Daily Archives: June 2, 2025

Authors: Assistant Professor DR. Ritu Jain, Aditya Pratap Saroj

Abstract: The Himalayan glaciers, also referred to as the "Third Pole," play a vital role in the ecological balance of the region and supply water to more than a billion Asians, sustaining agriculture, drinking water, and energy. Climate change has resulted in rapid glacial retreat, which has resulted in decreased water resources, enhanced disaster risks, and ecosystem threats. This chapter examines the effect of glacial melt, employing remote sensing, satellite imagery, and climate models to evaluate the scale of retreat and its consequences, including water scarcity and ecosystem disruption. It discusses adaptive measures, such as enhanced water storage, flood early warning systems, and sustainable agriculture to reduce the impacts of declining glacial melt. Community-based techniques, combining indigenous knowledge, are also mentioned as important in controlling water resources. Lastly, the chapter discusses the necessity of cross-border policy and cooperation to develop solutions for the water crisis to ensure the sustainable management of the region's glaciers and water.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Dr. Ritu Jain, Kajal Pandey

Abstract: Urban sprawl, defined as the haphazard expansion of city boundaries into rural and peri-urban lands, is a defining characteristic of contemporary urban growth in India. As a prominent Tier-2 city and capital of Uttar Pradesh, Lucknow has witnessed accelerated sprawl patterns over the past three decades. This paper investigates the extent, causes, and implications of this urban expansion using remote sensing data, GIS techniques, demographic trends, and field-based insights. With a focus on infrastructure strain, socio-economic disparities, environmental degradation, and spatial policy inefficiencies, this research identifies key trends, challenges, and solutions. Recommendations are proposed for integrated planning, sustainable growth, and data-driven governance.

 

 

Published by: vikaspatanker

Authors: Pallavi Srivastava

Abstract: In low-resource environments, diagnostic tools must prioritize affordability while also delivering accuracy, reliability, and durability suited to the unique challenges of the developing world. In recent years, global health diagnostics using minimally instrumented, microfluidic platforms with low-cost disposable components have gained momentum, driven in part by funding from organizations like the Bill & Melinda Gates Foundation and the National Institutes of Health. This surge in interest has resulted in a variety of promising prototype devices, many of which are undergoing advanced development or clinical testing. These include systems capable of multiplexed PCR assays targeting enteric, febrile, and reproductive tract infections, as well as immunoassays for conditions like malaria, HIV, and sexually transmitted infections. More recent innovations feature fully disposable diagnostics that operate without instruments, utilizing isothermal nucleic acid amplification techniques. Despite these advancements, scalable and truly low-cost manufacturing methods remain a major hurdle in creating affordable diagnostic solutions at volume. This overview highlights current platform development efforts, includes original research conducted at PATH, and emphasizes the need for continued action and innovation in this field.

 

 

 

Published by: vikaspatanker

Authors: Assistant Professor Dr. Ritu Jain, Himanshu Kasaudhan

Abstract: The Northeastern region of India, comprising the states of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura, represents a critical ecological zone within the Indo-Burma biodiversity hotspot. This area is home to a vast range of endemic and threatened species and features one of the highest levels of biological diversity in India. However, rapid deforestation caused by anthropogenic pressures—such as shifting cultivation (jhum), illegal logging, infrastructure expansion, and population growth—has led to severe ecological degradation. This chapter explores how Remote Sensing (RS) and Geographic Information Systems (GIS) have been employed to monitor forest cover changes and assess their impact on biodiversity. Through the use of satellite imagery, spatial analysis, biodiversity indices, and ecological modeling, this study highlights the extent, patterns, and consequences of deforestation on flora and fauna. The chapter concludes by offering conservation strategies and policy recommendations grounded in geospatial data and ecological science.

 

 

 

Published by: vikaspatanker

Authors: Assistant Professor Benasir Begam.F, Assistant Professor Agalya.A, Assistant Professor Gopalakrishnan T

Abstract: Machine vision, a sub-discipline of computer science and artificial intelligence, has evolved into a robust technological framework that enables machines to interpret and make decisions based on visual data. This review delves into the computational underpinnings of machine vision, tracing its development from classical image processing techniques to state-of-the-art deep learning architectures. Special emphasis is placed on domain-specific applications such as autonomous navigation, medical diagnostics, and smart manufacturing, highlighting how vision-enabled machines are reshaping real-world operations. The paper further explores benchmark datasets, evaluates key performance metrics, and outlines critical challenges. It concludes with a forecast of emerging paradigms—such as transformer-based vision models and neuromorphic computing—that promise to redefine the future of intelligent visual systems.

 

 

Published by: vikaspatanker

Authors: R.Aswathi, Dr.Karthikeyan S, K.Mehar Banu, Dr.Manimegalai R M.

 

 

Abstract: The platform’s intuitive user interface is designed for ease of use by This paper presents the design and development of a Digital Log Website tailored for biotechnology laboratories, aimed at enhancing the accuracy, efficiency, and compliance of scientific data documentation. In many research and clinical environments, traditional paper-based lab notebooks remain the norm, despite being prone to a variety of issues including data loss, transcription errors, lack of standardization, and limited accessibility across teams. These limitations pose significant challenges for reproducibility, collaboration, and regulatory compliance. The proposed digital log system offers a centralized, web-based platform that addresses these challenges by enabling real-time data entry, seamless integration with laboratory instruments, and streamlined communication among team members. Built using modern cloud technologies, the system supports scalability, remote access, and automated backups, ensuring data integrity and availability. Key features include secure user authentication, role-based access control, version tracking, and comprehensive audit trails to meet regulatory standards such as FDA 21 CFR Part 11 and GLP requirements. Students and lab technicians, minimizing training time while maximizing productivity. By transitioning from paper to digital documentation, laboratories can significantly improve data about instrument , reduce data loss risks, and enhance overall record quality and compliance readiness.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Research Scholar Aman Malik

Abstract: The proliferation of cloud computing has revolutionized data storage, access, and management, but it has also introduced complex challenges concerning cross-border data flow and legal jurisdiction. As data transcends national borders, existing legal frameworks struggle to keep pace with the decentralized nature of cloud services. This paper examines the legal, technological, and regulatory implications of cross-border data flows within cloud infrastructures, emphasizing the tension between data sovereignty and global commerce. The study explores how different jurisdictions—particularly the European Union with the General Data Protection Regulation (GDPR), the United States with its sectoral approach, and emerging frameworks in Asia—address data localization, transfer mechanisms, and enforcement of jurisdiction. Through a comparative legal analysis, the paper highlights gaps, overlaps, and potential conflicts in international data regulation. It concludes with recommendations for harmonized legal standards, multilateral cooperation, and technologically adaptive policies to ensure secure, compliant, and innovation-friendly data ecosystems.

 

 

Published by: vikaspatanker

Authors: Research Scholar Aman Malik

Abstract: In an increasingly digitized world, data breaches and cybersecurity failures have emerged as significant legal and regulatory concerns for both public and private sector entities. This paper explores the legal implications associated with data security incidents, focusing on regulatory frameworks, liability issues, and enforcement actions in place prior to December 2018. Key legislation such as the European Union’s General Data Protection Regulation (GDPR), the United States’ sector-specific laws (including HIPAA and the GLBA), and emerging legal standards in Asia are examined. The study analyzes landmark data breach cases to highlight the evolving role of compliance, corporate responsibility, and the consequences of negligence in cybersecurity governance. It also discusses the legal challenges organizations face in cross-border data breaches and the implications for international cooperation. By assessing these issues through a legal and technological lens, the paper provides guidance on risk mitigation, legal preparedness, and the necessity for robust cybersecurity policies to meet growing regulatory expectations.

 

Published by: vikaspatanker

Authors: Alim Shaikh, Dr.Santosh Gaikwad, Dr. A. A. Khan, Dr. R. S. Deshpande

 

Abstract: Speech-based interaction with large lan- guage models (LLMs) is revolutionizing human-computer communication by enabling natural, voice-driven inter- faces. This study explores methods to prompt LLMs through automatic speech recognition (ASR) while ad- dressing challenges such as transcription errors, noise interference, latency, and prompt optimization. The proposed framework integrates ASR with LLMs using noise reduction, structured prompt engineering, and contextual adaptation. Experimental evaluations using models like OpenAI Whisper and GPT-4 demonstrate improvements in performance metrics such as Word Error Rate (WER) and response latency. Applications span healthcare, accessibility, and customer support, and future work will focus on expanding multimodal capabilities and enhancing ethical and energy efficiency aspects.

DOI: http://doi.org/

 

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Authors: Konka Kishan, Thuppathi Krishna Sree, Ramagiri Nissy Jasmine, Prathikantam Rakshitha

 

 

Abstract: Deep reinforcement learning (DRL) has excelled in video games but remains vulnerable to adversarial attacks. The project unveils Orthogonal Adversarial DRL (OADRL) to improve robustness in both discrete and continuous action spaces. OADRL integrates orthogonal regularization to limit overfitting and adversarial training to enhance resilience. The method assess against standard DRL models, measuring reward stability, adversarial robustness, and generalization. The project presents the OADRL reduces sensitivity to perturbations while maintaining high performance. OADRL improves robustness, ensuring smoother policies and greater resistance to adversarial noise. The insight highlight its potential for real-world applications like robotics and autonomous systems.

DOI: http://doi.org/

 

 

Published by: vikaspatanker