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70 articles for “model selection”
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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
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Machine Learning Innovations for Effective Spam Comment Filtering in Social Networks
Abstract: The increasing prevalence of social media platforms has revolutionized communication, fostering unparalleled levels of connectivity and data exchange. However, the widespread increase in spam comments presents a serious threat to the integrity of online discussions, potentially undermining the quality of interactions. To confront this issue, our proposed model utilizes machine learning techniques to bolster spam comment detection across various social media platforms. This endeavor involves a thorough investigation encompassing data …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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Zebra Fish Embryo Assay: A Wonderful Tool for Ecotoxicological Risk Assessment with Special Reference to Heavy Metals - An Overview
Abstract: In recent years, environmental pollution has become a pressing concern, prompting extensive research in aquatic ecotoxicology. With environmental degradation getting worse day by day, ecotoxicology research has gained a lot of attention. This area of study examines how biological communities in aquatic environments are affected by environmental contaminants. To unravel the toxicological mechanisms of these exogenous compounds, scientists turn to biological models. Several aquatic species, including zebrafish, toads, and big …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 2, 2025 · pp. 56–70 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Cost Model of Acquisition and Merger in Construction Industry
Abstract: Merger and Acquisition in India is at an all-time high with more buyers now than before; it has been accounting for 80% of closed deals in 2020–2021, up from 70% in 2017–2019. To determine the Merger and Acquisition of the company, this article explores the main factors in the Merger and Acquisition process. And also study the main framework of the Merger and Acquisition. And, also, the article discusses the …
Published in International Journal of Architectural Design and Planning Read article
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Comparative Analysis of Kinetic Models for Simulation of Biogas Production from Cow Dung and Fruit Waste via Anaerobic Digestion
Abstract: This study investigates the optimization of biogas and biofertilizer production from cow dung and fruit waste through anaerobic digestion, utilizing various microbial growth kinetic models. Simulations were conducted using the Monod, Moser, Contois, and Tessier models to predict biogas yield and assess model accuracy. Results indicated that the Tessier model provided the closest fit to experimental data, with a biogas yield of 0.45 m³/kg VS, while the Monod model overestimated …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 47–63 Read article
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Research on Selection Method of the Optimum Alternative Using Improved AHP Method in NSDL Environment
Abstract: In this paper, we have considered the development of a decision-making tool to optimize the design of the ship-roll fin stabilizer using improved analytical hierarchy process (AHP) in a network-oriented system description language (NSDL) environment developed by combining the advantages of Petri nets and object-oriented programming languages. First, we have considered the network-oriented system description language NSDL, a new software development tool that combines the advantages of Petri nets and …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 1, 2025 · pp. 46–56 Read article
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QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Integrating Plant Selection, Planting Design, and Landscape Construction for Sustainable Site Development
Abstract: This paper explores the interrelationship between plant selection, planting design, and landscape construction in achieving ecologically sustainable and aesthetically pleasing outdoor environments. Plant selection involves choosing species that are well adapted to site conditions, ecological functions, maintenance regimes, and visual preferences. Planting design refers to the arrangement, composition, and spatial organization of plant materials to meet functional, aesthetic, and environmental objectives. Landscape construction encompasses implementation—from site preparation and planting through …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Emerging Trends in Membrane-Based Gas Separation Technologies
Abstract: Membrane technology has emerged as a groundbreaking solution in various fields, revolutionizing industries such as water treatment, energy production, biomedicine, and environmental protection. Over the past few decades, significant advancements have been made in membrane materials, fabrication techniques, and performance optimization. With the growing global demand for efficient and sustainable separation processes, research has increasingly focused on enhancing membrane permeability, selectivity, and durability to improve performance across various industries, including …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 16–22 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Impact of Topical Pure Honey Application on Radiation-induced Oral Mucositis in Patients Receiving Radiation Therapy
Abstract: This quasi-experimental study assessed the effects of pure honey on radiation-induced oral mucositis in patients with head and neck cancer undergoing radiation therapy in Kottayam. The primary objectives were to evaluate the severity of oral mucositis in both experimental and control groups, determine the effectiveness of honey in alleviating symptoms, and examine the relationship between mucositis severity and selected demographic variables. Utilizing Bertalanffy’s General System Model as a conceptual framework, …
Published in International Journal of Oncological Nursing and Practices · Vol. 2, Issue 2, 2024 · pp. 14–18 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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Influence of Mechanical Parameters on Corrosion Behavior of Metal Coupons in Simulated Environmental Conditions
Abstract: This study investigates the influence of mechanical parameters—namely applied stress, surface roughness, and deformation history—on the corrosion behavior of metal coupons exposed to corrosive environments. Mild steel and aluminum alloy specimens were prepared with controlled variations in tensile stress, polishing grades, and cold-working levels to simulate real-world mechanical influences. These coupons were immersed in a 3.5% NaCl solution under ambient conditions, and their corrosion rates were monitored over a 30-day …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 6–12 Read article
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Development of Automobile Scaled Model from CAD (Blender) Using FDM 3D Printing
Abstract: Additive manufacturing (AM), also known as 3D printing, has emerged as a disruptive technology with the potential to transform automotive manufacturing. This paper reviews the applications of AM across the automotive product development lifecycle. The paper examines case studies demonstrating the use of AM for developing computer-aided design (CAD) models from concept sketches. Overall, AM brings several benefits such as design flexibility, faster time-to-market, and distributed production. However, there are …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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A Comparative Analysis of Factors Contributing to Relapse in Alcohol and Opioid Dependence Among Patients Admitted to Selected Hospitals in Ludhiana, Punjab.
Abstract: Introduction: Substance abuse involves the dangerous or detrimental use of psychoactive substances, such as alcohol and illegal drugs. The use of these substances can result in dependence syndrome, which encompasses a range of behavioral, cognitive, and physiological effects that arise from ongoing substance use. Objectives: This study was carried out to examine the factors linked to relapse in alcohol and opioid dependence among patients admitted to selected hospitals in Ludhiana, …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article