Volume 14 | Issue 6

 Abstract

Increased population and rampant urbanization has caused a tremendous amount and complexity in solid waste which poses a big problem to the traditional waste management structures. Conventional means of waste collection process is mostly manual, time-stated and inefficient and this geometrical overflow of bins, inadequate separation of waste, hiked up cost of operation and environmental pollution. In order to overcome these restrictions, in this paper, there was a review and conceptual implementation of a Smart Waste Management System with Raspberry Pi and IoT-based monitoring systems incorporated and coupled with enhanced waste sorting and real time alerts.

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 Keywords

A Review on IoT-Driven Intelligent Waste Monitoring System with Raspberry Pi Integration

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The growing agricultural field demands, integration of modern techniques to improve product quality. The artificial intelligence offenly called as AI found its applications in every field nowadays. The effective use of such technique can lead to increase output. The agricultural field experiences several challenges like crop prediction, crop health monitoring, and weather forecasting, disease prediction for plants and payment gateway systems for effective farming. The implementation of AI in agricultural field offer better flexibility, better stability, better performance and cost effectiveness. This paper highlighted exhaustive review of use of the AI techniques in agricultural field by focusing on higher productivity and economical considerations.

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Crop prediction, Crop health monitoring, Plant disease prediction, Weather forecasting

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The existing conventional financial advice, based on traditional models, is not only liable to various biases but also not capable of dealing with the high degree of volatility of the Indian Market. The aim and objective of conducting this study are to bridge the gap between the existing shortcomings through developing an innovative web-based AI-Driven Portfolio Management & Advisory System for adaptive and complaint financial advice on each and every financial product listed on the exchanges of India, such as stocks, mutual funds, bonds, etc. The approach undertaken involves using a powerful multi-layered mechanism, such as reinforcement learning algorithms for adaptive portfolio allocation, NLP algorithms for incorporation of market sentiments, quant-based algorithms such as Monte Carlo and quant for risk analysis.

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 Keywords

AI Advisory, Black-Litterman, EDI, India Market, Monte Carlo Simulation, Portfolio Management, Reinforcement Learning, SEBI Compliance

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Mental health challenges such as stress, anxiety, and emotional imbalance are increasingly affecting students, youths, and working professionals in today's fast-paced society. Social stigma, lack of awareness, and limited access to professional support often prevent individuals from seeking timely help. This paper presents EmoCare, an AI-based web platform designed to promote emotional well-being through real-time emotion detection and personalized support. EmoCare utilizes Natural Language Processing (NLP) and Sentiment Analysis to analyze user text and identify emotional states such as positivity, negativity, stress, and anxiety. Based on the detected emotions, the system generates tailored responses in the form of motivational quotes, relaxation techniques, and supportive messages. Developed using React.js for the frontend, Node.js for the backend, and MongoDB for data storage, the platform ensures a secure, user-friendly, and privacy-focused environment. EmoCare provides a free and stigma-free digital space for emotional expression, aligning with global mental health initiatives by the World Health Organization (WHO) and Google. The proposed system demonstrates how artificial intelligence can effectively contribute to accessible mental health support and digital well-being.

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 Keywords

Mental Health, Sentiment Analysis, Emotional Support, AI Wellness Platform, Well-being

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This paper addresses the issue of admission status ambiguity during the centralized admission process. It reveals the process of deploying a unique way of adding transparency to the system which will benefit the prospective students, parents, admission team and even the management officials. This paper shows an innovative method of displaying the admission allocation and actually admitted students on the Institute website. In Maharashtra, the higher education Institutes admit students through Centralized Admission Process which is conducted by Government of Maharashtra. On the MH CET admission website, the list of allotted students to the Institute is available. There are few admission rounds conducted during the whole process where students get the chance to take admission in the allotted college or to opt for betterment. Some of the seats are available for Institute Level Admission. For these seats also the merit list needs to be displayed based on which the seats in each branch are filled. During this process, Parents and students have to visit various institutes for checking the seat availability in the institutes of their choice. The admission team in every college also have to face certain challenges such as completing the student registration, fees payment etc. including other formalities. This paper attempts to create a web portal which works as Admission Indicator for a particular institute. It displays a number of seats allotted for every branch. It also gives a real time tracking to the students and parents to check how many seats are filled and the count of vacant seats. This Indicator display will help all stakeholders in decision making thereby reducing ambiguity and confusion.

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 Keywords

Real Time Admission Count Indicator, Gradio, GUI, Python.

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The rapid growth of counterfeit medicines presents a significant challenge to public health, supply chain integrity, and regulatory compliance in global healthcare systems. Conventional centralized supply chain management (SCM) systems suffer from limited transparency, susceptibility to data tampering, and single points of failure. To address these issues, this paper proposes MediLedger, a blockchain-based medicine traceability framework that ensures end-to-end visibility, authenticity, and security across pharmaceutical supply chains. The system utilizes blockchain's immutable distributed ledger, cryptographic hash functions, smart contracts, and QR-code-based verification to prevent the circulation of counterfeit drugs. Each medicine unit is assigned a unique digital identity recorded on the blockchain, enabling real-time verification by manufacturers, distributors, regulators, and consumers. A custom validation and consensus mechanism is employed to ensure data integrity, tamper resistance, and automatic recovery from malicious or faulty nodes. Experimental results demonstrate that MediLedger improves traceability, reduces verification time, and enhances trust among all stakeholders in the pharmaceutical ecosystem.

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 Keywords

Blockchain, Counterfeit Product Detection, Supply Chain Management, QR Code Authentication, Custom Blockchain, SHA-256.

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 Abstract

Counterfeit products are a major problem in modern supply chains and cause financial loss, brand damage, and safety risks to consumers. Traditional centralized systems are not secure and can be easily modified or attacked. To overcome these issues, this paper proposes a custom blockchain-based decentralized system for anti-counterfeit product authentication in IoT-integrated supply chains. Each product is registered by the supplier and assigned a unique QR code. Product information is secured using SHA-256 hash generation and stored in a custom blockchain network. The company module verifies product movement, while end users can scan QR codes to check product authenticity in real time. If any mismatch is found, the system alerts users about possible counterfeit products. The proposed system improves transparency, data security, and trust among supply chain participants and provides an effective solution for counterfeit detection.

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 Keywords

Blockchain, Counterfeit Product Detection, Supply Chain Management, QR Code Authentication, Custom Blockchain, SHA-256.

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 Abstract

Automated Exoplanet Detection Using Artificial Intelligence and Machine Learning

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Automated Exoplanet Detection Using Artificial Intelligence and Machine Learning

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Education in the twenty-first century is undergoing rapid transformation due to advancements in information and communication technology. Traditional methods of teaching are increasingly supplemented with digital tools and online resources to create more effective and engaging learning experiences. Among the various innovative instructional approaches, blended learning has emerged as one of the most widely adopted methods in schools and higher educational institutions. Motivation for learning is a crucial factor influencing students' academic success. It refers to the internal and external forces that stimulate students' interest, enthusiasm, and willingness to participate in learning activities and achieve educational goals. Students who are highly motivated tend to demonstrate greater attention, persistence, effort, and commitment to their studies. The present study investigated the effect of the Blended Learning Approach on motivation for learning among elementary school students. A pre-test-post-test control-group experimental design was employed to examine the effectiveness of blended learning compared with conventional face-to-face teaching. The study was conducted in a purposively selected private school in Sirsa district, Haryana, India. A total of 120 eighth-grade students participated in the study and were randomly assigned to an Experimental Group (n = 60) and a Control Group (n = 60). The purposive sampling technique was adopted to select participants with similar socio-economic backgrounds, academic curriculum, and school facilities. The Experimental Group received instruction through a Blended Learning Approach, while the Control Group was taught using the Traditional Teaching Approach. Motivation for Learning was measured using a self-developed Motivation for Learning Scale. The findings revealed that students exposed to blended learning demonstrated significantly higher motivation to learn than those taught through traditional methods. The study concludes that blended learning is an effective pedagogical strategy for enhancing learners' motivation at the elementary school stage.

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Blended Learning, Motivation for Learning, Experimental Study, Elementary Education, Social Science, Eighth-Grade Students.

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Juvenile delinquency in India is often misunderstood as an issue of individual wrongdoing, but a closer examination shows that it is largely shaped by social surroundings. Edwin H. Sutherland's Differential Association Theory offers a useful framework to understand how criminal behaviour is learned through interaction with family, peers, and environment. This paper examines the role of Juvenile Justice Boards (JJBs) in addressing such learned behaviour within the framework of the Juvenile Justice (Care and Protection of Children) Act, 2015. It also incorporates relevant provisions of the Bharatiya Nyaya Sanhita, 2023 (BNS) and Bharatiya Nagarik Suraksha Sanhita, 2023 (BNSS) , which now govern substantive and procedural criminal law in India. Through analysis of landmark judgments such as Sheela Barse v. Union of India , Salil Bali v. Union of India, and Pratap Singh v. State of Jharkhand , the paper highlights the judiciary's consistent emphasis on rehabilitation over punishment. The paper argues that JJBs are structurally designed to address learned criminal behaviour, but their effectiveness is limited by institutional weaknesses, lack of trained personnel, and social stigma. It concludes by suggesting reforms to strengthen their role in breaking cycles of criminal learning.

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Juvenile delinquency, JJB'S, NCRB, Differential Association

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The Indian software industry has witnessed rapid transformation with the widespread adoption of Agile methodologies aimed at improving flexibility, speed, and customer-centric delivery. However, Agile environments continue to face challenges related to real-time monitoring, predictive decision-making, and efficient resource utilization. In this context, the concept of a Digital Twin - a dynamic, data-driven virtual representation of a system - has emerged as a promising approach for enhancing Agile project management.

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Digital Twin Agile Software Development, Indian IT Industry, Project Monitoring, Predictive Analytics, Industry 4.0

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Storyboarding is a powerful visual communication technique that bridges ideas, narratives, and execution across multiple disciplines, including filmmaking, animation, advertising, education, multimedia, user experience (UX), and corporate communication. It enables creators to transform abstract concepts into sequential visual representations, thereby improving clarity, collaboration, and decision-making. This paper examines the significance of storyboarding as a communication tool through theoretical discussion and a case study based on film production. The study explores how storyboarding enhances communication among directors, cinematographers, editors, production designers, actors, and technical crews while minimizing production errors and improving creative outcomes. The findings suggest that storyboarding is not merely a planning instrument but an essential communication medium that integrates visual thinking, collaborative design, and narrative coherence. The paper concludes that the increasing adoption of digital technologies and artificial intelligence has expanded the role of storyboarding beyond cinema into education, healthcare, business, and digital media communication

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Storyboarding, Visual Communication, Film Production, Communication Design, Sequential Art, Multimedia, Pre-production, Visual Storytelling

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CERVICAL CANCER IS A MAJOR PUBLIC HEALTH CONCERN WORLDWIDE, PRIMARILY CAUSED BY HUMAN PAPILLOMAVIRUS (HPV) INFECTION. THIS STUDY ASSESSED THE EFFECTIVENESS OF A STRUCTURED TEACHING PROGRAMME (STP) ON KNOWLEDGE REGARDING THE IMPORTANCE OF HPV VACCINATION AMONG LATE ADOLESCENT GIRLS IN SELECTED HIGHER SECONDARY SCHOOLS OF MEHSANA DISTRICT. USING A QUANTITATIVE ONE-GROUP PRE-TEST AND POST-TEST DESIGN, 60 PARTICIPANTS WERE SELECTED THROUGH PURPOSIVE SAMPLING. THE FINDINGS SHOWED A SIGNIFICANT IMPROVEMENT IN KNOWLEDGE SCORES AFTER THE INTERVENTION, DEMONSTRATING THE EFFECTIVENESS OF THE STP. THE STUDY CONCLUDED THAT STRUCTURED EDUCATIONAL PROGRAMMES ARE EFFECTIVE IN INCREASING AWARENESS AND KNOWLEDGE ABOUT HPV VACCINATION AND CERVICAL CANCER PREVENTION AMONG ADOLESCENT GIRLS.

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A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING IMPORTANCE OF HPV VACCINE FOR PREVENTION OF CERVICAL CANCER AMONG LATE ADOLESCENT GIRLS OF SELECTED HIGHER SECONDARY SCHOOLS OF MEHSANA DISTRICT

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 Keywords

Chronotype, Morningness-Eveningness Questionnaire, Dietary Diversity Score, Indian Diabetes Risk Score, Circadian Rhythm, MNC Employees, Type 2 Diabetes

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For years in Western culture, sign language has been an ancient visual language and method of communicating. It consists of the use of traditional signs, gestures or a manual alphabet using your hands to assist with signing. The Machine Learning-based sign language identification system is a project that allows someone who has a disability to communicate and provide an output from sign language into text or audio; therefore, the machine can read the signs, and the machine will know what the user is trying to say even if the user has no knowledge/sign language. To provide better services to disabled individuals is the purpose of this project through advanced technology. The purpose of Sign Language is to communicate the user's need for information. The Project will capture sign language using specific technologies and will provide an audio notification of its result on the website. The Project is developed using Machine Learning technology and other advanced technologies. The purpose of the Project is to use hand sensors used to detect sign/capture sign as input to identify the needs of the disabled person. The purpose of the project is to provide a path for helping the world through humans.

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 Keywords

Gesture navigation, TensorFlow, Keras, OpenCV-Python, matplotlib, pandas, numpy, MediaPipe, seaborn, Flask, scikit-learn, pyttsx3, YOLOv5.

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Citric acid has got several other applications in various fields. Currently, the global production of citric acid is estimated to be around 7,36,000 tones/year and the entire production is carried out by fermentation. In Brazil, almost the entire demand of citric acid is met through imports. There is constant increase (3.5-4%) each year in its consumption, showing the need of finding new alternatives for its manufacture. Citric acid is produced by mycological fermentation on an industrial scale using crude sugar solutions such as molasses and strains of Aspergillus niger. In the present study Plackett burman design was used to evaluate the components of the media affecting the production of citri acid using Aspergillus niger. Two major components NaNo3 and KCL was found to be most effective giving maximum yield and the citric acid was crystalized in the laboratory.

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Citric acid, plackett Burman design, sodium nitrate, potassium chloride

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The unprecedented international success of Liu Cixin's ???? Three-Body trilogy -- culminating in the 2015 Hugo Award and subsequent global translations, screen adaptations, and the viral Netflix series of 2024 -- has repositioned Chinese science fiction (Chinese SF) as a significant cultural and geopolitical phenomenon. This paper examines three interlocking dimensions of that phenomenon: the historical trajectory of Chinese SF as a literary genre shaped by recurring cycles of promotion and suppression; its persistent instrumentalisation as a pedagogical tool for the dissemination of scientific values and creative thinking; and its increasingly explicit function as a vehicle of state-endorsed cultural soft power in China's engagement with the world. Drawing on the Callahan (2023) framework of "pessoptimism," neo-socialism, and tianxia, as well as on You Wu's (2020) analysis of translation and global mediation, and on the critical reception of Liu Cixin's work in both Chinese and international scholarship, this paper argues that the relationship between Chinese SF and Chinese power is neither simple nor singular. Chinese SF simultaneously registers anxieties and aspirations that the state cannot fully control, transmits a cosmological imagination that transcends national borders, and serves as a vehicle through which the Chinese state projects its vision of technological modernity. The paradox, this paper contends, is precisely the source of Chinese SF's global resonance.

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 Keywords

Chinese Science Fiction; Liu Cixin; Three-Body Problem; Soft Power; Cultural Diplomacy; Hugo Award; Translation; Global Reception; Chinese Dream; Tianxia

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Pornography in India represents a complex moral and ethical dilemma situated at the intersection of law, culture, technology, and individual freedom. As one of the world's fastest-growing digital markets, India has witnessed unprecedented access to online pornographic content following the expansion of affordable internet services. Despite statutory restrictions under the Information Technology Act, 2000, and periodic governmental bans on adult websites, consumption remains widespread, raising critical questions about enforceability, personal liberty, and societal values. The debate surrounding pornography in India is deeply influenced by traditional norms, religious beliefs, and evolving global perspectives on sexuality. On one hand, critics argue that pornography contributes to the objectification of women, reinforces gender stereotypes, promotes unrealistic expectations of intimacy, and may correlate with sexual violence or exploitation. Concerns regarding child pornography, trafficking, and non-consensual content further intensify the ethical stakes. Advocacy groups and policymakers often frame pornography as a threat to public morality and social stability, emphasizing the need for stricter regulation and digital monitoring. On the other hand, proponents contend that adult pornography consumption, when consensual and legally regulated, falls within the ambit of personal autonomy and freedom of expression. They argue that censorship may infringe upon constitutional rights, particularly under Article 19 of the Indian Constitution, and that moral policing cannot substitute comprehensive sex education and gender sensitization. The tension between privacy, state control, and community standards thus becomes central to the discourse. Moreover, the rapid proliferation of smartphones and social media platforms has blurred the boundaries between private and public domains, complicating legal enforcement and ethical accountability. The emergence of user-generated content platforms further challenges conventional regulatory frameworks. Ultimately, pornography in India encapsulates a broader societal struggle between tradition and modernity, regulation and freedom, morality and rights. Addressing this issue requires a nuanced approach that balances legal safeguards against exploitation with respect for individual liberties, while fostering informed dialogue, digital literacy, and ethical awareness within a transforming socio-cultural landscape.

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 Keywords

Pornography, Ethics, Morality, Digital Regulation, Freedom of Expression

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The rapid proliferation of Internet of Things (IoT) devices, real-time applications and 5G networks have resulted in the growing network congestion, latency, and bandwidth utilization in the centralized cloud computing systems. One promising paradigm that decentralizes computation by pushing processing power closer to data sources is edge computing. In this paper, we propose an effective framework of edge computing for network optimization in distributed systems. The framework includes latency-aware routing, dynamic resource allocation and intelligent job offloading to improve the network performance. The proposed model aims at improving Quality of Service (QoS), reducing latency, and minimizing bandwidth consumption. Analytical tests indicate that the framework performs better than traditional cloud-based systems in terms of performance and latency. The architecture is scalable to the needs of next generation communication networks, smart cities and industrial internet of things (IoT).

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Internet of Things (IoT Quality of Service (QoS), Multi-access Edge Computing (MEC).

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 Abstract

The study was conducted to assess the knowledge regarding basic women's rights among the Women and to determine the association between knowledge level and demographic variables among 235 participants. A descriptive research design was adopted. Findings revealed that 54.9% participants had good knowledge, 30.2% had average knowledge and 14.9% had poor knowledge. No statistically significant association was found between knowledge level and selected demographic variables.

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Women's rights, knowledge, variables, Women.

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Creative Commons Attribution 4.0 and The Open Definition