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57 articles for “Validation of Experiments”
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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Design, Mathematical Modeling, and Dynamic Optimization of a Speed Breaker-Based Vehicular Kinetic Energy Harvester
Abstract: Decentralized energy harvesting methods are becoming more popular due to rapid urbanization and the rising need for sustainable infrastructure. The road-embedded vehicle kinetic energy harvester (VKEH) design, mathematical modelling, and experimental validation are presented in this work. This paper presents the structural engineering, continuum mathematical modeling, and experimental validation of an optimized road-embedded vehicular kinetic energy harvester (VKEH). The mechanism utilizes a spring- loaded, low-friction rack-and-pinion transmission coupled with a …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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InSilico Analysis and Homology Modeling of Tetrahydroprotoberberine Oxide involved in the Berberine Biosynthesis
Abstract: Objective: Berberine, a bioactive compound found in various plant species, exhibits diverse pharmacological properties with potential applications in pharmaceutical research. The biosynthesis of berberine involves several enzymatic steps, with (S)-tetrahydroprotoberberine oxidase playing a pivotal role. This study aimed to elucidate the structural and functional characteristics of (S)-tetrahydroprotoberberine oxidase to better understand its role in berberine biosynthesis and its potential biotechnological applications. Methods: Using bioinformatics tools and computational methods, the physicochemical …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 7–26 Read article
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Exploring Potential Phytochemicals for Myasthenia Gravis Treatment: A Molecular Docking and ADME Analysis Approach
Abstract: Objective: Muscle feebleness and exhaustion derived from a disruption in neuromuscular transference are hallmarks of the crippling autoimmune disease myasthenia gravis (MG). The drawbacks of the current MG therapy options are frequently partial efficacy and adverse effects. To investigate the potential of phytochemicals in MG control, in this work we integrated molecular docking with ADME (absorption, distribution, metabolism, and excretion) analysis using a computer method. We identified molecules exhibiting favorable …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 1–13 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 Read article
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Molecular Docking Analysis of Phytocompounds from Ficus hispida Aagainst Epidermal Growth Factor Receptor Kinase Domain
Abstract: The Epidermal Growth Factor Receptor (EGFR) kinase domain plays a key role in cancer, as it promotes tumour growth and helps cancer cells survive, making it an important focus for developing treatments. Through comprehensive computational analysis, this study investigates the anticancer potential of phytocompounds from Ficus hispida, a medicinal plant renowned for its diverse bioactive compounds, as novel EGFR inhibitors. Molecular docking techniques using Py Rx software were employed to …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 Read article
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Molecular Docking Analysis of Phytocompounds from Ficus hispida Against Epidermal Growth Factor Receptor Kinase Domain
Abstract: The Epidermal Growth Factor Receptor (EGFR) kinase domain plays a key role in cancer, as it promotes tumour growth and helps cancer cells survive, making it an important focus for developing treatments. Through comprehensive computational analysis, this study investigates the anticancer potential of phytocompounds from Ficus hispida, a medicinal plant renowned for its diverse bioactive compounds, as novel EGFR inhibitors. Molecular docking techniques using Py Rx software were employed to …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 48–62 Read article
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Rainwater Measuring Algorithm in O(1) Time Complexity
Abstract: The Rain Terraces Time Complexity Data Structure Algorithm (RTTCDSA) introduces a novel method for managing temporal data efficiently, inspired by the natural flow of rainwater on terraced landscapes. This study presents the conceptual framework and implementation details of RTTCDSA, which leverages principles of temporal dynamics and landscape morphology to organize and query temporal data with optimal time complexity. RTTCDSA employs a hierarchical structure akin to terraced landscapes, facilitating rapid traversal …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 26–32 Read article
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Design and Optimization of Radial Turbines for Waste Heat Recovery Applications
Abstract: Waste heat recovery (WHR) offers a compelling way to improve sustainability and energy efficiency in several different industrial sectors. In waste heat recovery (WHR) systems, radial turbines are essential because they capture waste heat and transform it into useful mechanical or electrical energy. A thorough summary of the design and optimization concepts guiding radial turbines for WHR applications is given in this review article. After outlining the basic concepts of …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 52–58 Read article
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Gene prioritization of colorectal cancer using computational approach
Abstract: Colorectal cancer (CRC) continues to be a major worldwide health issue, underscoring the need to pinpoint crucial genetic elements influencing its initiation and advancement. In this investigation, we utilize sophisticated computational methods to prioritize potential genes linked to CRC development. Through the utilization of various bioinformatics tools and comprehensive methodologies, we systematically examine extensive microarray datasets to identify potential genetic contributors. Initially, a vast amount of CRC microarray data (approximately …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 39–52 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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A Review of Drug Design Techniques Assisted by Computers to Combat Diabetes
Abstract: Diabetes mellitus is a global health concern characterized by chronic hyperglycemia and associated complications. The creation of innovative medicines with enhanced efficacy and safety profiles continues to be a top focus, notwithstanding improvements in treatment. A useful method in drug development, computer-aided drug design (CADD) makes it easier to identify possible therapeutic candidates and optimise lead molecules. An extensive synopsis of CADD tactics used in the fight against diabetes is …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 1–10 Read article
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Comparative Analysis of Energy Storage System’s Hybridization for Electric Vehicles: Evaluating Lithium-Ion Batteries, Supercapacitors, and Fuel Cells on Performance Metrics
Abstract: High-performance energy storage systems (ESS) in electrically powered cars are becoming more and more necessary as transportation options become more environmentally conscious. This research provides a thorough comparison of hybrid energy storage systems (HESS) that link fuel cell technology, supercapacitors, and batteries made of lithium ion. Critical performance metrics are assessed for each technology, including energy density, power density, efficiency, lifecycle durability, thermal performance, cost and sustainability. It summarizes the …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 1, 2025 · pp. 12–29 Read article
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Optimization of Process Parameters for AISI 304 Using Micro-EDM Drilling Process Through Response Surface Method
Abstract: The increasing demand for micro-parts in high-tech products, such as micro-electromechanical systems (MEMS) applications and micro-electronic devices, has driven significant advancements in micromachining technologies. Among the various micromachining processes, the fabrication of accurate microholes and pins is critical for the performance and reliability of miniature components. Micro-hole drilling plays a vital role by enabling the production of deep holes with excellent straightness, roundness, and surface quality. It is widely used …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 37–47 Read article
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An Integrated Autonomous Rover-Drone System for Intelligent Exploration and Environmental Monitoring
Abstract: This paper presents a hybrid autonomous exploration platform integrating a ground rover and aerial drone, enhanced by swarm intelligence and a custom-trained YOLO V8 object detection model. The rover is equipped with GPS, IMU, and environmental sensors (DHT11, MQ135, BMP180), while the drone performs real-time aerial mapping and obstacle prediction. A YOLO V8 model, trained on 500 annotated terrain images (six classes: rocks, pits, trees, water, animals, vegetation), achieves a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Smart Monitoring and Controlling of the Battery and Motor
Abstract: The demand for effective battery and motor monitoring and management to guarantee dependability, safety, and peak performance has increased due to the quick development of electric vehicles and smart industrial systems. The smart monitoring and control methods used in battery management systems and motor control systems are thoroughly reviewed in this paper. In addition to speed, torque, efficiency, and fault situations in motors, it emphasizes important characteristics like temperature, voltage, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 11–15 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article