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35 articles for “UCS”
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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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Experimental Study on Heart Disease Prediction Using Different Machine Learning Algorithms
Abstract: Heart disease which can also be referred to as the cardiovascular disease is one of the raising concerns in today’s world. It is one of the major health problems causing death among humans irrespective of the age group and therefore has made it necessary to look into different medical factors that are required to predict the same in advance using the collected historical datasets of various patients. Thus we have …
Published in Journal of Artificial Intelligence Research & Advances Read article
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An Overview of Spam Detection Techniques
Abstract: Spam is also known as unsolicited commercial email (UCE) has become a major worry for the internet's and worldwide commerce's long-term viability. Fake emails and other forgeries, such as phishing, are examples of spam emails. Which aim to collect confidential personal information about users on the network or to act illegally against authority. Spam produces a variety of issues, which can result in financial losses. Spam creates bottlenecks and traffic …
Published in Journal of Advancements in Robotics Read article
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An Approach for Travel Pattern Analysis Using HDBSCAN and Apriori Algorithms
Abstract: Most mega-city regions around the world are suffering from an ongoing increase in the number of commuting trips. Understanding commuting patterns is crucial for both public and authority planners. The understanding of travel patterns helps passengers to know about the places and the time where they could get vacant transport and also helps authority planners in laying out a new transport service. The traditional way of understanding travel patterns includes …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
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Stabilization of Heavy Metal Sludge to Pass the TCLP Test Using Cement with a Sinter as a Additive
Abstract: According to the U.S. Stabilisation is the best-proven technology now in use, according to the Environmental Protection Agency's definition in Title 40, Part 268 of the Code of Federal Regulations (40 CFR 268).This method prevents harmful contaminants from leaking into the environment by physically and chemically trapping them all in a matrix. The investigations used 15 different water-mixed combinations of cement, fly ash, sinter, and lime. The study also examined …
Published in Journal of Polymer & Composites · Vol. 11, Issue 10, 2023 · pp. 16–24 Read article
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Ulcerative Colitis- An Ayurvedic Review And Treatment – A Case Study
Abstract: Ulcerative colitis (UC) is a chronic autoimmune disease that causes inflammation and ulcers of the Large intestine. It is one of the most common GI disorder. Usually the pain affects only the intestinal mucosa and sub mucosa, causing small ulcers in the intestinal lining called ulcers. In most of patients, the disease begins from the anus and continues to spread. Its pathogenesis is multi factorial and includes genetic predisposition, epithelial …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2024 · pp. 31–39 Read article
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Machine Learning Approaches for Phishing Detection: A Comparative Study
Abstract: These days, everyone has an internet addiction. All of us have used the internet for banking, booking, recharging, and buying. Phishing is a type of website threat that exists online. On the original website, phishing is an attempt to illegally obtain information such as login ID, password and credit card information. In this research, we proposed an efficient phishing detection system based on machine learning. Overall, the experimental findings demonstrated …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 35–45 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Unified Web Solutions: Video Conferencing, Summarization, Collaboration, and Tech Media
Abstract: This paper presents the development and implementation of a versatile web-based application suite designed to enhance virtual collaboration and learning experiences. The suite consists of four main applications: uTalkApp, a video conferencing platform; uCoLabCanvas, a collaborative design tool; uTechMedia, a curated video content hub; and Synopsizer, an article summarization tool. Built using modern technologies such as Next.js, TypeScript, and Tailwind CSS, and hosted on Vercel, each application aims to address …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Integrative Network Biology Analysis of GSE6011 Uncovers Molecular Signatures in Duchenne Muscular Dystrophy
Abstract: Duchenne muscular dystrophy (DMD) is a rare, severe neuromuscular disorder demonstrated by progressive skeletal muscle deterioration and premature mortality. Despite advances in supportive care, no definitive cure exists, highlighting the need to explore novel molecular targets. The current study aimed to uncover key dysregulated genes and molecular pathways in DMD through a dataset-specific network biology approach. Publicly available microarray data (GSE6011) from DMD quadriceps muscle biopsies of 22 patients and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 36–48 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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AL6061/Al2O3-Ash Reinforced Composites: An Experimental and Statistical Study Using Ultrasonic Stir Casting
Abstract: This study presents an experimental investigation on the influence of fly ash particle size on the mechanical properties of aluminum alloy (Al6061) composites fabricated through Ultrasonic Assisted Stir Casting. Fly ash, a low-cost and low-density by-product of thermal power plants, has emerged as an effective reinforcement material due to its excellent fluidity, high filling capability, and ease of processing. It has been increasingly utilized in metal, polymer, and rubber composites …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1123–1133 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Developmental Responses to Structured Training Loads in Competitive Youth Judo
Abstract: This study investigates the influence of a planned and regulated training-load structure on the physical and technical growth of elite youth Judoka aged 10 to 16. A four-week training program progressively modified the key variables of training intensity, frequency, and volume to support performance development while avoiding over-fatigue and injury. Ten athletes participated with performance assessed before and after training using tests for Muscular endurance, Core stability, Lower body explosive …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 07–15 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article