| 1 |
Author(s):
Vivek Bhakta.
Page No :
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Why Torque Control Screwdrivers are Essential in Automotive Assembly Lines in India 2025-2026
Abstract
Torque control screwdrivers play a crucial
role in ensuring precision, efficiency, and safety in automotive assembly lines. They help maintain quality standards, reduce errors, and improve overall productivity in India’s fast-growing automotive sector.
| 2 |
Author(s):
Vivek B..
Page No :
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Using VMS for Amazon, Flipkart, Meesho, and Other Platforms in Nashik and Pune in India 2025-2026
Abstract
This article explores the role of Vendor
Management Systems (VMS) in supporting sellers across e-commerce platforms like Amazon, Flipkart, Meesho, and others. It highlights how VMS tools
enhance compliance, efficiency, and scalability for businesses in India during 2025–2026.
| 3 |
Author(s):
Vivek B..
Page No :
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Top 5 Industries Benefiting from Smartxbrains Torque Control Electric Screwdriver in India 2025-2026
Abstract
This article explores how various industries in India are leveraging the Smartxbrains Torque Control Electric Screwdriver to improve precision, efficiency, and scalability. Them tool’s adoption in sectors such as electronics, automotive, and manufacturing is reshaping workflows and enhancing quality control standards across 2025–2026.
| 4 |
Author(s):
V. B..
Page No :
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The Impact of Wire Harness Testing on Automotive Manufacturing Efficiency in Nashik and Pune in India 2025-2026
Abstract
Wire harness testing plays a critical role in enhancing automotive manufacturing efficiency, particularly in industrial hubs like Nashik and Pune. The integration of advanced testing methods ensures quality, safety, and operational reliability while supporting the region’s growing automotive ecosystem.
| 5 |
Author(s):
V. B..
Page No :
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The Impact of Torque Precision on Reducing Rework in Manufacturing Plants in India 2025-2026
Abstract
This article explores how torque precision plays a vital role in minimizing rework in manufacturing plants. By ensuring accuracy in fastening processes, industries can achieve higher efficiency, cost reduction, and improved product quality.
| 6 |
Author(s):
V. Bhakta .
Page No :
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The Benefits of Using Torque Control Electric Screwdrivers in Industries in Nashik and Pune in India 2025-2026
Abstract
This article explores the advantages of
torque control electric screwdrivers in industrial applications, with a focus on Nashik and Pune. It highlights how precision fastening, efficiency, and ergonomic design support manufacturing excellence and productivity
| 7 |
Author(s):
Vivek B..
Page No :
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Tata Cliq VMS Software – The Ultimate Solution for Video Data Management in India 2025-2026
Abstract
The Tata Cliq VMS Software offers a
comprehensive solution for video data management, streamlining storage, security, and accessibility. It is
designed to meet the growing demand for intelligent
video management in India’s rapidly advancing digital infrastructure.
| 8 |
Author(s):
Vivek Bhakta.
Page No :
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Tata Cliq VMS and SecurePack360: Redefining Video Management Standards in India 2025-2026
Abstract
This article explores how Tata Cliq’s VMS
and SecurePack360 are reshaping video management standards by integrating cloud-based solutions, security features, and scalability. The focus is on innovation, compliance, and cost-effectiveness in modern surveillance systems
| 9 |
Author(s):
Vivek.
Page No :
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Special Purpose Machines (SPM) Transforming Manufacturing in Nashik and Pune in India 2025-2026
Abstract
This article explores how Special Purpose
Machines (SPMs) are revolutionizing manufacturing in Nashik and Pune. By improving efficiency, precision, and scalability, these machines are setting benchmarks for advanced industrial growth in India.
| 10 |
Author(s):
vivek b..
Page No :
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Snapdeal VMS Software: The Ultimate Tool for Video Data Management in India 2025-2026
Abstract
The Snapdeal VMS Software is a cutting-edge
video data management solution designed to optimize security, enhance data storage, and simplify compliance.
This system bridges the gap between traditional DVR
methods and modern cloud-based solutions, offering scalability and cost-efficiency for enterprises in India.
| 11 |
Author(s):
Vivek.
Page No :
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Snapdeal VMS: Simplifying Video Management for E-Commerce Success in India 2025-2026
Abstract
The blog highlights how Snapdeal’s Video
Management System (VMS) simplifies video monitoring and security for e-commerce platforms. It emphasizes
cloud-based solutions, scalability, and compliance benefits tailored for India’s fast-growing digital retail market.
| 12 |
Author(s):
Vivek B..
Page No :
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Snapdeal VMS and SecurePack360: A Partnership for Video Excellence in India 2025-2026
Abstract
This article highlights the collaboration
between Snapdeal VMS and SecurePack360, focusing on video management innovation and secure packaging solutions. The partnership emphasizes efficiency, scalability, and compliance in modern video ecosystems.
| 13 |
Author(s):
Vivek Bhakta.
Page No :
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Importance of Wire Harness Continuity Testing for Automotive Manufacturers in Nashik and Pune in India 2025-2026
Abstract
This article explores the critical role of
wire harness continuity testing in ensuring safety, reliability, and compliance for automotive
manufacturers in Nashik and Pune. As the automotive industry transitions into 2025–2026, precision in electrical systems remains a cornerstone of quality production.
| 14 |
Author(s):
Vivek .
Page No :
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How Torque Control Electric Screwdrivers Improve Quality Control in Nashik and Pune Industries in India 2025-2026
Abstract
Torque control electric screwdrivers play
a crucial role in enhancing quality control processes within industries in Nashik and Pune. By ensuring precise torque application, these tools improve accuracy, reduce human error, and contribute to overall manufacturing efficiency.
| 15 |
Author(s):
Vivek B..
Page No :
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How to Reduce Fake Return Claims Using a Smart VMS in India 2025–2026
Abstract
This article explores how Smart Vendor
Management Systems (VMS) can effectively reduce fake return claims in India’s retail and e-commerce ecosystem.
By integrating technology-driven monitoring, real-time tracking, and fraud detection, Smart VMS solutions ensure transparency, efficiency, and customer trust.
| 16 |
Author(s):
Vivek .
Page No :
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How to Choose the Right Torque Range Screw Gun for Your Assembly Line in India 2025-2026
Abstract
This article explores key considerations when selecting the right torque range screw gun for assembly line operations. It emphasizes precision, efficiency, and safety as critical factors in ensuring smooth industrial workflows.
| 17 |
Author(s):
Vivek Bhakta.
Page No :
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A Complete Guide to Snapdeal VMS (Video Management System) Explained in India 2025-2026
Abstract
This article provides insights into Snapdeal’s
Video Management System (VMS), highlighting its benefits, features, and applications in managing video data for e-commerce sellers. The discussion emphasizes efficiency, fraud prevention, and scalability.
| 18 |
Author(s):
Vivek B..
Page No :
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A Complete Guide to Tata Cliq VMS (Video Management System) Explained in India 2025-2026
Abstract
This article explores Tata Cliq’s Video
Management System (VMS), highlighting its features, benefits, and applications in the Indian market. It provides insights into how VMS technology is shaping security, compliance, and digital management in 2025–2026.
| 19 |
Author(s):
Vivek Bhakta.
Page No :
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How a Torque Control Gun with Poka-Yoke Reduces Defects in Electronics Manufacturing in India 2025-2026
Abstract
This article explores how torque control guns
equipped with Poka-Yoke mechanisms help reduce defects in electronics manufacturing. By ensuring precision, consistency, and error-proofing in assembly processes, these tools enhance both product quality and manufacturing efficiency.
| 20 |
Author(s):
V. B..
Page No :
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How Our Smart Torque Screwdriver Prevents Missing Nuts in High-Speed Assembly in India 2025–2026
Abstract
This article explores how smart torque
screwdrivers are revolutionizing high-speed assembly processes by ensuring accuracy, efficiency, and prevention of missing nuts. The solution enhances reliability in industrial settings while reducing human error.
| 21 |
Author(s):
Saniya Shafi Ahmed Shaikh.
Page No : 1-2
|
MINI LAKEHOUSE ON DUCKDB + LOOKER STUDIO: A DATA ENGINEERING PIPELINE
Abstract
Small organizations often rely on messy, inconsistent spreadsheets that limit analytics quality. This paper presents a Mini Lakehouse architecture built using DuckDB, Parquet, and Python, with Looker Studio dashboards. The workflow ingests Excel data, performs structured cleaning, builds a star schema, enforces data quality checks, and stores curated data in Parquet/DuckDB. This fully local, low cost pipeline provides reproducible, auditable analytics without cloud infrastructure. The result is a governed, BI ready system suitable for small teams and academic environments.
| 22 |
Author(s):
Hibha Z Mujawar, Soujanya M Pattar, Shreedevi Mandsoppi.
Page No : 1-2
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ANDRIOD BLUETOOTH BASED WOMEN’S SAFETY IN CAB
Abstract
This project presents an Android-based women’s safety system designed to enhance security for female passengers traveling in cabs. The system uses Bluetooth communication between the passenger’s mobile application and a dedicated safety device installed in the vehicle. In emergency situations, the user can trigger an alert through the mobile app or an integrated hardware button, which immediately sends real-time location details and distress notifications to predefined contacts. The solution ensures quick, reliable, and discreet communication without depending solely on mobile data connectivity. By integrating Bluetooth technology, GPS tracking, and user-friendly Android interfaces, the system aims to provide an effective safety mechanism that improves confidence and security for women during cab travel.
| 23 |
Author(s):
Akshar Grover, Kanishka Chaturvedi, Grishi Sachdeva.
Page No : 1-3
|
Spam Email Classification using NLP
Abstract
Spam emails pose a significant challenge by inundating inboxes with unsolicited messages, advertisements, and potential security threats such as phishing and malware. This study explores the application of Natural Language Processing (NLP) and machine learning techniques for spam detection. Using a structured dataset, we preprocess and extract features from email content before applying classification algorithms. The study evaluates two models: Logistic Regression and a deep neural network with a multi-layered architecture. Results indicate that the neural network outperforms Logistic Regression in terms of accuracy and adaptability. This research contributes to enhancing spam detection methodologies by improving classification accuracy and minimizing false positives.
| 24 |
Author(s):
Aakanksha Shelar, Vidya Nikam.
Page No : 1-3
|
Review paper on IoT based Weather Reporting system
Abstract
The weather monitoring and reporting system project is used to get live reporting of whether condition. It will monitor temperature, humidity, moisture. The proposed system is a progressive solution for whether monitoring at a particular place and make the data available over the internet. This data can then be viewed in an application so that necessary and timely action can be taken. The system makes use of sensor, siren and other electronic component for the monitoring of climate parameters. The system deals with controlling and monitoring the environmental adjust like temperature, relative humidity, rain drop, flame with sensors and sends the information to the cloud which can also be accessible on Android app and then plot the sensor data as scripted form.
| 25 |
Author(s):
Jyoti parmar.
Page No : 1-4
|
An Overview on High Performance Thin layer Chromatography
Abstract
HPTLC method includes selection of stationary phases, mobile phases, detection methods, and optimization of experimental conditions to achieve high resolution, sensitivity, and reproducibility. HPTLC is one type of planner chromatography and most advanced form of instrumental TLC. HPTLC operates on the same separation by adsorption concept as TLC. HPTLC offer wide choice of stationary phase Like Silica gel for normal phase and C8, C18 for reversed phase modes where sample can be detectable in nanograms with increased precision and sensitivity. HPTLC is a great instrument for detecting adulterations and is well suited for checking stability as well as assessing and tracking the processes of cultivation, harvesting, and extraction.Furthermore, the article explores the wide range of applications of HPTLC in pharmaceutical, environmental, food, and forensic analysis by integration of HPTLC with other analytical techniques, such as mass spectrometry (MS) and spectrophotometry, to enhance its capabilities.. This review aims to serve as a valuable resource for researchers and analytical chemists involved in the development and optimization of HPTLC methods for complex matrix.
Keywords : HPTLC , Resolution , Advantage , Pharmaceutical
| 26 |
Author(s):
Abhigyan Ranjan, Ritesh Kumar .
Page No : 1-4
|
Small Language Model for coding and debugging
Abstract
The proliferation of Large Language Models (LLMs) has significantly impacted software development, yet their substantial computational and resource demands create barriers to widespread accessibility. This paper details the development and evaluation of a Small Language Model (SLM) designed as an efficient, practical alternative for coding assistance. The primary goal is to create a lightweight, low-latency model specialized in Python, capable of performing real-time code completion and generating functions from natural language prompts. The methodology employs a transformer-based decoder-only architecture (100-300M parameters) trained on a filtered, high-quality dataset of open-source code. Model performance is assessed using the pass@k metric from the HumanEval benchmark for functional correctness, alongside measurements of inference speed and memory footprint to validate its efficiency. This research will deliver a proof-of-concept prototype, demonstrating that specialized SLMs can offer a sustainable and effective solution that enhances developer productivity while democratizing access to advanced AI-powered coding tools.
| 27 |
Author(s):
Mayank Kumar.
Page No : 1-4
|
Text to Image AI SAAS
Abstract
The emergence of generative Artificial Intelligence (AI) has revolutionized creative content generation, enabling machines to produce high-quality visual outputs from textual descriptions. This research presents the design and implementation of 'Pictura'—an AI-powered text-to-image Software-as-a-Service (SaaS) web application. The project aims to democratize visual creativity by allowing users to generate unique, high-resolution images from natural language prompts using a user-friendly interface built on the MERN stack (MongoDB, Express.js, React.js, Node.js). The system securely integrates the Clipdrop API for AI-based image generation while incorporating features like user authentication, image management, and sharing capabilities. The research explores a full-stack implementation approach emphasizing modular development, data integrity, and security using JWT authentication. The outcome demonstrates a scalable and accessible solution for rapid visual content creation, bridging the gap between human imagination and AI-assisted artistry.
| 28 |
Author(s):
Smriti Thakur, Dr. Yatu Rani.
Page No : 1-4
|
AI in Cybersecurity : Instrusion Detection using Machine Learning
Abstract
The rapid increase in cyberattacks across modern digital infrastructures has highlighted the urgent need for intelligent and adaptive security solutions. Traditional intrusion detection systems (IDS), though widely deployed, struggle to detect novel, evasive, and complex threats due to their dependence on predefined signatures and static rules. Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has emerged as a powerful alternative for intrusion detection by learning from historical attack patterns and modeling anomalous behaviors.
This research paper provides a structured overview of AI-driven intrusion detection techniques, focusing on signature-based, anomaly-based, and hybrid ML models. The paper examines their mechanisms, performance strengths, limitations, and practical applicability across different network environments. Furthermore, it evaluates commonly used datasets such as NSL-KDD and CICIDS2017 that form the foundation of IDS research.
The study also identifies challenges in deploying ML-based IDS, including interpretability issues, scalability constraints, adversarial vulnerabilities, and false positive rates.
| 29 |
Author(s):
Dr. Shailaja Mudengudi, Komal L Mane, Laxmi B Amargol, Vani S Sarvi .
Page No : 1-4
|
Synchronous V/S Asynchronous FIFO Design
Abstract
This project presents the design, implementation, and comparative analysis of Synchronous FIFO and Asynchronous FIFO architectures using Verilog HDL and EDA tools. FIFO (First-In-First-Out) memories are widely used in digital systems for temporary data storage and reliable communication between subsystems. However, designing FIFO architectures that ensure high speed, low power, and reliable clock-domain crossing remains challenging.
| 30 |
Author(s):
Tushar Verma .
Page No : 1-4
|
DIFFERENT TYPES OF ACTING ACROSS REGIONS: FORMS, TRADITIONS AND TECHNIQUES
Abstract
Acting is a cornerstone of dramatic art in theatre, film, and other performance media, yet the ways in which actors approach their craft vary significantly across cultural and regional traditions.
This paper explores how different regions of the world deploy distinct acting types and techniques, shaped by historical, cultural, and aesthetic traditions; societally embedded performance conventions; media (theater vs film vs television); and the evolving global interchange of ideas. In particular, the paper investigates classical and contemporary traditions in Western, South Asian
(especially Indian) and African/West African contexts showing how each region has developed unique forms of actor training, performance style, audience expectation, and narrative structure. Drawing from key theoretical frameworks (for instance, the Naṭya Sastra of ancient India), the research outlines how acting is conceived not merely as imitation or representation but as a creative process involving mind, body, and cultural signifiers. The study identifies major forms of acting
(e.g., realist, stylized, presentational) and traces how they manifest regionally: for example, in Indian classical theatre the modes of Angika (gesture), Vachika (voice), Aharya (costume), and Sattvika (inner emotion) are formalized; in Western modern film acting the legacy of the Konstantin Stanislavski “system” / method acting emphasizes psychological realism; and in African film and theatre particular linguistic, gestural, and communal performance traditions persist while adapting to modern media. The paper argues that understanding region-specific acting types enhances our appreciation of the actor’s craft and deepens cross-cultural insights into performance. Furthermore, in the globalized era there is a blending of techniques Indian film actors adopting American-style method acting, for example but the regional roots remain influential. The paper concludes with reflections on how acting training and performance will continue to diversify in the 21st century as digital media, global audiences, and hybrid performance forms further transform what it means to act.
| 31 |
Author(s):
Harshita soni.
Page No : 1-4
|
NET NEUTRALITY AND THE FUTURE OF DIGITAL COMMUNICATION IN INDIA
Abstract
This paper explores the evolving idea of Net Neutrality , the principle that Internet Service Providers (ISPs) and governments must treat all digital data equally, without discrimination or special pricing based on its source, type, or platform. In India, where digital transformation is reshaping everyday life, maintaining a fair and open internet has become crucial to ensuring innovation, inclusion, and democracy. Using frameworks such as Gatekeeping Theory and Information Asymmetry, this study examines how India’s regulatory landscape, particularly the role of the Telecom Regulatory Authority of India (TRAI), has shaped the maintaining neutrality. The paper concludes that while India has built a strong legal structure to protect a free internet, constant vigilance is essential against newer and subtler challenges like algorithmic throttling or exclusivity-based network handling , that could quietly weaken digital equality.
Keywords: Internet, Net neutrality, Digital India, Telecom Regulatory Authority of India [TRAI]
| 32 |
Author(s):
Roshan Thasfiha M. Abbas.
Page No : 1-5
|
Fiber reinforced concrete
Abstract
Fiber-reinforced concrete (FRC) has piqued interest in civil engineering in the few recent years because of its ability of improving weak tensile strength and shrinkage cracks of concrete. There are many possibilities in the research field for FRC.
This paper reviews, summarizes and compares the current and past researches on FRC. Based on the main research achievements on FRC in recent years, this paper compiles and briefs the existing theoretical research FRC materials and related topics to facilitate the reference of researchers in the same field.
| 33 |
Author(s):
Meenu, Shubham Sharma.
Page No : 1-5
|
Enhancing Learning with Retrieval-Augmented Generation in AI Teaching Assistants
Abstract
This research paper is about creating an AI Teaching Assistant using the Retrieval-Augmented Generation (RAG) method to make learning easier and more
effective. In today’s world, artificial intelligence is becoming an important part of education. Many AI tools can help students study, but some of them give limited or outdated answers because they only use the data they were trained on. The RAG approach
helps to solve this problem by using two steps. First, it searches for the most suitable information from a large collection of data, and then it uses a language model to generate an answer in simple and clear language. This helps the system give more accurate
and useful answers to students’ questions. The AI
Teaching Assistant made with this method can help
students understand difficult topics, answer their queries, and provide extra study help whenever needed. It can also support teachers by saving time and improving communication with students.
Overall, this study shows that RAG can make AI teaching tools more helpful, interactive, and
personalized for better learning
| 34 |
Author(s):
Mahek Sharma .
Page No : 1-5
|
GoGlobe Artificial intelligence in Travel
Abstract
It is an AI power personalized travel planning with application designed to eliminate the complexity and time consumption associated with traditional trip to planning.
| 35 |
Author(s):
Tamladipta Sen.
Page No : 1-5
|
Bridging Financial Theories and Market Realities: Insights from Key Episodes in the Indian Financial Market
Abstract
The Indian financial market has undergone a remarkable evolution, emerging as a complex ecosystem where classical financial theories and modern behavioral dynamics coexist. This paper examines the intricate linkage between established financial theories and real-world developments within the Indian financial system, using an event- and concept-based approach. It integrates seminal frameworks such as the Efficient Market Hypothesis (EMH), Behavioral Finance Theory, Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), Agency Theory, Information Asymmetry and Signaling Theory, and Financial Instability Hypothesis to interpret pivotal market and policy episodes – ranging from the Harshad Mehta scam (1992) and the Ketan Parekh bubble (2001) to the Global Financial Crisis (2008), Demonetization (2016), IL&FS collapse (2018), COVID-19 pandemic (2020), and Adani-Hindenburg episode (2023). By synthesizing theoretical frameworks with these events, the study reveals that India’s financial market operates as a behavioral-institutional hybrid system – a structure where rational efficiency is continuously negotiated with psychological tendencies, policy interventions, and structural constraints. The paper concludes that the evolution of India’s financial market underscores the necessity of adaptive theoretical models that account for behavioral diversity and institutional maturity in emerging economies.
| 36 |
Author(s):
Priyanka. G .
Page No : 1-6
|
IMPACT OF REVIEWS AND RATINGS ON CONSUMER PERCEPTION OF AUTOMOBILES
Abstract
In today’s digital age, online reviews and ratings have become powerful tools influencing consumer decision-making, especially in the automobile sector. This study focuses on understanding how customer reviews and ratings impact consumer perception, brand image, and purchase intentions of automobiles. With the growing reliance on digital platforms, consumers often evaluate vehicles based on the experiences and feedback shared by previous
buyers. The study aims to analyze the relationship between online reviews, ratings, and factors such as trust, satisfaction, and brand credibility. Primary data is collected through surveys to identify patterns in consumer behavior, while secondary data from automotive websites and review portals support the analysis. The findings of this research highlight that positive reviews and high ratings significantly enhance consumer confidence, whereas negative feedback can deter potential buyers. This paper concludes that online reputation management and customer engagement are essential for automobile brands to sustain competitiveness in the digital marketplace.
| 37 |
Author(s):
M. Deviroshini, Dr. S. Muthumani, Sam Bodunrin.
Page No : 1-6
|
STUDY ON INFLUENCE OF DIGITAL MARKETING ON CUSTOMER PURCHASE BEHAVIOUR
Abstract
In the modern business landscape, digital marketing has emerged as a crucial tool for influencing customer purchase behaviour. This study examines the impact of various digital marketing channels—such as social media marketing, search engine optimization, email campaigns, and online advertisements—on consumer decision-making processes. The research aims to identify how factors like online engagement, personalized content, digital trust, and brand visibility affect customers’ awareness, interest, and purchasing intentions.
| 38 |
Author(s):
Muskan jain.
Page No : 1-6
|
A REVIEW ON COMPARISON OF REVERE PHASE – HPLC FROM NORMAL PHASE -HPLC
Abstract
This review mainly focuses on comparing between normal phase and reverse phase HPLC also its instrumentation and applications. The importance of RPHPLC in analytical method development and their strategies along with brief knowledge of critical chromatographic parameters needed for optimized an efficient method development has been mentioned. The key difference between reverse phase and normal phase HPLC is that the reverse phase HPLC uses a nonpolar stationary phase and a polar mobile phase whereas the normal phase HPLC uses a polar stationary phase and a less polar mobile phase.
Keywords: Chromatography, RPHPLC, Instrumentation of HPLC, Applications
| 39 |
Author(s):
Yash Pandey.
Page No : 1-6
|
Klipify: AI Educational Platform
Abstract
Klipify is an AI-driven educational platform that
transforms YouTube videos into structured learning resources.
By leveraging advanced video processing and natural language
understanding, it generates smart clips, concise summaries,
timestamped notes, and interactive study assistance. Addressing
the challenge of unstructured educational content, Klipify distills
lengthy videos into clear, accessible formats, helping learners
focus on key concepts efficiently. Its modular, scalable architecture integrates tools like VideoDB and Google GenAI, while the
Streamlit-based interface ensures ease of use. Klipify bridges the
gap between abundant digital content and organized learning,
making education more engaging, efficient, and personalized.
Index Terms—AI in Education, Natural Language Processing,
Streamlit, Video Segmentation, YouTube Learning, Educational
Technology
| 40 |
Author(s):
Srishti Gupta.
Page No : 1-6
|
The Military Object Detection System using YOLOv7: An Automated Deep Learning Solution for Defense and Surveillance
Abstract
The Military Object Detection System represents a significant advancement in the application of artificial intelligence for
defense and surveillance applications. This research presents the development and deployment of a robust, automated solution
utilizing YOLOv7 (You Only Look Once, version 7) architecture for detecting military bases and related objects across diverse
media formats including static images, recorded videos, and real-time webcam streams. The system is designed to operate
securely in offline environments, ensuring strict data privacy and compliance with defense protocols. The project encompasses
data preparation with 13 military object classes (Aircraft, Camouflage, Drone, Fire, Grenade, Hand Gun, Knife, Military-
Vehicle, Missile, Pistol, Rifle, Smoke, and Soldier), comprehensive model training utilizing state-of-the-art deep learning
techniques, and deployment across multiple input modalities. Performance evaluation demonstrates exceptional results with
mean Average Precision (mAP) at 0.5 intersection over union reaching 86.9% and precision at 90.1%, indicating strong
generalization and reliability. The system delivers real-time detection at over 30 frames per second, making it highly suitable
for operational surveillance and threat assessment. This paper presents the complete methodology, architectural details,
experimental results, and operational deployment strategies for a practical deep learning-based military object detection system
Keywords: YOLOv7, object detection, military applications, deep learning, real-time detection, surveillance, convolutional
neural networks, automation
| 41 |
Author(s):
Seema Timmanagoudar.
Page No : 1-6
|
Design and Simulation of an AHB to APB Protocol Bridge
Abstract
Efficient communication between high-speed and low-speed components in System-on-Chip (SoC) architectures requires reliable protocol conversion mechanisms. The AMBA AHB (Advanced High-Performance Bus) and APB (Advanced Peripheral Bus) represent two widely adopted communication protocols serving distinct classes of system components. This work presents the complete design, RTL implementation, simulation, and synthesis analysis of an AHB to APB protocol converter.
The bridge translates high-speed, pipelined AHB transactions into simple, non-pipelined APB operations using a finite-state-machine (FSM)-based controller. The architecture supports a single AHB master, four APB slaves, and parameterized 512-bit wide data/address paths. Functional verification is performed using Cadence Xcelium, while synthesis and timing analysis are carried out using Cadence Genus. Simulation confirms correct protocol conversion, APB sequencing, and data handling. Synthesis results further validate area feasibility, clock performance around 100 MHz, and predictable power consumption. This work demonstrates a complete, synthesizable AMBA-compliant bridge suitable for SoC subsystem integration
| 42 |
Author(s):
SHREYAS GOSWAMI.
Page No : 1-7
|
Role of Ai and Ml in disease diagnosis and Early detection
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) are transforming disease diagnosis and early detection by enabling faster, more accurate, and data-driven clinical decision-making. By analyzing complex medical data such as imaging, biosignals, and electronic health records, AI and ML models can identify subtle patterns indicative of early disease onset. This paper reviews current advancements, key applications, and challenges, highlighting how these technologies enhance diagnostic precision and support timely intervention.
| 43 |
Author(s):
Amruta Sakhare.
Page No : 1-8
|
Dark Web Monitoring in Cyber Threat Intelligence (CTI)
Abstract
The dark web is a hidden, encrypted portion of the internet that acts as a central location for a variety of illegal activities and presents serious risks to both individuals and companies. With the ability to provide proactive insights into prospective cyber threats prior to their manifestation, dark web monitoring has become an essential part of Cyber Threat Intelligence (CTI). Within the context of the CTI framework, this article investigates the technology, approaches, and difficulties related to monitoring the dark web. It talks about automated methods and tools, like machine learning and natural language processing (NLP), that are used to collect and evaluate data from dark web sources. It also discusses the moral and legal issues surrounding the surveillance of dark web activity. This study demonstrates how dark web monitoring can improve cybersecurity through case studies and practical implementations.
| 44 |
Author(s):
LADDIKA SASHANK.
Page No : 1-8
|
IOT BASED SMART BATTERY MONITORING SYSTEM
Abstract
This paper work presents an Internet of Things-based system developed to observe and manage lithium-ion battery behavior through real-time sensing and cloud communication. The system measures essential battery parameters, including voltage, current, temperature, state of charge, and gas emissions, using integrated sensors connected to a Wi-Fi–enabled microcontroller. Collected data is processed and sent to a cloud dashboard, where users can remotely view battery performance and receive automated notifications when values exceed safe operating limits. The monitoring unit incorporates charging control and temperature-driven activation of a cooling mechanism to prevent overcharge, overheating, and chemical instability. Experimental validation confirms that the system provides accurate parameter tracking, stable wireless communication, and timely alert generation. The results demonstrate that the approach enhances battery protection, improves operational reliability, and extends usable battery life through continuous, automated supervision. The proposed design offers a low-cost and scalable method for intelligent battery monitoring suitable for portable devices, renewable-energy storage, and other applications requiring dependable real-time oversight.
| 45 |
Author(s):
Dr. GAURI SHANKAR YADAV.
Page No : 1-10
|
The Psychological Impact of AI Companies and Virtual Therapists on Emotional Regulation and Loneliness
Abstract
Artificial intelligence (AI) has rapidly entered the sphere of psychological well-being through conversational agents, virtual therapists, and affective computing applications. Companies such as Replika, Woebot, and Wysa increasingly mediate emotional experiences once reserved for human relationships. This paper explores the psychological impact of such AI-driven interventions on emotional regulation and loneliness. Integrating theories of emotion regulation (Gross, 1998; 2021), social connectedness (Baumeister & Leary, 1995), and human–AI interaction, the study synthesizes empirical and theoretical findings on how digital companions shape affective processes. While AI companions can reduce perceived isolation and facilitate adaptive coping, they may also reinforce avoidance behaviors, displace authentic social contact, and blur boundaries between empathy simulation and emotional dependence. The literature review reveals a complex dialectic: AI may both soothe and sustain loneliness. The paper calls for nuanced frameworks integrating technological literacy, ethics, and clinical psychology to guide responsible AI mental-health design and policy.
Keywords: Artificial intelligence, virtual therapy, emotional regulation, loneliness, affective computing, digital psychology, mental health technology.
| 46 |
Author(s):
P. Reshma.
Page No : 1-10
|
Multimodal Patient Monitoring System for Abnormality Detection using Hybrid CNN-BiLSTM model
Abstract
The prompt and precise identification of heart abnormalities from biological information is essential in advanced healthcare systems. This paper introduces an AI-based hybrid framework for real-time detection of cardiac anomalies by combining electrocardiogram (ECG) and photoplethysmogram (PPG) signal processing with sophisticated machine learning methodologies. The suggested system employs extensive preprocessing and augmentation techniques, such as Gaussian noise injection, amplitude scaling, and temporal shifting, to increase signal diversity and enhance model generalization robustness. Morphological and temporal cardiac characteristics—including P-wave duration, PR interval, QRS complex width, ST-segment level, T-wave duration, and Pulse Transit Time (PTT)—are obtained utilizing the WFDB, NeuroKit2, and BioSPPy frameworks. Annotation-assisted feature labeling and automated P-wave delineation are integrated to guarantee dependable beat-level characterisation.
An ensemble CatBoost model is utilized for classification, exhibiting enhanced efficacy compared to traditional Random Forest classifiers in managing non-linear, multi-dimensional biological data. The model's efficacy is assessed by cross-validation and confusion matrix analysis, resulting in a mean accuracy enhancement over 15% relative to baseline approaches. The findings underscore the efficacy of gradient boosting topologies for comprehensive cardiac health evaluation. This framework establishes a basis for real-time, AI-enhanced heart monitoring and can be further incorporated into smart wearable and telemedicine systems to enable early detection and predictive diagnosis in cardiovascular healthcare
