Category Archives: Uncategorized

Authors: Hachimenum Nyebuchi Amadi, Biobele A. Wokoma, Victor Nneji Chikwendu, Richeal Chinaeche Ijeoma

Abstract: A micro-grid is a localized energy system that typically operates as part of a larger, wide-area synchronous grid but can function independently when necessary. It comprises energy generators, loads, storage units, and control systems, all highly integrated and manageable. This study presents the design and implementation of a 60,000-watt solar photovoltaic (PV) microgrid incorporating an advanced fault detection and localization mechanism, aimed at addressing the limitations of conventional reactive fault systems. These traditional systems often respond only after fault currents surpass the tolerance thresholds of grid components, leading to reduced efficiency, equipment damage, or total system failure. To mitigate these issues, a DC micro-grid consisting of six solar PV arrays was modeled using Proteus 8.15 Professional and Siemens TIA Portal. Each array comprised 32 units of 400W, 12V panels arranged in an 8×4 configuration, delivering 72V per array. The PV arrays were individually connected through dedicated contactors (MCB1–6). Fault detection and isolation were achieved using smart electronics, specifically Arduino Nano microcontrollers integrated with WCS1600 current sensors capable of sensing up to 500A. The system efficiently identified and isolated faults occurring within any array. During testing, no faults were flagged for current values of 72.33A, 90.42A, 123.69A, 117.15A, 172.02A, and 199.09A, as they remained within the safe 200A threshold. However, overcurrent values recorded at PV arrays 3, 4, 5, and 6 (235.09A, 307.43A, 412.72A, and 209.09A, respectively) due to simulation of fault (short circuit, load-related faults, battery system faults, DC bus fault or converter and distribution fault) were promptly detected, and the affected arrays were disconnected to protect the system. Compared to previous research, this approach leveraging a hybrid of Arduino Microcontroller and Siemens S7-1200 PLC (CPU1214CDC/DC/DC) demonstrated improved efficiency and reliability in proactive fault detection and localization. Ultimately, the study successfully developed a programmable, feedback-enabled microgrid system capable of anticipating and mitigating faults before component tolerance limits are breached.

DOI: https://doi.org/10.5281/zenodo.17587332

 

Published by: vikaspatanker

Authors: M. Kumaraguru, B. Bhuvaneswari

Abstract: Cloud gaming is a rapidly evolving domain that provides seamless access to immersive, high-quality gaming experiences. Despite its advantages, reducing latency remains a significant hurdle, especially under varying network conditions. This study introduces an innovative solution that leverages artificial intelligence (AI) to tackle these issues. The proposed system integrates AI techniques to enhance multiple facets of cloud gaming, such as video compression, traffic routing, resource distribution, and prediction of user interactions. Machine learning algorithms continuously fine-tune streaming configurations in response to live network metrics and individual user preferences, thereby lowering latency and boosting visual fidelity. Furthermore, reinforcement learning is employed to optimize backend resource management, improving both scalability and operational efficiency. The use of AI-powered predictive analytics facilitates customized gameplay by forecasting user behavior and dynamically adjusting game mechanics. Through behavioral analysis and preference modeling, the system personalizes content delivery, difficulty settings, and in-game support.

Published by: vikaspatanker

Authors: Mrs. Khatal Kavita, Miss Akanksha Vishwasrao, Miss Nikita Shinde, Miss Apeksha Vishwasrao

Abstract: Managing daily expenses is an important task for people who want to keep track of their finances. The Expense Tracker Web Application is built to make it easier to record, manage, and understand personal financial data. The backend runs on Python Flask, and the front end uses HTML, CSS, and JavaScript to create a user-friendly and responsive interface. The backend supports basic functions like adding, editing, deleting, and viewing expense records, while also ensuring that the data is valid and accurate. It stores information securely in a SQLite database, which allows users to keep and access their financial records easily. The application uses Pandas for handling data and Matplotlib or Plotly for creating visual graphs. This lets users see their spending patterns by category and over time through pie charts and bar or line charts. Additionally, the project focuses on security by cleaning up inputs, checking user data, and optimizing queries for better performance. The system helps users manage daily expenses by organizing data and providing login protection and visual insights to support effective tracking and analysis of spending..

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Authors: Prof. Sangeeta Alagi, , Priti Jagdale, Swati More, Vaibhav Prasad

Abstract: The rapid advancement of deep learning technologies has enabled the creation of highly realistic synthetic media, commonly known as deepfakes. These manipulated videos pose serious threats to information integrity, personal privacy, national security, and public trust. This comprehensive literature survey examines the state-of-the-art approaches in deepfake detection, with particular emphasis on methods that combine Convolutional Neural Networks (CNNs) for spatial feature extraction with temporal analysis techniques. We systematically review detection methodologies, benchmark datasets, evaluation metrics, current challenges, and emerging research directions. This survey synthesizes findings from over 50 research papers published between 2018 and 2024, providing insights into the evolution of detection techniques and the ongoing arms race between deepfake generation and detection technologies.

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Authors: Aakanksha Raghunath Chaudhari, Sharmistha Sujit Sarkar

Abstract: With the rapid growth of digital communication and online services, network security has become a primary concern for organizations and individuals. Traditional intrusion detection systems (IDS) rely heavily on predefined signatures, making them ineffective against zero-day attacks and unknown threats. To overcome these limitations, AI-based anomaly detection systems have emerged as a powerful approach for identifying unusual patterns in network traffic that may indicate malicious activity. This research introduces NetGuard, an intelligent system that leverages machine learning and deep learning techniques to detect anomalies in network traffic. The system provides real-time threat detection, reduces false alarms, and enhances network resilience against evolving cyber threats.

DOI: https://doi.org/10.5281/zenodo.17570618

 

Published by: vikaspatanker

Authors: Aryan Bhatt, Aryan Verma

Abstract: Artificial Intelligence (AI) methods, specifically Large Language Models (LLMs), are increasingly being employed by developers and students to produce source code. Though helpful, such AI-produced code is problematic in terms of plagiarism, originality, and academic honesty. Hence, differentiating between code written by humans and code generated by AI has become vital for the prevention of plagiarism. This article provides an empirical evaluation of current AI detection tools to determine how well they can detect AI-generated code in educational and coding environments. The findings indicate that most of the tools are ineffective and not generalizable enough to be useful for detecting plagiarism. In order to deal with this problem, we suggest a number of solutions, such as fine-tuning LLMs and machine learning-based classification based on static code metrics and code embeddings obtained from Abstract Syntax Trees (AST). Our top-performing model outperforms current detectors (e.g., GPTSniffer) and gets an F1 score of 82.55. In addition to that, we carry out an ablation study to study the contribution of different source code features to detection accuracy.

DOI:

 

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Authors: Morziul Haque, 2Mohammed Shaik Fahad, Ansh Goyal, Bhagyashree .N. Singh, Priyanka Sahu, Dr. Basavaraj Neelur, Deepak Kumar Punna, Lavanya Dahiya

Abstract: In 1977, NASA launched two identical spacecrafts known as Voyager 1 and 2, which is the most important ambassador of mankind to the universe. Voyager as a project which was originally intended to be a planetary exploration mission, transformed into a historic project which incorporated both scientific, engineering and humanistic goals. Throughout a period of close to five decades, the Voyagers have unrelentingly provided deliveries in terms of firsts in regard to the outer planets, the heliosphere and the interstellar medium. They are nowadays the well-known stepping-stones of human inquisitiveness and venture beyond the solar frontier. The theory discussed in this paper is a literature review about the current scholarly debate around the issue of the scientific success, the engineering strength, and cultural meaning of the Voyager mission in terms of the 21st century digital era. It also calls attention to modern reinterpretations of Voyager data with these aspects may involve the use of artificial intelligence (AI) and astrophysical modeling, as well as the continued debate surrounding the following, interstellar communication and preservation. Through the lens of both the empirical heritage and with an emphasis on the philosophical influence of the Voyager program, this review explores the mission against the background of 21st century space exploration and human self-understanding.

DOI: https://doi.org/10.5281/zenodo.17568692

 

Published by: vikaspatanker

Authors: Garima, Ravi Kumar Rana, Niranjan Singh Rathee

Abstract: In the current research work a new Schiff base (2,2'-((1E,1'E)-((4-methyl-1,2-phenylene)bis(azaneylylidene))bis(methaneylylidene))bis(4-bromophenol) (H2L) and its metal complexes were prepared using condensation reaction of 3,4-diaminotoluene and 5-bromo salicylaldehyde. The Schiff base was further coordinated with Co2+, Ni2+, Cu2+& Zn2+ metal ions to synthesize its 1:1 metal complexes. All the synthesized compounds were examined using a variety of characterisation methods, including proton-NMR, electronic, mass, ESR, IR spectroscopy and TGA. FT-IR and NMR spectral data elucidate that the metal ions are coordinated with the tetradentate ligand through 2-N (imine) and 2-O (hydroxyl) atoms. All of the metal complexes were assumed to have an octahedral geometry based on the UV-Visible spectra. Antibacterial & antifungal activity of synthesized product was tested. The results demonstrated that all the sample exhibited considerable antimicrobial properties.

DOI: https://doi.org/10.5281/zenodo.17557767

 

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Authors: Praniti Gijare, Sneha Kunnummal, Suhani Heblikar, Harsh Sakhare, Rushabh Parab, Reshma Sonar

Abstract: Phishing attacks targeting college students have surged by 224% in the education sector during 2024, In recent months, attacks aimed at stealing login details have exploded in volume, with credential-related phishing growing at an unprecedented rate and now representing the fastest-rising threat faced by campus communities. Methods that rely mainly on lectures or passive training have not made a substantial impact on how well students identify or avoid phishing threats, leaving many learners at risk despite completing such programs in reducing phishing susceptibility, with studies revealing minimal behavioural change despite widespread implementation. This research investigates whether interactive coding simulations using Python-based phishing detection exercises can significantly improve college students' ability to identify and avoid phishing attacks compared to conventional lecture-based training. A quasi-experimental pre-test post-test design employed 90 undergraduate students across three groups: interactive simulation training (n=30), traditional lecture-based training (n=30), and control group (n=30). The interactive group developed basic Python scripts to detect phishing characteristics including suspicious URLs, sender anomalies, and social engineering tactics. Results indicate the interactive simulation group demonstrated Students who took part in coding-based, hands-on exercises were able to spot phishing attempts nearly twice as well as those who received traditional classes, showing a remarkable 42% boost in detection skills over standard methods 18% in the lecture-based group and The students who didn’t receive any security Students who didn’t participate in any cybersecurity activities barely improved at all, showing almost no change in their ability to recognize phishing scams; this highlights that without fresh skills, people generally stick to old habits even when digital threats are increasing 5% improvement, which suggests that without any active intervention, most people simply continue their usual habits even if they face ongoing cyber risks. The findings suggest hands-on coding simulations provide superior learning outcomes through experiential engagement, addressing a There is a clear need for practical, engaging Cybersecurity education still relies heavily on traditional classroom approaches, most of these traditional methods don’t really equip students for the types of scams and online risks they will actually encounter in their daily lives, leaving important gaps in both confidence and readiness the constantly changing landscape of digital threats fail to prepare students for real-world online risks they often lack the tools and confidence, most students aren’t equipped with the practical skills they need to spot and steer clear of today’s online dangers, which means entire groups remain vulnerable unless more effective and engaging education is provided.

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Authors: C.Jaya Prakash Reddy, R.Jaswanth, K.Rajeshkumar

Abstract: In a world where digital threats are on the rise, especially in education, we designed a mobile-first LMS (Learning Management System) to promote cybersecurity awareness in universities. Using Flutter for cross-platform app development and Firebase for cloud backend, this solution helps students and staff learn, interact, and stay informed—even offline. Key features include video modules, real-time quizzes, secure authentication, and user-friendly dashboards tailored for students, instructors, and admins. It’s lightweight, fast, scalable—and ready to make cybersecurity education smarter and more accessible.

Published by: vikaspatanker