| 1 |
Author(s):
Vivek Singh.
Research Area:
Computer Engineering
Page No:
1-9 |
Integrated Strategies for Efficient Data Management in NoSQL Databases
Abstract
As data volumes continue to grow at an exponential rate, managing and storing this data efficiently has become increasingly crucial. NoSQL databases, with their ability to handle unstructured data, have emerged as a preferred solution, offering superior scalability and flexibility compared to traditional relational database management systems (RDBMS). Techniques such as deduplication (eliminating duplicate data) and data compression, when combined with powerful tools like Hadoop and MongoDB, help optimize storage and reduce network usage.
However, a key challenge in both NoSQL and SQL systems is managing schema evolution—adapting the database schema as application requirements change. This process introduces risks of downtime, data inconsistency, and disruptions to ongoing operations. The lack of a standardized approach to schema evolution often leads to inefficient management, particularly as systems scale.
This paper reviews current methods used to address these challenges and highlights gaps in existing solutions. While some strategies attempt to automate schema changes or handle schema migrations in a way that reduces disruption, they often fall short in ensuring seamless transitions and maintaining data integrity. The paper proposes an integrated approach to schema management that combines the strengths of both NoSQL and SQL systems. By enhancing schema migration processes and focusing on consistency and downtime reduction, this approach aims to improve overall data management, providing a more reliable and efficient solution across diverse database environments.
| 2 |
Author(s):
Dr. Priya Sharma.
Research Area:
Computer Science
Page No:
10-21 |
Transforming Banking through Artificial Intelligence: Enhancing Service, Efficiency, and Security for the Digital Age
Abstract
This article examines the transformative role of Unified Communications (UC) in the banking sector, focusing on enhancing customer experience and improving operational efficiency. It explores how AI technologies, such as machine learning, natural language processing (NLP), and computer vision, are revolutionizing banking operations by streamlining service delivery and boosting productivity. These technologies enable advanced customer service solutions, such as personalized banking experiences and virtual assistants, which enhance accessibility for diverse populations.
The article also highlights key challenges in implementing AI, including regulatory compliance, data security, and change management. It discusses how banks are navigating these issues while integrating AI systems to improve both customer service and internal operations. Notably, the use of personalization engines has significantly boosted customer satisfaction, while AI-driven automation has improved team collaboration and resource management.
Looking to the future, the article explores emerging technologies such as quantum computing and edge computing, which are expected to further advance the banking sector’s capabilities. These innovations, combined with next-generation communication technologies, promise to reshape how banks deliver services and interact with customers. The article underscores the growing importance of AI and UC in driving both customer-centric solutions and operational advancements in the banking industry.
| 3 |
Author(s):
Dr. Vijay Kant Pandey, Dr. Mousumi Ghatak, Dr. Timbrel Menen Tigga.
Research Area:
Biotechnology
Page No:
22-27 |
Glycobiology of Neurodegeneration: Implications of Aberrant Glycosylation in Alzheimer’s Disease
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative illness in the world. It is caused by the buildup of amyloid-β (Aβ) plaques and hyperphosphorylated tau neurofibrillary tangles. These protein clumps have been the main focus of treatment research, but new evidence reveals that abnormal protein glycosylation is a key part of the development of Alzheimer's disease. Glycosylation is the process by which enzymes attach carbohydrate groups to proteins. This process controls how proteins fold, how stable they are, where they are located, and what they do. This review looks at the growing evidence for dysregulated glycosylation in Alzheimer's disease (AD), with a focus on important pathogenic proteins like amyloid precursor protein (APP), tau, and other related components. We look at how changes in glycosylation patterns lead to neurodegeneration and talk about how addressing glycobiological processes could help treat Alzheimer's disease.
| 4 |
Author(s):
Manish Kumar.
Research Area:
Civil Engineering
Page No:
28-34 |
Artificial Intelligence in Civil Engineering: Innovations and Applications
Abstract
Civil engineering is an expansive discipline focused on the design, construction, and upkeep of infrastructure and the built environment. Yet, certain complex topics within civil engineering present significant challenges in traditional classroom settings. While engineers trained in conventional educational environments once struggled with these intricacies, the rapid advancement of artificial intelligence (AI) technologies is now reshaping the learning landscape. AI is increasingly revolutionizing civil engineering education, providing novel methodologies to enhance curricula and pedagogical strategies for improved learning outcomes. As a powerful tool, AI aids in optimizing design processes, predicting material behavior, and boosting the overall performance of civil systems. The integration of AI into civil engineering education represents a transformative shift, introducing innovative approaches to both teaching and practical applications in this essential field. This paper conducts a comprehensive review of AI’s diverse applications in civil engineering, covering areas such as structural health monitoring, smart infrastructure management, geotechnical analysis, transportation planning, environmental sustainability, Building Information Modeling (BIM), and construction project management. Through a systematic analysis of relevant literature, the paper explores the role of AI-driven technologies—such as image processing, machine learning, and deep learning—in reshaping educational strategies and preparing the next generation of engineers to tackle the growing challenges of infrastructure development and maintenance. The paper highlights the potential of AI to foster experiential learning, encourage interdisciplinary cooperation, and provide valuable insights for educators, policymakers, and industry stakeholders striving to leverage AI’s capabilities within civil engineering education.
| 5 |
Author(s):
Dr.Sanjeev Gill.
Research Area:
Civil Engineering
Page No:
35-41 |
The Implementation of Hydropower Electric Generation That Is Able to Be Sustained Well into the Twenty-First Century
Abstract
Hydropower supplied about 71 % of the world’s renewable electricity in 2016, making it the dominant renewable source at that time. In Europe and North America, the boom years for dam construction were roughly 1920 to 1970; since most prime sites are now occupied and social environmental costs have risen, both regions are dismantling more dams than they build. From the 1970s onward, developers shifted their attention to large rivers in lower income regions—especially the Mekong, Amazon, and Congo—where new projects often come with familiar downsides: altered river ecology, deforestation, diminished aquatic and terrestrial biodiversity, greenhouse gas emissions from reservoirs, mass displacement, and major disruptions to local food systems, water quality, and agriculture.
This paper reviews the surge in large scale dams across the Global South; evaluates how climate change projections should shape siting decisions; and discusses persistent governance gaps, compensation shortfalls, and the tendency to overstate benefits while downplaying true costs. Finally, it outlines design and policy adjustments—such as pairing hydropower with solar, wind, and other renewables—that could help the sector deliver electricity with far lower social and environmental impacts.
