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1673 articles for “identification”
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Diet-Gene Interactions in Farm Animals: Molecular Dynamics, Gene Expressions, Signalling Pathways and Precision Nutrition for Sustainable Productivity
Abstract: Diet-gene interactions represent a central mechanism through which nutrition influences growth, health, and productivity in farm animals. Recent advances in molecular biology and genetics have revealed that nutrients act not only as metabolic substrates but also as signalling molecules capable of modulating gene expression, cellular pathways, and epigenetic regulation. This review synthesizes current knowledge on the molecular dynamics of nutrient utilization in farm animals, with emphasis on nutrigenomic responses, nutrient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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A Legal Analysis of Contract Negotiations in Professional Sports
Abstract: Contract negotiations are crucial aspect of professional sports, involving complex legal considerations and complex interactions between athletes, agents and team owners. This article provides a comprehensive legal analysis of contract negotiations in professional sports, examining the role of collective bargaining agreements, individual player contracts, and agent-player relationships. Through a critical examination of relevant statutes, case law and collective bargaining agreements, this article identifies key principles and trends shaping contract negotiations …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 31–45 Read article
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Hybrid Graceful QoS Degradation in Distributed Operating Systems
Abstract: Maintaining Quality of Service (QoS) in distributed operating systems is a critical challenge, especially in dynamic and resource-constrained environments. Traditional QoS mechanisms often fail to adapt effectively to unforeseen failures or load spikes, leading to abrupt service disruptions. This study reviews the concept of hybrid graceful QoS degradation, a paradigm that combines multiple strategies to ensure continuous, albeit potentially reduced, service availability. By intelligently integrating techniques like resource reservation, priority-based …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Ethical Risks of Generative AI in Education: Challenges, Implications, and a Responsible Use Framework
Abstract: The rapid diffusion of generative artificial intelligence (AI) technologies in educational settings is reshaping how teaching, learning, and assessment are designed and enacted. Large language models and related generative systems offer powerful capabilities for content creation, personalized feedback, and instructional support, promising gains in efficiency and learner engagement. However, their growing use also introduces a complex set of ethical risks that challenge foundational educational values such as integrity, equity, transparency, …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 23–30 Read article
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Comprehensive Review of Composite Materials: Classification, Manufacturing Methods, Mechanical Behavior, Failure Modes, and Emerging Applications
Abstract: Composite materials have emerged as one of the most significant classes of engineered materials due to their ability to deliver high strength to weight ratios, enhanced durability, and tailored multifunctionality. Over the past two decades, rapid progress in polymer chemistry, advanced reinforcement architectures, additive manufacturing, and automated fabrication has expanded the applicability of composites across aerospace, automotive, biomedical, civil, and renewable energy sectors. This paper provides a comprehensive review of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 923–939 Read article
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Optimization of Sustainable Electrochemical Machining Parameters for Polymer based Materials Using AHP Integrated TOPSIS Method
Abstract: The current paper describes the use of the AHP-TOPSIS method to optimize process parameters in sustainable electrochemical machining of polymer composites. Combine lightweight polymer matrices with reinforcing particles or fibers such as TiB₂, SiC, or Al₂O₃, offering high strength-to-weight ratio, corrosion resistance, and design flexibility, making them ideal for aerospace and automotive applications. Non-conductive and heterogeneous nature poses challenges during electrochemical machining, as it affects current distribution and material removal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1048–1059 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Performance Evaluation of Oat (Avena sativa) Varieties for Growth, Yield, and Yield Components in Southwest Ethiopia
Abstract: The improved feed shortage is main bottleneck of livestock production and productivity in southwest Ethiopia. Hence, the study was conducted in Southwest Ethiopia in Kaffa zone Gimbo district in 2017 and 2018 cropping seasons to identify the adaptable and high yielding oat variety (s). The trial consisted of five oat varieties (CI-8250, CI-8237, CI-2291, CI-2806 and ICARDA 6710) which were laid out in randomized complete block design with three replications. …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 13–18 Read article
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A study on Antibiotic Resistance: An Analysis of Molecular Mechanisms and Therapeutic Implications
Abstract: Antibiotic resistance (AR) represents one of the most critical existential threats to global public health, rapidly eroding the efficacy of established antimicrobial therapies and portending a return to the pre-antibiotic era. This analysis explores the intricate molecular landscape defining this crisis, focusing specifically on the primary mechanisms of action (MoA) utilized by major antibiotic classes—including cell wall inhibitors, protein synthesis inhibitors, and nucleic acid synthesis inhibitors—and the corresponding, diverse mechanisms …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 9–21 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Vision Sense Rover
Abstract: This paper presents the design and implementation of an autonomous obstacle-avoiding robotic system utilizing an Arduino Uno microcontroller, an ultrasonic distance measurement module, a servo-based scanning mechanism, an L298N motor driver module, and an ESP32-CAM for real-time visual monitoring. The proposed system is developed to operate without human intervention, using sensor- driven decision making for navigation. The ultrasonic sensor continuously measures the distance to adjacent obstacles, while the servo motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 38–43 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Understanding India’s Sustainable Land Management Research Landscape: Productivity, Collaboration, and Emerging Themes (2016–2025)
Abstract: Sustainable Land Management (SLM) has emerged as a critical research domain in India due to increasing land degradation, climate variability, population pressure, and competing land-use demands. Understanding the evolution, structure, and impact of scholarly research in this field is essential for guiding future research and policy interventions. This study presents a comprehensive scientometric assessment of India’s SLM research output during the period 2016–2025. Bibliographic data comprising 1,560 records were retrieved …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 17–27 Read article
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Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Triple-Threat Analysis: Measuring Mythril, Slither and Oyente Against Real-World Smart Contract Vulnerabilities
Abstract: Smart contracts have become fundamental building blocks of blockchain ecosystems, yet their immutable nature makes security vulnerabilities particularly devastating. This pa- per presents a comprehensive evaluation of three prominent static analysis tools—Mythril, Slither, and Oyente—for detecting vulnerabilities in Ethereum smart contracts. Through systematic experimentation with real-world contract categories (voting sys- tems, land registries, and crowdfunding platforms), we quantify the effectiveness of each tool across eight critical vulnerability types, including reentrancy, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Intelligent Systems: A study on AI and Machine learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are dynamic branches of computer science that focus on developing systems capable of executing tasks commonly associated with human intelligence. These activities encompass making choices, resolving issues, understanding language, identifying patterns, and learning through experience. Artificial Intelligence refers to the broad area of designing systems and frameworks that enable machines to perform tasks resembling human thought and behavior. This field integrates diverse technologies …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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An Automated Smart Contract Repair Framework for Reentrancy, Integer Overflow, and Denial- of-Service Vulnerabilities
Abstract: This paper introduces a novel static analysis framework designed to bridge a long-standing gap in Ethereum smart contract security: the disconnect between vulnerability detection and automated remediation. Although widely adopted tools such as Slither and Oyente are highly effective at identifying security weaknesses, they stop short of providing actionable fixes. As a result, developers manually patch vulnerabilities, a process that is not only time-consuming but also susceptible to human error …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 31–41 Read article