sports Psychology, Social Psychology, Political Psychology, Industrial Psychology, Media Psychology, Environment Psychology, Community Psychology, Military Psychology, and Health psychology, Criminal Psychology, to name a few.
EXPLORING USE OF COW URINE FOR EMMISON CONTROL
Authors: Mandhre Mr. Mohnesh Dnyaneshwar , Ghalme Dr. Sachin , B. Kale Mr. Aditya , Klahapure Mr.Amol
Published: June 2024

Air pollution is becoming increasingly important for us due to the rising number of petrol and diesel engine vehicles, which is leading to a significant increase in pollution and contributing to global warming. Therefore, it is crucial that we work towards reducing air pollution. The primary objective of this research is to conduct an experimental inquiry aimed at diminishing the release of harmful pollutants, including Hydrocarbons (HC), carbon monoxide (CO), carbon dioxide (CO2), and Nitrous Oxide (NOX), originating from the internal combustion engine of motor vehicles. These noxious emissions stem from the combustion of fuel, contributing to environmental degradation. A promising strategy for mitigating the effluence of these hazardous compounds during the combustion process in vehicular engines involves the utilization of catalytic converters based on noble metals. These catalytic converters effectively transform detrimental CO and HC gases into less harmful byproducts such as CO2 and H2O. Nevertheless, addressing concerns associated with the availability and cost of noble metals prompts the exploration of innovative alternatives. In light of this, a unique approach is proposed, involving the application of natural fluids to curtail emission levels. As an integral part of this research endeavor, various natural liquids, including cow urine, were subjected to pH testing and subsequently introduced into the exhaust system as distinct liquid agents. This research aims to find an alternative and eco-friendly solution to curb automotive emissions and combat air pollution effectively.
Comparative Study of Social Entrepreneurship Management for School Sustainability
Authors: Nurwaningsih Maria Dwi , Santosa Budi
Published: June 2024

Catholic private schools continue to make improvements, both in governance and learning innovation. Education service providers are encouraged to innovate to be able to face government policies and free market competition. One of them is through social entrepreneurship because social entrepreneurship is slowly entering the education system. Social entrepreneurship, with its mission-driven focus on creating value and positive environmental impact, supports the sustainability of the institution. By implementing social entrepreneurship in the management of school institutions, education plays a role in overcoming social and environmental problems. This study aims to analyze social entrepreneurship management for school sustainability, taking the objects of Sint Antonius Junior High School East Jakarta and Sang Timur Junior High School Karang Tengah. This qualitative research uses observation methods, in-depth interviews using snowball techniques, and forum group discussion on 165 informants. The research aspects are social entrepreneurship, social entrepreneurship strategy, social entrepreneurship management, the impact of implementing social entrepreneurship management, and the linkage of social entrepreneurship management with ISO 26000 and SDGs no. 4 and 12. The findings show that both schools have implemented social entrepreneurship, which needs to be improved for school sustainability. This study provides recommendations for education providers on whether they should develop social entrepreneurship management for school sustainability. Institutions need to build a comprehensive social entrepreneurship management system that is strengthened with a focus on social entrepreneurship and support of social entrepreneurship processes.
Spectral reflectance analysis for genome-wide association of thali rice Oryza sativa L. Under phosphorus-deficient condition
Authors:   , Pinit Sompop
Published: June 2024

The goals of this research have three main points: (i) to develop a rapid method for inorganic phosphorus quantification, (ii) to investigate spectral reflectance indices representing phosphorus deficiency in rice, and (iii) to determine SNPs associated with phosphorus deficiency tolerance in Thai rice via genome-wide association study (GWAS).

The punching method was developed to enhance the high throughput performance of the conventional Pi extraction and molybdate blue assay. Pi content can be extracted using equally small leaf areas without leaf grinding, balancing, and tedious transferring steps. The punching method provided comparable results to the conventional grinding method with a strong correlation in high and low accumulation rice cultivars under a phosphorus supplement series. Thousands’ Pi content of rice samples can be quantified within a few hours, exactly suited for large-scale phenotyping or screening experiments. P deficiency response of 172 Thai rice (Oryza sativa L.) accessions grown in three different P concentrations. I detected Pi content and spectral reflectance data by using the punching method and hyperspectral measurement, respectively. Pi content showed sensitive evaluation results to identify P deficient level in each different treatment. For hyperspectral analysis, ratio indices between NIR and VIS wavelength showed a strong correlation with Pi content without spectral interference. The 217 ratio indices and Pi content were associated with 113,114 SNPs derived from the whole-exome sequence. The 48 significant SNPs with low P-value were predicted from both R750/R700 and R740/R560. At the same time, Pi content association served 15 significant SNPs, which 3 SNPs of these superimposed from the index association. Interestingly, several known genes involving in P deficiency regulation were found that confirmed correct association affected by the performance of the novel phenotypic traits. Overall, the numerous candidate genes exposed their possibility in P deficiency modulation by considering previous gene expression, QTL mapping, and reported function.
การพัฒนาชุดตรวจที่ง่ายต่อการใช้งานสำหรับวัณโรคในช้างโดยอินเตอร์เฟียรอนแกมมารีลีส
Authors:   , พงษ์มา จิตสุดา
Published: June 2024

วัณโรค เป็นโรคติดต่อจากสัตว์สู่คนหรือจากคนสู่สัตว์ที่เป็นปัญหาด้านสาธารณสุขที่สำคัญระดับโลก รวมถึงในประเทศไทย เนื่องจากเชื้อ Mycobacterium tuberculosis (M. tb) complex (MTBC) ซึ่งเป็นเชื้อสาเหตุของวัณโรค สามารถพบการติดเชื้อได้ในสัตว์หลายกลุ่ม ทั้งสัตว์เท้ากีบ สัตว์ตระกูลลิง สัตว์เลี้ยงลูกด้วยนมรวมถึงช้าง การวินิจฉัยวัณโรคในช้างทำได้ยาก เนื่องจากช้างเป็นสัตว์ที่มีขนาดใหญ่ จึงไม่สามารถวินิจฉัยได้ด้วยวิธีเดียวกับมนุษย์ เช่น การเอกซเรย์ปอด และการทดสอบทางผิวหนัง นอกจากนี้ วิธีมาตรฐานโดยการเพาะเลี้ยงเชื้อจากน้ำล้างงวงช้างมีความไวต่ำ ใช้เวลานาน และตรวจได้เฉพาะระยะที่แสดงอาการเท่านั้น ดังนั้น การตรวจวินิจฉัยที่แม่นยำ ครอบคลุมทุกระยะการติดเชื้อ M. tb จึงเป็นสิ่งจำเป็น นำมาสู่การประยุกต์ใช้เทคนิค Interferon gamma release assay (IGRA) สำหรับเป็นวิธีทางเลือกในการวินิจฉัยวัณโรค ซึ่งเป็นวิธีตรวจหาอินเตอร์เฟียรอนแกมมา (IFN) ที่มีการหลั่งออกมาจากทีลิมโฟไซต์ชนิด memory หลังถูกกระตุ้นด้วยแอนติเจนจำเพาะของ M.tb งานวิจัยนี้จึงมีวัตถุประสงค์ที่จะพัฒนาวิธี IGRA ให้ใช้งานได้ง่ายกว่าที่มีอยู่เดิม โดยการคัดกรองเพปไทด์สังเคราะห์ของโปรตีน early secreted antigenic target 6 kDa (ESAT6) และ culture filtrate protein 10 kDa (CFP10) ที่สามารถกระตุ้นการหลั่ง eIFN ของเซลล์เม็ดเลือดขาวของช้าง และพัฒนาวิธีการตรวจโดยการกระตุ้นแบบ whole blood culture โดยเริ่มทำการตรวจการติดเชื้อของช้างด้วยวิธี IGRA เดิม (IGRA โดยใช้เซลล์เม็ดเลือดขาว PBMCs) ในตัวอย่างเลือดจากช้าง 20 เชือก โดยมีโปรตีนทั้งสายเป็นแอนติเจน พบว่าช้างมีการติดเชื้อ MTBC 50% ของตัวอย่างทั้งหมด ไม่ติดเชื้อ 30% และ 20% มีการติดเชื้อกลุ่ม Non tuberculous mycobacterium (NTM) จากนั้นทำการคัดกรองเพปไทด์สังเคราะห์ของโปรตีน ESAT6 และ CFP10 ในช้างทั้ง 20 เชือก พบว่าเพปไทด์สังเคราะห์ของโปรตีน ESAT6 และ CFP10 ที่มีประสิทธิภาพในการกระตุ้นเซลล์เม็ดเลือดขาวของช้างที่คาดว่าติดเชื้อ MTBC ให้หลั่ง eIFN ได้ มีจำนวน 13 สาย และ 14 สาย ตามลำดับ สำหรับการพัฒนา IGRA ด้วยการกระตุ้นแบบ whole blood culture พบว่าสามารถใช้ Pokeweed (PWM) (10 ไมโครกรัมต่อมิลลิตร) เป็นสารกระตุ้นในกลุ่มควบคุมบวก และพบว่ารีคอมบิแนนท์โปรตีนของ ESAT6 และ CFP10 (20 ไมโครกรัมต่อมิลลิตร) สามารถกระตุ้นการหลั่ง IFN ได้ แต่กลุ่มของเพปไทด์ที่คัดกรองได้จากการกระตุ้นแบบ PBMC culture นั้น ไม่สามารถกระตุ้นเซลล์เม็ดเลือดขาวได้ด้วยการกระตุ้นแบบ whole blood culture ผลการศึกษาในครั้งนี้แสดงให้เห็นว่า การกระตุ้นแบบ whole blood culture โดยใช้แอนติเจนทั้งสายของโปรตีน ESAT6 และ CFP10 สามารถใช้เป็นวิธีทางเลือกสำหรับการวินิจฉัยวัณโรคในช้าง ซึ่งเป็นวิธีที่ง่ายต่อผู้ใช้งาน และรวดเร็วกว่าการวินิจฉัยด้วย PBMCs IGRA
Some Properties Of Extending Hypermodules, C11-Hypermodules And T-Extending Hyperrings
Authors:   , Wongyai Chokchai
Published: June 2024

In this research, extending hypermodules, C11-hypermodules and t-extending hyperrings are defined and studied. We characterize extending hypermodules, C11-hypermodules and t-extending hyperrings in many ways under some conditions of hypermodules and hyperrings. Moreover, some properties concerning subhypermodules of extending hypermodules and C11-hypermodules are investigated. Especially, we study C11-hypermodules in the case that they can be decomposed as a direct sum of two subhypermodules.