Volume 12 | Issue 11

 Abstract

Acquiring knowledge is a phenomenon, where the owner of it gains through different mechanisms-through experience, external factors, internal factors, formal, informal, etc. and it may be tacit or implicit or explicit. Some knowledge is such that it is confined to some special group/clans or very much intervened/mingled with lifestyle or functional life/culture of the community. And such knowledge is mostly undocumented which hinges around the community and pass on generations to generations orally or through practice, legends, myths, taboos, poetry, etc. Such a treasure of knowledge is known as the indigenous knowledge or traditional knowledge. The beauty and pride of such knowledge is incomparable. Some communities are well known for their indigenous knowledge they retains. In the contemporary world, if modern technology and indigenous knowledge are simultaneously capitalized then some of the unaddressed problems related to every realm of life may be mitigated in more effective and efficient manner. Indigenous knowledge are very rich in nature but it is vanishing from its existence because these kind of knowledge is usually not documented, possessors are not willing to share, and not practiced. So, through this paper author attempts to highlight the issues and challenges confronted in the process of its documentation and dissemination of the same to reap full advantage

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 Keywords

Local knowledge, indigenous knowledge, documentation, dissemination, management model, AYUSH

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Addressing the skill shortages in the country, enhancing worker employability, meeting industry needs and driving economic growth depend greatly on India's Vocational Education and Training (VET) system. However, this mechanism is not independent of challenges such as economic, social and institutional. This review paper examines the prospects and problems in India's VET system, which is essential for fulfilling the country's changing labour demands. These obstacles reduce the efficiency of VET by creating a mismatch between the skills taught and those that employers require. The National Education Policy (NEP) 2020 seeks to normalise skill-based learning by integrating VET into regular education. India's VET sector may significantly improve its role in creating a competent, flexible workforce that is in line with domestic and international economic demands by tackling these issues. These components have been incorporated in this study to give an in-depth review that will guide future growth plans for the industry.

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Indian VET System, Challenges, Public-Private Partnership, National Education Policy 2020, Curriculum Modernisation

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The Role of Non-Governmental Organizations in Rural Development of India.

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The Role of Non-Governmental Organizations in Rural Development of India.

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The study looks at the hydrobiological properties of selected water bodies at different altitudes in Southern Tamil Nadu particularly focus on water quality, biodiversity and ecosystem health. The study seeks to evaluate the physical, chemical and biological properties of four freshwater ecosystems: Suthamalli Dam, Thenkarai Pond, Manjalar Dam, and Shanmuganathi Reservoir. These locations serve as crucial for irrigation and drinking water, but they are under threat from environmental factors such as Climate change, agricultural runoff , industrial pollution and anthropogenic activities which leads to eutrophication of the waterbodies. This study assesses phytoplankton, zooplankton and fish species composition, nutritional content, and heavy metal concentrations using field sampling and laboratory analysis. Statistical modelling and Geographic Information System (GIS) approaches reveal regional trends in water quality and biodiversity. The findings provide valuable insights and significant data into the impact of environmental changes on aquatic ecosystem health in Southern Tamil Nadu the conservation and sustainable management of these ecosystems. This research also supports local environmental management authorities in preserving aquatic biodiversity in the ecologically sensitive Western Ghats region.

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Hydrobiology, Water quality, Biodiversity, Altitudinal variation, Western Ghats, Tamil Nadu

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Stress, Coping strategies, Female football players

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The rise of digital technologies has revolutionized the way f the individuals to express themselves and interact with the world , leading to to the emergence of digital footprints- traces left by the users through through their online activities on social media, websites, and various online platforms. These footprints, formed through online activities, provide valuable insights into personality traits.Digital footprints, comprising online behaviors, social media activity, and other internet usage patterns, provide rich data sources for understanding personality traits. By analyzing these footprints, researchers can gain insights into personality traits,giving the way for applications in marketing, mental health, and education, while also raising important ethical considerations. This review explores the ways for personality prediction using digital footprints or the digital presence of an individual, examines key findings and applications. We have combined the concept of psychology and data science for predictions , focusing on the potential benefits and challenges in this new emerging field.

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 Keywords

personality prediction, Big five inventory, Myers-Briggs Type Indicator

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Ethics, morals, values, are the guiding force of our behaviour; Ethics which is plays central role stability and continuity of any society. This article deals with the philosophical background of strong ethical values of Buddhism; how it was destroyed by the arrival of Islam and the governing system in Central Asia. The transmission of Buddhism into central Asia is evolving as archaeological interpretation of the history of the central Asia. The spread of Buddhism in Central Asia by the Kushan (Kusana) dynasty through the silk trade route which was also became an channel for the transmission of art, literature, architecture, technology, culture, religion, philosophy, etc to different countries in Asia. Religion has played a major role in the history of Central Asia and religion is one of the important factors of social development. However, the conversion to Islam on revive of the Arabs and the demolition of Buddhist stupas and destruction of manuscripts, persecution of Buddhists which shown that how the Buddhism was declined by the Arabs. The Silk Route which is also known as the 'Ancient International Trade Road' that spread from China to Italy existed from second century BC to fifteenth century AD. This silk route was known for trade, many items such as silk, paper, raw materials and other goods was exported through India to China and Central Asia. This route also became a channel for the transmission of art, culture, religion, literature, architecture, philosophy, technology, etc to different countries in central Asia and beyond. Buddhism which was developed in India is one of the most important religions that transmitted through the Silk Road to central Asia.

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Central Asia, Religion, Buddhism, Silk Road, Islamization

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Deep Learning (DL) has become a crucial tool in predicting heart disease, offering significant advancements in early detection and personalized healthcare. These models can then predict the likelihood of heart disease in new patients based on similar input data. The existing system does not predict the specific type of heart disease, such as coronary artery disease, heart failure, or arrhythmia and it does not provide personalized treatment recommendations based on patient-specific characteristics and medical history. The system can improve patient care by enabling healthcare professionals to make informed decisions and provide personalized treatment plans. This system can detect heart disease at an early stage, enabling timely interventions and improving patient outcomes. The existing system does not predict the specific type of heart disease, such as coronary artery disease, heart failure, or arrhythmia and it does not provide personalized treatment recommendations based on patient-specific characteristics and medical history. CNNs can analyze medical images and data with high accuracy, enabling early detection of heart disease. Early diagnosis allows for timely intervention, reducing the risk of severe complications and improving overall public health. By accurately identifying high-risk patients, healthcare resources can be allocated more effectively, ensuring that those who need it most receive timely care.

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Heart Disease Prediction, Deep Learning, Convolutional Neural Networks (CNNs), Healthcare Resources, Heart Failure

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The rapid expansion of Android devices in the consumer and business markets highlights how important it is to have strong security standards in place to guard against changing online threats. Inherent weaknesses still exist despite improvements in security protocols, providing opportunities for malevolent actors to take advantage of. The strategic integration of an ATTiny85 microcontroller via the USB interface to take advantage of potential weaknesses is the main emphasis of this project, which explores the complex world of Android device security. Additionally, by highlighting potential flaws and associated exploitation methods, this initiative adds to the continuing discussion about Android device security. It seeks to clarify the complexities of contemporary security threats and promote a proactive strategy for protecting Android devices against malevolent intrusions through empirical research and testing.

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Project Scope and Limitations, Technical Restrictions, Problem with Compatibility, Legal and Moral Aspects to consider, Risk to Security, Objective of the Proposed Model, Attity 85 USB, Injecting Brute Force Code, Plug Android to Device, Attempt to unlock device, Algorithm Code, System Requirements, Future scope and Limitations, Conclusion

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The segmentation of fingerprints is a crucial step in automating the identification process. It is necessary to separate the ridge and valley structure of the fingerprint from the background, which often contains irrelevant data that can interfere with accurate feature extraction. In the proposed approach, fingerprint segmentation is treated as a classification problem, where the input image is classified into either the foreground or background class. To achieve this, an unsupervised learning algorithm called Stacked Sparse Autoencoder is employed to learn deep features that effectively distinguish the background region from the foreground. These deep features are then inputted into the SVM classifier. The results of the experiments demonstrate that the proposed method achieves state-of-the-art performance across various applications.

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Autoencoder, fingerprint segmentation, morphology

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This study presents a hybrid cyberbullying detection model that integrates advanced machine learning algorithms--Linear Support Vector Machines (LSVM) and Recurrent Neural Networks (RNNs)--to address the growing issue of cyberbullying on social media platforms like Twitter and Facebook. As cyber threats become increasingly sophisticated, traditional security measures often fall short, making the application of machine learning crucial for real-time detection and mitigation. Utilizing a dataset of text expressions, the system achieves an impressive 85% classification accuracy with LSVM and an 81% feature extraction accuracy with RNN, outperforming both deep learning and traditional machine learning techniques. The research employs Object-Oriented Analysis and Design Methodology (OOADM) to create a modular and efficient software solution that processes real-time messages for cyberbullying characteristics. The results highlight the superior capabilities of RNN and LSVM in analyzing complex patterns, essential for effective cyberbullying detection. By combining technical advancements with human engagement, this study emphasizes the need for a multifaceted approach to combat cyberbullying. The proposed framework not only enhances cybersecurity measures but also contributes valuable insights into the intersection of machine learning and online safety. Ultimately, this research offers a proactive defense strategy, demonstrating the potential of cutting-edge AI methods to address emerging cyber threats effectively.

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Cyberbullying Detection, Online Bulling, Machine Learning, Bulling, Text Tracking

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This study aims to assess depression, anxiety, and stress levels among college students using the DASS-21 (Depression, Anxiety, and Stress Scale-21) instrument. Given the growing mental health concerns within the college demographic, especially with the unique pressures of academic, social, and financial demands, the need for reliable tools to evaluate these mental health conditions is paramount. The DASS-21 scale, a concise and validated measure, is widely used for assessing the severity of these psychological states. Through a cross-sectional survey, students' responses to the DASS-21 items will provide insights into prevalent mental health issues and help identify key risk factors. Findings from this study aim to inform university counseling services and mental health support initiatives, contributing to strategies for early intervention and support systems tailored to student needs.

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Depression, Anxiety and Stress Scale-21, Postgraduate students of Jain University.

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The desire for happiness is universal. Not all are able to actively pursue it and if they do, they fall short since the concept of Happiness is vastly misunderstood. Happiness is assured when there is purpose and meaning to life. Finding our life purpose is however challenging. In this article, I attempt to revive one of the ancient tools for revealing our life purpose, Vedic Astrology, describe who the contenders are, and the role played by the Atmakaraka.

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Happiness, Life Purpose, dharma, Archetypes, Vedic Astrology, Atmakaraka

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Media trials have become increasingly prevalent in India, with media entities often assuming quasi-judicial roles in high-profile cases. This paper analyses the implications of media trials on the judicial process and the fundamental rights of the accused in India. Through examining key case studies and judicial responses, it investigates how media trials shape public opinion and affect fair trial rights, often leading to sensationalism, bias, and infringement of privacy. While media trials may aim to promote accountability, this paper argues for a regulatory framework to balance media freedom with safeguarding judicial integrity and the rights of individuals involved in legal proceedings. The paper offers insights into the need for responsible journalism that upholds democratic values without compromising due process and fairness.

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Media Trials, Judicial Process, Fundamental Rights, Fair Trial, Privacy, India

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This research study presents a comparative analysis of various dynamic control strategies for robotic manipulators. The study investigates and evaluates different control approaches, including feedback linearization, computed torque control, passivity-based control, among others, in terms of their performance characteristics. Through simulation studies and experimental validations, the effectiveness of each control strategy is assessed with respect to trajectory tracking accuracy, disturbance rejection capability, energy efficiency, computational complexity, and adaptability to changing operational conditions. The research also highlights the trade-offs and limitations of each control strategy, offering valuable insights into their practical applicability in real-world robotic systems. The findings of this study aim to provide guidance for engineers and roboticists in selecting the most appropriate dynamic control strategy for specific manipulator applications, thereby contributing to the advancement of robotic manipulation technologies.

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Adaptive Control, Computed Torque Control, Computational Load, Dynamic Control Systems, Feedback Linearization, Nonlinear Dynamics, Parameter Adaptation, Passivity-Based Control

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Abstract: This paper explores the multifaceted dimensions of women's empowerment and gender equality across various cultural and socio-economic contexts through The Convention on the Elimination of All Forms of Discrimination against Women (CEDAW). It was adopted by the United Nations in 1979, and serves as a foundational international treaty aimed at promoting gender equality and empowering women worldwide. This paper explores the impact of CEDAW in transforming legal frameworks, fostering social change, and enhancing women's rights. By obligating signatory nations to eliminate discrimination against women in all forms, CEDAW provides a comprehensive framework for addressing issues such as violence against women, economic inequality, and political participation. It is instrumental in reshaping societal norms and legal frameworks, driving systemic change that empowers women and promotes their fundamental rights on a global scale. The paper will discuss in detail the barriers that women face, including legal, economic, and social challenges, and highlights successful strategies implemented in different countries to promote gender equity at International Level.

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Key Words: Convention, Discrimination, Rights, Women and United Nation

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 Abstract

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Aurones, Antimicrobial, Autodock by PyRx

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This paper is highleted to Aggression between individual and team game inter-collegiate women players . Aggression in sport can be caused by a number of factors. The most identifiable reasons are the rules of the game (level of physical contact), frustration, instinct, presence, arousal, environmental cues, self control and also the behavior of those around. Other factors in aggression include personality, media involvement, coaching, role models and the society we live in. The following is an insight into the term aggression in sport, using the social learning theory and environmental cues theory I will explain examples of each theory and try and contrast them.

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Sports,Psychology and Aggression.

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: The fourth-largest public sector bank in India was formed in April 2020 when Canara Bank and Syndicate Bank merged. This research looks into the effects of that merger. Significant gains in market share, operational effectiveness, and product diversification have come from the combination. Key findings show that the banking industry is now more competitively positioned, with more assets, deposits, and a wider branch network that enable greater consumer access and service provision. A number of strategic proposals are put up to optimise the benefits of the merger: give top priority to the seamless integration of corporate cultures and operations; make investments in state-of-the-art IT infrastructure; and carry out strong customer retention campaigns. Achieving long-term success will also require concentrating on personnel management and streamlining the branch network. All things considered, the merger is a revolutionary move for both banks, putting them in a better position to compete in a changing financial environment and improve service quality and operational robustness. To ensure ongoing growth and navigate future hurdles, it will be imperative to employ adaptive tactics and constant monitoring.

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Canara Bank, Syndicate Bank, Merger, Market Share, Operational Effectiveness, Branch network, Banking industry, Financial environment, Constant monitoring, Public Sector Bank, Competitive positioning.

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