Volume 13 | Issue 4 |

 Abstract

In the present-day rapid and technology-oriented supply chain scenario, real-time inventory decision-making is a crucial element of operational effectiveness as well as competitive edge. Conventional inventory systems usually do not possess the sufficient responsiveness and precision that can accommodate the demands of today. The merger of the Internet of Things (IoT) and Blockchain technologies holds a compelling answer to this dilemma. IoT allows ongoing real-time tracking of inventory using smart sensors, RFID tags, and networked devices, enabling precise tracking of stock levels, movement, and storage conditions. In contrast, Blockchain offers a decentralized, secure, and unalterable ledger that guarantees data transparency and integrity to all supply chain partners. By merging these two technologies, companies can create smart, automated, and data-based inventory systems. This article suggests a conceptual model that uses IoT for real-time data capture and Blockchain for secure data storage and automated decision-making. The model seeks to streamline inventory operations by enhancing visibility, trust, and enabling quicker, wiser decisions along the supply chain.

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 Keywords

IoT (Internet of Things), Blockchain, Inventory Management, Real-Time Tracking, Smart Contracts, Transparency, Security, Predictive Analytics, Supply Chain Optimization

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India's rural development plan has increasingly centered not only on developing infrastructure but also on the development of human capital in the form of skill upgradation and employment generation. Deen Dayal Upadhyaya Grameen Kaushalya Yojana (DDU-GKY), initiated by the Government of India, Ministry of Rural Development, is just such a flagship programme aimed at empowering rural youths by way of market-oriented skill training and employment. This research aims to measure the awareness of DDU-GKY among rural youth of Coimbatore district, Tamil Nadu, and evaluate its contribution to promoting sustainable rural development. The principal aim of this research is to measure the level of awareness, participation, and perceived effect of DDU-GKY among the intended beneficiaries. Aside from this, it also delves into the functions of different stakeholders such as training providers, local government units, and community leaders in the implementation of the program. The study is based on a mixed-methods research design where it merges quantitative surveys of 150 rural youth belonging to different blocks of Coimbatore with qualitative interviews of local government officials, training center coordinators, and program participants. Statistical tools and thematic content analysis were used to analyze the data to determine patterns and insights. Nevertheless, the impact of the programme on the beneficiaries has been generally positive. Improved skills, better employability, and, in a majority of cases, proper placement in retail, hospitality, and electronics industries were indicated by the beneficiaries. Even a few could transition into self-employment or entrepreneurship, which is testimony to the capacity of the scheme to generate livelihoods that are sustainable.

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 Keywords

Rural development, Skill development, Employment generation, Vocational training.

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 Abstract

Numerology, the mystical study of numbers and their influence on human life, has been a topic of intrigue for centuries. Rooted in ancient philosophies and diverse cultures, numerology posits that numbers are not merely mathematical symbols but also carriers of spiritual and metaphysical significance. This paper explores how numerology serves as a tool to understand individual qualities and predict future possibilities. By examining its historical origins, methodologies, and applications, this research aims to evaluate the validity of numerology as a framework for personal insight and future forecasting.

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 Keywords

Numerology, Future, Lens,

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Creative Commons Attribution 4.0 and The Open Definition

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The fashion industry has a significant impact on the environment, and sustainable fashion consumption (SFC) has become a pressing concern. This study aimed to investigate the factors influencing sustainable fashion consumption behavior (SCB) among adults, specifically the role of values, attitudes, and norms in shaping such behavior, using the value-belief-norm framework. The study used an online cross-sectional survey design to collect data from 350 participants recruited through a convenience sampling method using social media platforms and email invitations, and the obtained data were analyzed using partial least squares structural equation modelling. The results of the study showed that biospheric (BV), altruistic (AV), and egoistic (EV) values significantly influenced the New ecological paradigm (EP), which, in turn, positively affected awareness of consequences (AC). Personal norms (PN) were positively influenced by EP, AC, and ascription of responsibility (AR). Social norms (SN) and trust in recycling (TR) were also found to positively influence sustainable fashion consumption intentions (SCI). Finally, the study found that SCI and TR were significant predictors of SCB, whereas the moderating effect of TR not statistically significant. The study's originality lies in its comprehensive investigation of the interplay between various factors (particularly using norms in two facets; PN and SN) in shaping SCB, using a structural equation modeling approach, and exploring the moderating effect of TR. The findings of this study suggest that interventions aimed at promoting SFC should focus on fostering values and beliefs that prioritize the environment, encouraging individuals to take responsibility for their actions, creating an environment in which SFC is normalized, and increasing TR.

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 Keywords

Consumption behavior, Sustainable fashion, Environmental concern, Data analysis

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This study explores the effects of an eight-week plyometric training program on cardiovascular endurance in adolescent Taekwondo athletes aged 11 to 14 years. Recognizing the high physical demands of Taekwondo, which combines explosive power with sustained aerobic activity, the research aims to determine whether structured plyometric exercises can enhance cardiovascular fitness in this demographic. Forty participants were selected and randomly divided into experimental and control groups. While both groups continued their regular Taekwondo routines, the experimental group received additional plyometric training three times a week. Cardiovascular endurance was assessed using the Beep Test both before and after the intervention. Data were analyzed using descriptive statistics, paired sample t-tests, and ANCOVA to account for baseline differences. The results revealed a significant improvement in the experimental group's cardiovascular performance compared to the control group, with a large effect size indicating the effectiveness of the intervention. The findings affirm that integrating plyometric training with regular sports routines can significantly enhance cardiovascular endurance in young athletes. The study highlights the potential of such training in developing well-rounded, sport-specific conditioning programs and provides valuable guidance for coaches, trainers, and sports scientists working with adolescent populations.

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 Keywords

Plyometric Training Cardiovascular Endurance Adolescents Taekwondo Athletes Beep Test Aerobic Fitness Youth Sports Training Explosive Power Physical Conditioning VO? Max

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Machine learning and Artificial Intelligence is playing a huge role in today's world. From self-driving cars to medical fields, we can find them everywhere. The medical industry generates a huge amount of patient data which can be processed in a lot of ways. So, with the help of machine learning, we have created a Prediction System that can detect more than one disease. Many of the existing systems can predict disease at a time with lower accuracy. Lower accuracy can seriously put a patient's health in danger. We have considered three diseases for now that are Heart, Parkinson's, and Diabetes and in the future, many more diseases can be added. The user has to enter various parameters of the disease and the system would display the output whether he/she has the disease or not. This project can help a lot of people as one can monitor the persons' condition and take the necessary precautions thus increasing the life expectancy.

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 Keywords

Diabetes, Heart, Parkinson's, SVM, KNN, Logistic Regression, Disease Prediction.

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The Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) scheme launched by the Government of India in 2019 seeks to extend direct financial assistance to marginal and small farmers so that they become economically stable and agricultural productivity is enhanced. This paper discusses the awareness, perception, and effect of the PM-KISAN scheme on farmers in Tirupur district, particularly Avinashi and Palladam taluks. 60 respondents were chosen by convenience sampling, and data were gathered through a structured questionnaire. The study used percentage analysis, Likert scale, and Chi-square analysis in interpreting the data. It was found that although the scheme has immensely facilitated farming investment and family needs, delayed payments, non-digitability, and registration problems still exist. In addition to this, most farmers also wanted more financial support and other assistance like the subsidy on crop insurance and fertilizer. The research concludes that though the scheme is popular and viewed as positive, its performance can be strengthened by its extension to tenant farmers, ease of registration, and provision of more financial assistance. The study provides useful findings for policymakers to maximize the scheme's implementation and assist the economic prosperity of rural Indian farmers.

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PM-KISAN, Farmers' Perception in Financial Assistance and Agricultural Support

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The Online Food Ordering System streamlines the process of ordering meals from restaurants through a user-friendly platform. Customers can browse menus, place orders, make payments, and track deliveries in real time. This system enhances convenience, improves restaurant operations, and ensures a seamless dining experience.

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Food, Order, Track and Restaurant

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Creative Commons Attribution 4.0 and The Open Definition

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Counterfeit medicine poses a significant threat to public health, with the potential to cause harm and undermine trust in healthcare systems. Traditional methods of detecting counterfeit drugs often fall short due to the increasing sophistication of counterfeiters. This research paper is an approach to tackle the issue by employing deep learning algorithms for image classification. It leverages the power of Deep Learning (DL) algorithms to automatically learn relevant features from images of pharmaceutical products and accurately distinguish between genuine and counterfeit drugs. The experimental results demonstrate the effectiveness of the DL model in achieving high accuracy and robustness in identifying counterfeit drugs. It not only advances pharmaceutical security measures but also showcases the potential of DL functions in image classification for safeguarding public health and safety. By comparing with the DL algorithms, it specifies the accuracy of the counterfeit drugs.

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 Keywords

Counterfeit Medicine, Deep Learning (DL), Image Classification, Pharmaceutical Security

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Creative Commons Attribution 4.0 and The Open Definition

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Around the world, differences in race have severe implications for socioeconomic status and politics. This essay analyses the case of racial inequalities in India and the US and argues that India's reservation policy is more effective in mitigating social injustice. Discrimination based on caste is an age-old issue in India. The government has instituted a legally mandated quota system for the Scheduled Castes (SCs), Scheduled Tribes (STs) and Other Backward Classes (OBCs). Unlike American policy, India's system provides guaranteed quotas in politics, employment, and education which enhances representation and helps marginalized sections to move up the social ladder. A comparison analysis reveals that while India has a legally guaranteed proactive reservation policy, the United States has a passive strategy that is open to judicial review and capricious enforcement. Both systems have their flaws, yet India's has been more effective in narrowing the socio-economic gaps. The analysis shows that India's reservation system fills the gaps of social mobility and historical injustices more efficiently than other systems. While other countries including the US have some issues, they could learn a great deal from India regarding socially just legislation. It can gain insights from India's unique way of formulating socially equitable legislation. The United States might incorporate certain features of India's approach to implement more definitive changes in providing greater equity to racial minorities. This research contributes toward social justice issues by evaluating different mechanisms and their effectiveness in reducing systematic discrimination.

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 Keywords

social justice system

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Creative Commons Attribution 4.0 and The Open Definition