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588 articles for “computational modeling”
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Multi-phase Flow Simulation Using Computational Fluid Dynamics
Abstract: Computational fluid dynamics (CFD)-based multi-phase flow simulation is a fast developing topic with broad applications in many scientific fields and industry. An extensive account of current developments, difficulties, and uses in multi-phase flow simulations is given in this review paper. Important modeling strategies, numerical methods, validation procedures, and new developments in CFD-based multi-phase flow analysis are covered. This paper is to contribute to the ongoing development and use of CFD …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 28–34 Read article
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Comparative Cooling Analysis of EV Battery Packs using MATLAB Simscape
Abstract: Since electric vehicles (EVs) transition to high- voltage systems to enable quicker charging and enhanced delivery of power, the high heat emitted during rapid discharge is a significant challenge. This paper presents a direct comparative study of passive air cooling and active liquid cooling of a lithium-ion battery pack. Due to the high cost of constructing the physical prototypes, we created a computationally efficient and hierarchical virtual prototype in MATLAB …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 2, 2026 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Representation-Theoretic Symmetry Reduction and Fuzzy-Grey Optimization of Modular Vibration Systems
Abstract: This paper presents a representation-theoretic framework for symmetry-aware vibration control in modular structural systems. Exploiting cyclic symmetry, the mass, damping, and stiffness operators are block-diagonalised into irreducible representations, reducing the full structural dynamics to a collection of lower-dimensional modal subsystems. This decomposition provides both computational efficiency and a rigorous mathematical description of symmetry-preserving dynamic behaviour. To account for imperfections arising in practical implementations, near-symmetry defects in stiffness and damping are …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 22–30 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 Read article
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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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A Study on Precision Blood Propulsion in Motor-Driven Artificial Hearts
Abstract: The development of biocompatible, energy-efficient pumping mechanisms is pivotal for advancing artificial heart (AH) technology. This study explores a motor-driven centrifugal pump designed to replicate the physiological dynamics of natural ventricles while mitigating complications associated with conventional axial and pulsatile systems. The proposed system employs a brushless DC motor with closed-loop control, integrated with pressure and flow sensors to modulate rotational speed (RPM) and generate biomimetic cardiac output. The suggested …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 53–59 Read article
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Exploring the Dynamics of Memristors: Mechanisms, Models, and Multifaceted Applications
Abstract: Memristors, a fundamental electronic component first proposed by Leon Chua in 1971, have garnered significant attention due to their unique electrical behavior and promising applications in various fields. This paper provides a comprehensive overview of memristors, covering their basic principles, characteristics, fabrication methods, and applications of Memristor and it’s significance with flux charge linkage. The paper also shows study of a grounded memristor emulator and it’s working as a memristor …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
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An Evaluation of Versatile CNC Machines for Tabletop Applications
Abstract: The tabletop CNC provides a comprehensive analysis of computer numerical control (CNC) machines tailored for tabletop use. In today's rapidly evolving manufacturing landscape, compact and adaptable CNC systems have gained prominence due to their potential to revolutionize small-scale production and prototyping. This research examines a range of versatile CNC machines, assessing their capabilities, precision, ease of use, and suitability for various tabletop applications. By exploring key factors such as size, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 88–104 Read article
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Virtual Reality Horror Chronicles: Exploring Fear in Virtual Reality
Abstract: Virtual reality (VR) provides a distinctive and immersive experience, enabling users to engage in digital environments in an exceptionally realistic manner. It offers a sense of presence and immersion, making users feel as though they are physically present within a virtual world. Games can be single-player or multiplayer, and they often involve challenges, objectives, or narratives for players to engage with. Gaming is a powerful tool for promoting VR technology …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 32–43 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 Read article
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Analyzing Cavitation in Marine Propeller: A Computational Approach with Consideration for Polymer Applications
Abstract: A major source of noise and blade damage in marine propellers is because of the phenomenon of hydrodynamic cavitation. The Computational Fluid Dynamics (CFD) analysis approach is employed for the prediction of the cavitating propeller’s performance characteristics under various conditions of operation with the advance coefficient (J) ranging from 0.55 to 0.91 and cavitation number (σ) in the range of 0.80 to 4.50. The numerical simulation is performed on INSEAN …
Published in Journal of Polymer & Composites · Vol. 12, Issue 8, 2024 · pp. 29–44 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article