Volume 14 | Issue 4 |

 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.

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 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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 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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 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).

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 Keywords

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

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 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.

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 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

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Abstract Tourism has emerged as one of the fastest-growing sectors contributing significantly to regional economic development, particularly in hill regions. The district of Almora in Uttarakhand is widely known for its scenic beauty, cultural heritage and religious significance, attracting a large number of domestic and international tourists every year. The present study examines the economic, environmental and socio-cultural impacts of tourism on the local community in Almora district. The study is based on primary data collected from 200 host community members across five major tourist destinations Almora, Ranikhet, Dwarahat, Shetlakhet and Manila using structured questionnaires, field observations and interviews. The findings reveal that tourism has generated employment opportunities, improved infrastructure and increased income levels, thereby enhancing the standard of living of local residents. However, tourism development has also resulted in environmental challenges such as pollution, traffic congestion and pressure on natural resources. Furthermore, socio-cultural changes, including shifts in traditional lifestyles and cultural practices, have been observed. The study highlights the need for sustainable tourism planning to balance economic benefits with environmental conservation and cultural preservation in the region.

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 Keywords

Keywords: Tourism, Economic Impact, Environmental Impact, Socio-Cultural Impact, Conservation, Almora District

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Fatigue, distraction, and emotional instability are examples of human behavioral elements that continue to be a big global concern when it comes to road accidents. In order to provide real-time driver monitoring, this study suggests a Human Behavior-Based Driver Safety System (HB-DSS) that combines a Facial Emotion Recognition (FER) module with a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model. Drowsiness (Eye Aspect Ratio and PERCLOS), distraction (mobile usage and gaze deviation), emotional state (stress and anger), head position variation, and yawning frequency are among the behavioral indications that the system concurrently examines. This method incorporates multimodal behavioral analysis to improve detection accuracy and reliability, in contrast to conventional systems that concentrate on single features.

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 Keywords

Driver Safety, Deep Learning, CNN-LSTM, Emotion Recognition, Drowsiness Detection, Behavioral Analysis, IoT Alerts

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Waiting time dynamics are the key determinant of customer satisfaction of service systems. The presented research paper suggests and analyzes control charts (Six Sigma) to statistically measure the mean waiting time of the M/M/s multi-server queueing model. The suggested methodology combines the process capability ideas namely the capability index Cp with the traditional Statistical Process Control (SPC) tools to obtain tighter control limits than the traditional Shewhart 3? framework. A large comparison numerical experiment of fifteen configurations of arrival rates and three system parameterisations (differing ? and s) proves that the Six Sigma method always produces smaller control limit intervals (CLI), and hence, is more sensitive to detecting process variation. With the traffic conditions being 73 to 76 percent decrease of the CLI. Also, the influence of server capacity on the variability of waiting time is analysed systematically. The results are practical guidelines to the service system managers who want to implement real time statistical monitoring instruments based on the principles of Six Sigma.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Queueing theory; M/M/s model; Six Sigma; Statistical Process Control; Control charts; Waiting time; Process capability; Erlang-C; Service quality

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Creative Commons Attribution 4.0 and The Open Definition

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Digital Technological skills can change the behaviour of teachers and students towards education. We can use different type of technological skills to change education learning system and make better new communicated world. Digital technology is the study by creating and using available resources. Digital technology is the process of integrating technology into education in a positive manner. It promotes teachers and students to use technology in teaching learning process. Teachers need to develop the use of internet, digital literary information, use of social media, other apps and websites, citing useful sites. Teachers will have to use different presentation software, YouTube video and Blog information. Teachers will have to prepare about mobile technology, new technology and self- learning technology. Teachers will have to connect with E-mail networking, Free resources and citing sources, new apps and new educational websites, new teachers education and updated with new educational information. Digital devices like iPads and e-books offer lightweight and convenient alternatives to heavy notebooks and textbooks, increasing interest in research. This paper explores the necessity of digital technologies in education, highlighting their major applications and the challenges in education.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Technology, Types of Technology in Teacher Education, Technology skills, Teacher Education,

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Creative Commons Attribution 4.0 and The Open Definition

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This paper is about a web application that uses deep learning to detect and classify skin lesions. The application uses a kind of dataset called the HAM10000 dataset, which has a lot of pictures of skin lesions. The system uses something called transfer learning and a new way of combining parts of the system to get better results. The model is made up of two parts: one part is a -trained ResNet50 and the other part is a custom Convolutional Neural Network. These two parts work together to get an understanding of the skin lesions. The system is very good at classifying the skin lesions with a validation accuracy of 91.2% and an F1-score of 91.7%. The system is made to be used by dermatologists to help them diagnose skin lesions. It is a web application. It is easy to use and can be used in real-time. This work shows that deep learning can be very helpful in medical image analysis and it can be used to make a tool to help healthcare practitioners.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skin Cancer Detection, Deep Learning, Transfer Learning, Convolutional Neural Networks, Medical Image Analysis, HAM10000 Dataset

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Creative Commons Attribution 4.0 and The Open Definition