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567 articles for “model evaluation”
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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The Integrity of Eadic-Hofstee Plot Model to Predict the kinetic Parameters of Crude Oil Degradation using Vernonia amygdalina Stem
Abstract: The integrity of Eadic-Hofstee concept was tested for the determination of the functional coefficients and parameters of crude oil degradation kinetics. The techniques enhanced the relationship between the substrate divided by the specific rate of the substrate degradation against substrate concentration (TPH). The investigation reveals the values of the biokinetic parameters of maximum specific rate of substrate degradation (Vmax) and the equilibrium constant values of the substrate degradation (Ks). The …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 37–47 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Role of Organizational Culture in Mediating AI-Induced Social Alienation: A Meta-Analysis
Abstract: The fast adoption of artificial intelligence (AI) in the workplace has raised worries about its influence on employee well-being, particularly social alienation. Social alienation is characterised by feelings of detachment and estrangement at work. It can harm job satisfaction, staff engagement, and organisational performance. Existing literature suggests that organizational culture is crucial in shaping employee experiences with AI technologies. This meta-analysis investigates how organizational culture mediates the relationship between AI …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 28–33 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Design and Development of an Electromagnetic Propulsion Train
Abstract: The recent advancement of new transportation techniques led to the search for methods of propulsion that were superior to classical mechanical systems. Among these new moments, electromagnetic propulsion (EMP) has attracted attention because this technique allows for motion generation via electromagnetic force without using conventional wheel-based friction processing. The paper describes the conceptual design, principle of working and performance evaluation of a prototype model train to be propelled electromagnetically.The system, …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 19–24 Read article
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AI Evaluator – Automated Examination Evaluation
Abstract: An AI system for automated exam grading is proposed. It tackles inefficiencies in human evaluation. The system uses TrOCR for accurate handwritten text recognition and a GPT model trained on graded responses for evaluation. This approach offers efficiency and reduced bias, but challenges remain. Evaluating open-ended questions and ensuring explainability require further development. It starts by looking at how AI technologies, such as machine learning, deep learning, and natural language …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
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Optimizing Cellular Manufacturing Systems: Minimizing Production Time with Collaborative Robots (Cobots) using PSO
Abstract: This study focuses on the implementation of cobots in a cellular manufacturing system to minimize production time. The use of cobots, collaborative robots capable of working alongside human operators, aims to increase efficiency and reduce manual labor in the manufacturing process. The mathematical model presented in this research evaluates the impact of cobots on production time by considering various factors, including task times, machine setup, inspection, waiting, and idle times. …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 22–27 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Magnetorheological Composite Dampers for Railway Wagon Suspension: Modelling Validation and Performance Analysis
Abstract: Railway wagons encounter continuous vibrations due to track irregularities, resulting in reduced ride comfort and higher dynamic loads. Conventional suspension systems based on springs, hydraulic dampers, or air suspensions provide only limited vibration mitigation. This work investigates the application of magnetorheological (MR) fluid-based dampers, where a polymeric carrier oil (silicone oil) reinforced with carbonyl iron particles serves as a smart composite suspension medium. The MR fluid is synthesized and characterized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 43–63 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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Comparison Analysis of Transformer Boosting and Induced Degeneration Topology Design of LNA for Millimeter Wave Frequency Range Using Polymeric Substrates
Abstract: In this study, a comparison between transformer boosting and source degeneration LNA topologies is conducted using two polymeric substrates—Polyimide (PI) and Liquid Crystal Polymer (LCP)—for millimeter-wave (mmWave) applications. With growing interest in flexible and high-frequency electronics, polymeric materials offer unique advantages such as low dielectric constants, mechanical flexibility, and thermal stability. The analysis explores gain, return loss, and noise figure performance while evaluating the influence of dielectric properties on the …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 1–24 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Use of the Computer Statistics in Oncology
Abstract: Currently, the use of computer statistics and computer statistical modeling in oncology for obtaining an accurate diagnosis, determination of the choice of treatment method and its correction in the process of ongoing treatment, prediction of the outcome of the disease, and evaluation of the effectiveness of the chosen treatment tactics is a decisive factor. The use of computer statistics, based on an adapted scientific and statistical package of the SSP …
Published in Research & Reviews : Journal of Statistics Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article