All articles
1036 articles
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Challenges, Risks, and Limitations of Vibe Coding in AI- Assisted Software Development
Abstract: Vibe coding a new way of programming driven by LLMs (Large Language Model).it helps developers to write code from natural language. Coders can use prompts to AI for there code generation. Ai assistant generate software directly threw the text. Now they are able to make tasks and understand the user requirements. This process make our development fast and easy for the developers. but vibe coding has some drawbacks sometime it …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Role-Based Online Food Ordering and Delivery System Using Django and Restful Architecture
Abstract: Traditional food ordering processes in restaurants rely heavily on manual interactions, including in- person ordering, phone-based bookings, and unstructured coordination between customers, restaurants, and delivery personnel. These approaches lead to inefficiencies such as delayed order processing, incorrect order handling, lack of real-time tracking, and poor coordination among stakeholders. Although modern applications exist, many academic implementations lack modular architecture, role-based access control, and scalable backend design. This paper presents the design …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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A Review on Tailor Craft E-Commerce: Design, Implementation and Evaluation
Abstract: The rapid growth of e-commerce has transformed how consumers purchase products and interact with businesses. In particular, the clothing and fashion industry has embraced digital platforms to extend its reach, improve accessibility, and offer convenience to customers. However, challenges such as unclear product information, insecure payment methods, poor user experience, and inefficient order tracking still limit customer satisfaction in many platforms. The Tailor Craft E-Commerce project aims to bridge these …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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IoT Based Home Automation System using ESP8266 & Google Assistant
Abstract: This research paper discusses a smart home automation system When the Internet of Things is implemented, a simple house can be converted into a smart home with better automation and security. This paper aims to create a voice/text- controlled home application that will help users control their appliances remotely. Switching appliances ON or OFF as per their requirements by just sending text SMS instructions or voice commands. Even if the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species
Abstract: The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems. Traditional phylogenetic methods are accurate but become more expensive when they are processing with thousands of marine taxa parallelly. This article shows a critical analysis of parallel greedy algorithms as an adaptable solution for large-scale marine phylogenetics. It examines the main principles of greedy …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 33–45 Read article
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A Comprehensive Study of Risk-Adaptive Access Control in Advanced Database Management Systems
Abstract: The current control methods for accession of a crucial resource often struggle to provide adequate security in dynamic and complex advanced database management systems (DBMS). These static models lack the flexibility to adapt to evolving threats and contextual changes, leaving potential vulnerabilities. Risk-Adaptive Access Control (RadAC) emerges as a sophisticated solution, integrating real-time risk assessment into authorization decisions to dynamically adjust access permissions. This review article provides a comprehensive study …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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The Evolution of Computer Languages: Fundamentals, Paradigms, and Consequences
Abstract: In today’s society, computers are important tools because they let us quickly analyze, store, and share information. A variety of programming languages that let people talk to machines are at the heart of how computers work. These languages, which are divided into low-level and high-level kinds, connect human logic and machine actions. Low-level languages such as machine code and assembly allow direct interaction with computer hardware. In contrast, high-level languages …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 16–28 Read article
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Comparative Study of BERT Variants for Sentiment Analysis with Error Analysis
Abstract: The use of media is going up fast in India, and this has led to the rise of Hinglish. Hinglish is an informal blend of Hindi and English that people commonly use in everyday conversations, especially across social media platforms such as Twitter, Facebook, and WhatsApp. People use Hinglish to talk to each other in a way that is not very formal. Hinglish blends English vocabulary with informal usage, often …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 39–48 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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A Systematic Literature Review on Security Challenges in Cloud–Edge Hybrid Systems
Abstract: Cloud–edge hybrid systems have become a key framework in today’s distributed computing landscape, combining fast, near-source data processing at the edge with the flexible scalability and resource richness of centralized cloud infrastructures. However, this in- tegration introduces a complex security landscape where tradi- tional perimeter- based cloud security measures are insufficient for resource- constrained and physically exposed edge nodes. This literature review synthesizes findings from established research publications (2020–2025), focusing …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Privacy and Security Enhancement in Mobile Ad Hoc Network (MANET) Using Information Hiding Techniques Based on Man-In-The-Middle Attack: A Review
Abstract: The mobile ad hoc network (MANET) is widely spread throughout the entire world for quick communication. MANET is a type of ad hoc network with specific features of independent direct connections between devices. The current MANET network is rapidly used in wireless communication in fast and easy access terms, but MANET has many weaknesses in privacy and security, which makes information leakage in unprotected communication. So, goals are the most …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 35–50 Read article
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A Review of Locking Protocols for Concurrency Control in Parallel Databases
Abstract: In modern database systems, many transactions may run at the same time. When several users try to access the same data or update the data simultaneously, then it creates a problem such as inconsistency data, lost updates or misinformation and may lead to conflicts between the transactions and deadlocks. To avoid these types of issues and maintain the correctness of the database, concurrency control protocols are mainly used. This paper …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 Read article