Authors: Mr.P.Tamilnesan, G.Devaprakash, J.Mouleeshwaran

Abstract: This project presents comprehensive power system studies of a 13.8 kV substation network to improve power quality and operational reliability. Load flow analysis is carried out to evaluate voltage profiles, power losses and reactive power flow while maintaining a minimum lagging power factor of 0.95 at the Point of Common Coupling. Short circuit analysis is performed to determine fault current levels and verify equipment and protection adequacy. Motor acceleration studies assess starting currents, voltage dips and dynamic performance of large motors. Power factor improvement is achieved through optimal selection and placement of capacitor banks. The impact of capacitor switching, including transients and self excitation effects is evaluated. Harmonic analysis is conducted to ensure acceptable distortion levels. Transient stability of the system during disturbances is analyzed using ETAP. The study demonstrates improved voltage stability, reduced losses and enhanced system reliability.

DOI: https://doi.org/10.5281/zenodo.19383047

 

Published by: vikaspatanker

Authors: Sowmya Yattapu

Abstract: Artificial Intelligence is fundamentally transforming the discipline of data engineering. This paper examines how AI is reshaping core data engineering functions including relational and cloud database management, data warehousing, enterprise analytics, digital analytics platforms such as Adobe Analytics, and cloud-native platforms such as Snowflake. Drawing on current industry practices and emerging platform capabilities, this paper analyzes the impact of AI on pipeline development, data quality management, automated metadata governance, and real-time analytics. This paper further discusses how the role of the data engineer is evolving from manual code writing to strategic architecture and AI-assisted orchestration. The paper also addresses key challenges including data privacy in regulated financial environments, skill evolution requirements, and the governance of AI-generated outputs. Paper findings indicate that organizations which invest in AI-ready data infrastructure, establish strong governance frameworks, and upskill their engineering teams will gain significant competitive advantages in the next decade.

DOI: https://doi.org/10.5281/zenodo.19382867

Published by: vikaspatanker

Authors: Mrs.M. Lavanya, U. Dhivakar, A. Mohamed Arsath, N. Mohamed Rasheen

Abstract: In many colleges, students face difficulties during placement preparation due to limited training resources, lack of real interview exposure, and insufficient guidance on resume building and job selection. Traditional placement training is often theoretical, time-restricted, and does not accurately reflect real company recruitment processes. As a result, students struggle with aptitude tests, technical interviews, and HR rounds, which affects their confidence and employability. Smart Placement is an AI-powered web-based application developed to overcome these challenges by providing a complete and structured placement preparation platform for all students. The system simulates real recruitment processes through aptitude, reasoning, technical, and HR interview modules. Aptitude and reasoning tests enhance logical thinking and problem-solving skills, while the technical round strengthens core subject knowledge. A key feature of the platform is the real-time AI based HR interview module, which evaluates communication skills, confidence level, and behavioral responses. The system also includes an automated resume builder that generates professional, industry-standard resumes for freshers and experienced candidates. Additionally, Smart Placement offers job search, job notifications, and company offer listings, enabling students to explore real-time job opportunities. By integrating AI-driven interviews, resume automation, and job availability tracking into a single platform, Smart Placement improves placement readiness, boosts confidence, and bridges the gap between college training and industry recruitment requirements.

DOI: https://doi.org/10.5281/zenodo.19382255

Published by: vikaspatanker

Authors: Nitesh Baranawal, Herambh Sakpal, Pranay Manoj, Kaustabh Kadam, Prof.Mohan Kumar

Abstract: The Steganography Hider System is a secure information-hiding solution designed to protect sensitive data by embedding it within digital images, making it imperceptible to unauthorized users. Unlike traditional encryption, which only disguises data, steganography conceals the very existence of the information, providing an additional layer of security. This system employs techniques such as Least Significant Bit (LSB) substitution, transform domain methods (e.g., DCT), or advanced neural network approaches to embed secret messages while maintaining the visual quality of the cover image. The proposed system allows users to securely hide and retrieve confidential information, ensuring data confidentiality, integrity, and robustness against common image processing operations such as compression, noise addition, and format conversion. This project serves as a practical demonstration of the importance of information security in today’s digital communication era, providing a user-friendly interface that can be applied in various fields such as secure communications, copyright protection, and digital forensics.

DOI: https://doi.org/10.5281/zenodo.19381939

 

Published by: vikaspatanker

Authors: Ms. V. Mounica, V. Rakesh Firoz, T. Yashwanth, P. Ratna Babu, P. Sowmya

Abstract: In today’s competitive job market, resume screening plays a critical role in recruitment processes. However, traditional Applicant Tracking Systems (ATS) rely heavily on keyword matching and lack transparency, personalization, and intelligent feedback. This paper presents AICRUIT, a dual-mode intelligent resume evaluation platform designed to enhance resume screening using Natural Language Processing (NLP) and Explainable AI (XAI). The system operates in two modes: a Normal Review Mode using TF-IDF-based keyword matching and an AI Review Mode powered by advanced language models. It evaluates resumes across multiple criteria such as structure, skills, experience, and ATS compatibility. Additionally, AICRUIT provides an explainable score breakdown, enabling users to understand and improve their resumes effectively. Experimental results demonstrate high usability, with structured scoring and real-time feedback improving resume quality and user engagement. The platform bridges the gap between automated screening and human-like evaluation, making it a powerful tool for job seekers.

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Published by: vikaspatanker

Authors: Harini M S, Dr. Geetha Margret Soundri, Devaki s

Abstract: Origami presents numerous forms and intricate production techniques, and it is considered one of the essential contemporary art forms. To enhance the creative expressions in fashion design, this paper outlines the various ways origami art is applied in fashion design by examining its external and structural features, conducting experimental analysis of fabric properties, and summarizing suitable expressive techniques. The findings indicate that origami's folding applications and clothing design can be achieved through techniques such as ironing, crimping, stitching, texture shaping, and repeated combination moulding, including pattern deformation folding, fabric transformation folding, and modular combination folding. The use of folding techniques in creating three-dimensional clothing designs and surface textures is emphasized. To reduce manufacturing flaws and enhance mechanical performance, this work employs curved-crease origami principles to manufacture composite structures using NCFs. The results reveal that the biaxial NCFs are able to develop adequately without any wrinkle flaws over origami-based geometries. Situation-based design thinking motivates designers to be creative by applying their expertise and abilities to develop design solutions. This research explores design thinking and investigates an approach to fashion design education that supports students in cultivating three-dimensional creative abilities. The project involved from the Fashion and Design Department and was conducted as a planned activity. Origami served as the inspiration to explore complex structures, starting with two-dimensional ideas and progressing to three-dimensional shapes, first using paper and later translated into fabric for a skirt design. The general results indicate that the project offers a successful method for fashion design education designed to encourage creative thinking. This teaching approach to fashion design and pattern making offers a contemporary, practical learning experience for design students, allowing them to develop creative designs by combining the production process with the broader design strategy. These encouraging findings suggest that work must go on concerning automation methods based on origami.

DOI: https://doi.org/10.5281/zenodo.19368866

 

Published by: vikaspatanker

Authors: Dileep Chandra Mouli, Mrs.D.Sudha M.E

Abstract: Today Cyberattack are heavily automated, relying on AI based intrusion methods and fast evolving malware to evade network defense mechanisms. Static honeypots are used for threat monitoring, but they can be quickly identified by professional attackers, limiting their usefulness in practice. This work develops an AI-Powered Polymorphic Honeypot (AIPPH), which facilitates adaptive, intelligent, and stealthy threat deception for advanced network security systems. The above- mentioned approach integrates machine-learning-based behavioral analysis, dynamic environment generation, and polymorphic service emulation for the honeypot to evolve all its system signatures, network behavior, responses, and operating- system-level characteristics in real time. This flexibility greatly improves engagement times by attackers and minimizes the risk of honeypot detection. A real-time threat intelligence module deepens the capabilities of the system by clustering attacker behavior and discovering previously unknown zero-day attacks.

Published by: vikaspatanker

Authors: Tellakula Bhuvana Sai Ram, Patteparapu Kethana Lakshmi, Shaik Baji Shareef, Kuchu Karthik Naidu, A. V. S. Sudhakar Rao

Abstract: In today’s digital era, access to quality learning resources is often limited by financial constraints and lack of personalized guidance. Traditional online learning platforms primarily follow a one-way knowledge delivery model, which restricts real-time interaction and collaborative growth. This paper presents Peer Skill, a credit-based peer-to-peer skill exchange platform that enables users to both learn and teach skills without any monetary transactions. The platform introduces a unique credit point mechanism, where users earn credits by teaching skills and spend them learning new ones. The system incorporates session booking, teacher approval workflows, real-time virtual classes using video conferencing tools, and a feedback-based rating system to ensure quality learning experiences. Additionally, users can apply to become teachers through an admin-controlled verification process involving interviews.

Published by: vikaspatanker

Authors: Dr C Chinna Suresh Babu, S.Kamruddin

Abstract: Andhra Pradesh is called as the “Rise Bowl” of India, Andhra Pradesh consists of 13 districts. Out of these 13 districts Y.S.R Kadapa (nearst while Kadapa) District has lots of mineral resources ,irrigation projects, Cement and Uranium Industries and well known for Turmeric ,Paddy and Red Gram crops as well as Historical places like Gandikota etc., In this Project weare going to deal with only the Irrigational Structures or Projects in Kadapa District like how many Major, Minor, Medium Irrigational works, at what extent they are helping Kadapa District, About Ongoing Irrigation and also about Water work’s or Projects, about rivers flowing in Kadapa District. The present study will provide a clear-cut information about the irrigation profile of the entire YSR with emphasis on major and minor irrigation structures and networks which will provide an overall glimpse to the district which will helpful to the future studies and common man also. Introduction Y.S.R. Kadapa district lies in the Rayalaseema region and experiences low rainfall (~700 mm annually). The district depends heavily on irrigation systems such as canals, reservoirs, and groundwater. Despite having major irrigation projects like K.C Canal and Telugu Ganga Project, large areas still face water scarcity.

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Published by: vikaspatanker

Authors: Thilak Patel, Bharath, Abhiram, Vamshi

Abstract: Budget Mate is an online expense tracker that offers smart finance management using machine learning. Users can input or extract expense and classify it by categories such as utilities, groceries, housing, entertainment, and subscription services. The machine learning based classification requires little manual input, while increasing the fidelity of managing and tracking finance. Users can track monthly expenses, analyze spending patterns, and reflect on their financial behaviors through interactive data visualization on a user dashboard. Furthermore, Budget Mate provides users with insight into a potential money management source that is smarter than tracking money—it provides solid budget plans, and savings recommendations based on any user behavior, which could encapsulate historical expense data, conversation note, and even some higher level personal finance inquires, potentially expanding to a method of money management beyond expense tracking and giving a proactive form of money management. Using a unified simplified interface, the service can scale beyond simple expense, and can seriously accommodate divergent scenarios.

DOI: https://doi.org/10.5281/zenodo.19366908

 

Published by: vikaspatanker