Volume 13 | Issue 6 |

 Abstract

The exponential growth of textual data in cloud environments, particularly in applications like Vision-and-Language Navigation, poses critical challenges for storage efficiency and data confidentiality. Traditional deduplication techniques reduce redundant data but compromise security by exposing sensitive information. To address this, we propose DEDUCT, a secure and efficient hybrid deduplication system that combines client-side preprocessing and encryption with server-side content-defined chunking and storage optimization. DEDUCT ensures confidentiality through convergent encryption, enabling deduplication over encrypted data while resisting side-channel attacks. Experimental evaluation on benchmark textual datasets demonstrates a compression rate of up to 66% without sacrificing data security. The system supports multiple file types, secure file sharing, and role-based access control, making it highly suitable for resource-constrained devices and modern cloud infrastructure. This approach achieves a balance between security and storage efficiency, paving the way for secure file handling in large-scale cloud systems.

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 Keywords

Deduplication, Cloud Security, Convergent Encryption, Textual Data, Storage Optimization, Confidentiality, Role-Based Access, IoT.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Additive Manufacturing (AM), commonly known as 3D printing, has emerged as a disruptive technology for fabricating intricate metallic components across various industries. This review provides a comprehensive overview of the current state of metal AM, covering fundamental principles, prevalent processes, material diversity, design considerations, post-processing techniques, defect analysis, and a survey of key applications. By synthesizing insights from recent research and established literature, this paper aims to be a valuable resource for researchers, engineers, and practitioners seeking to understand and advance the field of metal AM.

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 Keywords

Additive Manufacturing, Metal Components, 3D Printing, Powder Bed Fusion, Directed Energy Deposition, Materials, Applications, Defects, Post-Processing.

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 Abstract

The Medicine Smart Box is a helpful device and app designed to make managing daily medicines easier and safer for patients and their caregivers. With the Android app, users can add their medicines, set reminders to take each dose on time, quickly save medicine details like expiry dates. The app keeps an eye on these dates and alerts users before any medicine expires, so they don't accidentally take old medicine.It also tracks how much medicine is left and sends alerts when supplies are running low, helping people remember to refill their medicines on time. This is especially useful for elderly people or those with long-term health needs.The smart box itself has an emergency button that, when pressed, sends a quick alert via SMS to the user's family, so help can come fast if needed.Overall, the Medicine Smart Box and app help people take their medicines properly, avoid expired drugs, keep track of their medicine supply, and get emergency help if necessary making healthcare safer and easier for everyone.

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 Keywords

Medication Management, Expiry Date Tracking, Reminder Alerts, Stock Monitoring, Emergency Assistance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Quantum computing is a cutting-edge domain that will transform the realm of computation. classical computing relies on binary bits for calculations, quantum computing uses quantum bits i.e qubits and takes advantage of principles from quantum mechanics, such as superposition and entanglement. This research paper covers the main characteristics of quantum computing and algorithms, their applications, current limitations, and potential future developments. It elucidates quantum algorithms for the tasks of optimizing searches and factoring large integers, as well as their potential effects on machine learning, cryptography and solving complex problems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Quantum Computing, Qubits, Superposition, Quantum Entanglement, Quantum Algorithms, Characteristics, Functioning of quantum computing, Prospects of quantum computing, Future potential.

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 Abstract

As we know, the machine learning field has been continuously evolving and Kolmogorov-Arnold Networks (KANs) have caught the attention of many researchers recently due to their performance and profound applications in mathematical and physics problems. These networks have been originated from the theorem of Kolmogorov Arnold and dominated traditional machine learning models. These networks have been equipped with dynamic adaptable and learnable univariate parameters and replacing traditional networks having fixed learnable weights. A lot of variants of KAN are already in use such as Graph KAN, Temporal KAN, Convolutional KAN, Rational KAN, etc. With the objective of assisting the keen researchers to navigate this complex field of KAN, this article aims to provide an in-depth study of various KAN architectures and discusses future potential applications of KAN in computer vision and other domains.

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 Keywords

KAN, Kolmogorov Arnold Network, Deep Learning, Computer Vision

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Land-cover classification is one of the core applications in the field of remote sensing. It is a valuable resource for city planners to achieve sustainable development. Many metropolitan cities are experiencing disorganized growth with a high intensity of urban sprawl due to the economic pull and better standards of living offered in metropolitan cities when compared to the surrounding rural areas. If this pattern of growth continues, it will lead to unsustainable development. This leads to an increase in pressure on urban infrastructure and the ecosystem. The traditional methods which are used for urban mapping are time consuming. Land Cover Semantic Segmentation is a process of developing an automated system for land cover classification. This system takes a multiband satellite image of an area as input and outputs the land cover map of the area at the same resolution as the input. For this purpose UNET models were trained in the task of predicting the land cover semantic segmentation of satellite images.

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 Keywords

deep learning semantic segmentation; LoopNet; Landsat 8; land use dataset; land use extraction; multispectral bands; Thailand;

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 Abstract

This study investigates the impact of macroeconomic and market-specific variables on stock returns, in addition to the effect of investment styles, i.e., value and growth investing. It focuses on the region, stock market and examines the risk and uncertainty in future markets through sensitivity analysis. The results provide valuable insights for investors, policymakers, and scholars. By analysing the influence of macroeconomic variables, including GDP, inflation, and interest rates, on stock returns and assessing the efficacy of various investment strategies, the research adds to the literature base on stock market behaviour and investment choice.

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 Keywords

Sensitivity analysis, robustness, stock market behaviour

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Coronary Artery Disease also called as Ischemic Heart Disease. It results from narrowing of the coronary arteries due to atherosclerosis. This is due to buildup of cholesterol and other materials, called plaque, on their inner walls. This buildup is called atherosclerosis. As it grows, less blood can flow through the arteries. As a result, the heart muscle can't get the blood or oxygen it needs. This can lead to chest pain (angina) or a heart attack. Over a time, CAD can also weaken the heart muscle and contribute to heart failure and arrhythmias. As of 2010, CAD was the leading cause of death globally resulting in over 7 million deaths. Males are affected more than females. 65 years male reported at a multispeciality hospital in southern part of kerala with the complaints of chest pain, nausea, light headache, fast heart rate for last 1 week. He had a past medical history of type 2 diabetes mellitus with hypertension. He was diagnosed with Coronary Artery Disease based on a blood tests and ECG. He was continuously monitored for 3 days and prescribed with medications. The patient was found stable, and he was discharged from the hospital with some discharge medications and patient advised to return for OPD follow up in 7 days.

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 Keywords

Coronary Artery Disease, Aspirin, Patient Counselling

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 Abstract

This research presents a comprehensive study of the geological and hydrogeological framework of the Bhopal region in central Madhya Pradesh. Bhopal's subsurface conditions are shaped by a complex geological history encompassing the Vindhyan Supergroup of sedimentary formations, Deccan Trap basaltic flows, and Quaternary alluvium. This paper delineates the lithostratigraphy, structural controls, and aquifer systems that define the region's groundwater regime. It investigates how topography, sedimentology, and tectonics influence aquifer characteristics and groundwater availability. Given the growing urban pressure and climate variability, the study emphasizes the need for sustainable groundwater management strategies informed by geological understanding. The findings can support integrated water resource planning, urban development, and climate adaptation in the region.

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 Keywords

Vindhyan Supergroup, Deccan Trap, Aquifer System, Hydrogeology, Urbanization, Groundwater Management

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 Abstract

Empowering students through targeted educational initiatives remains a cornerstone of inclusive socio-economic development. The Tamil Pudhalvan Scheme, launched by the Government of Tamil Nadu, is a strategic intervention aimed at bridging the financial gap faced by Tamil medium male students in pursuing higher education. This study explores the level of awareness, accessibility, and perceived effectiveness of the scheme among students in Coimbatore city. Employing a mixed-methods research approach, the study collected quantitative data through structured questionnaires from 120 respondents and qualitative insights via interviews with key stakeholders. The findings reveal that while a moderate awareness of the scheme exists, detailed understanding regarding eligibility, application procedures, and long-term benefits is limited. The study highlights that students from urban and better-educated families tend to benefit more, whereas rural and economically disadvantaged students face barriers due to limited awareness, infrastructure challenges, and poor institutional implementation. Overall, the Tamil Pudhalvan Scheme is seen as a promising initiative with considerable potential to enhance employability, reduce dropout rates, and promote skill development--provided its outreach and implementation mechanisms are further strengthened.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Education Policy, Awareness, Tamil Pudhalvan Scheme, Higher Education, Financial Assistance, Skill Development

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Creative Commons Attribution 4.0 and The Open Definition