Volume 14 | Issue 4 |

 Abstract

The rapid rise in municipal solid waste is placing enormous pressure on urban infrastructure, recycling systems, and the natural environment. Proper waste separation at the source remains one of the most effective strategies for reducing landfill burden and improving recyclability, but manual sorting is slow, inconsistent, and hazardous for workers. This paper describes an automated garbage classification system built on a deep learning backbone, designed to sort waste in real time. The system uses MobileNetV2 with transfer learning to classify waste into twelve distinct categories. Training was supported by aggressive data augmentation and a two-phase learning process that first trains a custom classification head, then fine-tunes the deeper feature extraction layers. On a dataset of 15,515 images, the system reached a validation accuracy of 96.97%, which held up well across precision, recall, F1-score, and confusion matrix evaluations. The results confirm that lightweight deep learning architectures can approach the performance of far heavier models while remaining deployable on edge hardware, smart waste bins, and IoT-connected systems.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Garbage Classification, Deep Learning, MobileNetV2, Transfer Learning, Image Classification, Convolutional Neural Networks (CNN)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The importance of detecting plant diseases is paramount in improving crop production. Conventional methods for detecting plant diseases are, however, cumbersome and demand specialized knowledge to implement successfully. This research project is intended to create a new method for deep learning known as the Attention-Driven Vision Transformer Framework for Leaf Fungal Disease Detection. This approach incorporates a ViT (Vision Transformer) model augmented with attention mechanisms that facilitate effective extraction of global and local features of the images. During the training phase of the model, publicly available databases related to different plant diseases are used so that the system can detect diverse forms of fungal infections. Image processing operations include normalization, augmentation, and resizing, which enable the model to improve its generalization ability. Also, the use of the attention mechanism will allow the system to identify critical features of the leaf image. Results from tests performed on the proposed method suggest that it offers excellent performance in terms of accuracy and precision in identifying various fungal infections. Moreover, the system is robust to varying background illumination conditions. Therefore, it may be applied to automate fungal infection identification using both mobile and web applications. In general, this research shows how powerful transformers can be when applied in agriculture, providing an efficient and intelligent way of detecting diseases on plants at the early stages of their appearance.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Vision Transformer, Attention Mechanism, Deep Learning, Computer Vision, Precision Agriculture

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Romanticism, individualism, emotional depth, nationalism

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Food insecurity and food waste are two paradoxical crises that co-exist in every modern city. Tonnes of edible surplus food are discarded daily by restaurants, households, and institutions while millions of people remain chronically undernourished. This paper presents the Smart Food Donation and Surplus Redistribution System -- a PHP and MySQL web application that digitizes the full donation lifecycle and connects food donors directly with NGOs.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Food Donation, Surplus Redistribution, NGO Coordination, PHP, MySQL, Web Application, Role-Based Access Control, Delivery Tracking, Geo-Location, Leaflet.js, Food Waste Management, Chart.js

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Jal Jeevan Mission (JJM) is the flagship program of Government of India under the Ministry of Jal Shakti, aims to ensure Functional Household Tap Connections (FHTCs) to all rural households and provide safe, adequate, and regular drinking water. The present study is conducted in the village- Sonthi, District - Bilaspur, Chhattisgarh to analysis the impact of the Jal Jeevan Mission on the daily activities and socio-economic engagement of rural women in the village, and health outcomes of rural households in the village. The study's conclusions illustrate that although the program has greatly lessened the tedious task of collecting water, enhanced hygiene standards, and given more time for home and livelihood activities, a number of issues still exist. Problems including inconsistent supply, poor tank cleaning, low water pressure, and ongoing reliance on conventional sources draw attention to deficiencies in infrastructure upkeep and service provision. Despite these drawbacks, JJM has improved socio-economic activities, health knowledge, and community involvement, especially for women who have historically been responsible for water collecting.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Word : Jal Jeevan Mission (JJM), Functional Household Tap Connections (FHTCs), Swachh Bharat Mission (SBM), Village Water and Sanitation Committees (VWSCs)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Supervisory Control and Data Acquisition (SCADA) water-treatment plants manage chemical dosing, pH and chlorine levels, and pumping operations, but increasing connectivity has exposed them to cyber risks such as unauthorized access, insider tampering, falsified sensor data, and malicious PLC commands. These attacks can silently alter treatment parameters and disrupt operations while appearing normal. Traditional SCADA security methods based on thresholds and signatures often miss slow, evolving attacks and still expose raw operational data, creating both security and privacy risks. This project proposes an intrusion detection framework that leverages a Temporal Convolutional Network (TCN) autoencoder to learn normal operating patterns across SCADA signals that are commonly targeted by Cyber-Physical Process Manipulation Attacks, including chemical dosing, pH and chlorine behavior, pump and tank dynamics, network activity, user interactions, and PLC control operations. The system learns normal plant behavior over time and automatically detects unusual changes that may indicate an attack, without needing predefined attack rules. Believable sensor readings and PLC responses are generated so that malicious commands only affect the virtual system, while the actual plant remains fully protected. This detection-then-protection strategy ensures service continuity, prevents physical damage, enables attacker behavior analysis, and significantly reduces operational risk in modern water-treatment facilities.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cyber-Physical Systems (CPS),SCADA Security,Water Treatment Plant Monitoring,Intrusion Detection Systems (IDS),Anomaly Detection, Deception Technology ,Honeypots,Industrial Control Systems (ICS),Network Security,Critical Infrastructure Protection,Machine Learning in Cybersecurity, Attack Mitigation Strategies,Real-Time Monitoring,Threat Intelligence

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an adaptive neuro-symbolic multi-agent medical intelligence architecture designed to enable trustworthy clinical reasoning under dynamically evolving patient conditions. The proposed framework integrates temporal clinical drift simulation, adversarial diagnostic validation, retrieval-grounded medical reasoning, and uncertainty-aware escalation mechanisms into a unified, clinically coherent pipeline. Unlike conventional static medical chatbots, the system continuously adapts its diagnostic reasoning as patient symptoms evolve over time. Multiple autonomous agents collaboratively generate, critique, and validate diagnoses using evidence retrieved from trusted medical knowledge repositories. Comprehensive experimental evaluation demonstrates marked improvements across diagnostic explainability, hallucination suppression, emergency risk detection, and adversarial robustness. The proposed architecture establishes a robust foundation for clinically adaptive, explainable, and safety-conscious healthcare AI ecosystems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Generative AI; Neuro-Symbolic AI; Multi-Agent Medical Reasoning; Clinical Intelligence Systems; Temporal Disease Simulation; Explainable Healthcare AI; Adversarial Diagnostic Validation; Retrieval-Augmented Generation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

War is considered as an extreme form of socio-economic, political religious and national conflicts between states or geographical boundaries. The reasons for the war is vary from one situation to other but it has many consequences on social, political, economic and ecological life of people. Throughout the history of mankind war has been considered as very common phenomenon of the society. War may take place because of two reasons one is economic another one non-economic. Later on 1970's the entire globe is commonly accepted concept of sustainable development which regarded as "meeting the needs of present generation without compromising needs of the future generation. In order to achieve sustainable development many countries have adopted many strategies and policies of their own. In India we adopted the concept of sustainable development policy in the 1987 and we have many policies and strategies to achieve this concept. But still so many external factors like climate change, environmental pollution, wars will definitely have the deep impact on the overall development of the country. In this article let us discuss the present sustainable development strategy in India and also impact of war.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

sustainable development, war impact, strategy

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The impact of social media on children and students is a growing concern, with research highlighting negative effects on academic performance, mental health, and well-being, including cyberbullying, exposure to inappropriate content, and addiction (B?la?-Baconschi & Purice, 2023), (D'Lima & Higgins, 2021, pp. 320-338), (Moreno, 2016), (Young & Oza, 2021, pp. 373-379), (Astorri et al., 2022). While general-purpose platforms offer social connection, they often present distractions detrimental to academic success (Dacka, 2023). This research paper introduces CampusConnect, a specialized social media application designed to support students' academic and career needs while mitigating the risks associated with traditional social media. CampusConnect fosters a focused environment for academic collaboration and knowledge sharing, offering features such as group project tools, resource sharing, event scheduling, secure messaging, and job/internship postings. Developed using Python and PHP with a Flask backend and MySQL database, the platform incorporates an iterative development process, including requirement gathering, design, development, testing, and deployment. Initial findings from implementation and user feedback indicate improved academic focus, increased collaboration, and enhanced career development opportunities. The paper analyzes CampusConnect's effectiveness in mitigating the negative impacts of general social media platforms, while suggesting future enhancements such as live video integration, personalized learning features, and gamification to further optimize student engagement and academic outcomes. The study contributes to the ongoing discussion on responsible technology use and the creation of supportive digital learning environments for students (Bopp & Stellefson, 2020), (Dacka, 2023).

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

The Impact of Social Media on Children: Challenges and Solutions Through a Specialized Application

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Corporate Social Responsibility (CSR) serves as a fundamental element which determines how contemporary consumers interact with products and companies. This research study examines how Corporate Social Responsibility (CSR) practices affect consumer purchasing behavior within the Indian e-commerce industry and the cosmetics industry. The researchers conducted quantitative research by collecting data from 101 participants who completed a standardized questionnaire. The research demonstrates that CSR transparency together with active participation by companies leads to higher levels of consumer trust and brand loyalty which results in increased purchase behavior. Consumers display an attitude-behavior gap because they value ethical and sustainable practices but refuse to spend extra money on those practices. Financial challenges stop people from making ethical purchases although their understanding of CSR raises with their age and education and income levels. The research discovers that Corporate Social Responsibility (CSR) improves brand reputation and customer trust but its effect on actual purchasing behavior depends on companies demonstrating authentic information together with full disclosure.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Corporate Social Responsibility (CSR), Consumer Behaviour, Brand Loyalty, Transparency, Ethical Practices, Purchase Intention, Attitude-Behaviour Gap, E-commerce, Cosmetics Industry, India.

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Creative Commons Attribution 4.0 and The Open Definition