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28 articles for “Error Reduction”
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The Strength of Dry, Fresh and Decomposed Raffia Palm Trunk in the Bioremediation of Oil-based Drill Cutting
Abstract: In this research, the impact of dry drill cuttings and compost tea on the environment's ability to degrade oil-based drill cutting contamination is investigated. The experiment was conducted in the research center located at the workshop of Agricultural and Environmental Engineering Department, Rivers State University, Port Harcourt. Oil-based drill cutting samples were placed in bulk in eleven reactors (T1, T2, T3-T11) with four replications. The original drill cuttings' physiochemical characteristics …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 3, 2024 · pp. 26–33 Read article
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The Influence of Fresh Raffia Palm Trunk on the Bioremediation of Oil-Based Drill
Abstract: This study determines the effect of fresh raffia palm for biodegradation of oil-based drill cuttings bioremediation. The experiment was conducted at the rivers institute of Agricultural research and training (RIART) located at the Rivers State University, Port Harcourt. Samples of oil-based drill cuttings were bulked in eleven reactors with four replications (T1, T2, T3-T11). The physiochemical properties of the initial drill cuttings were analyzed. Also, the physiochemical properties of the …
Published in International Journal of Pollution: Prevention & Control · Vol. 1, Issue 2, 2023 · pp. 41–48 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Facial Biometrics for Attendance System
Abstract: This paper discusses the necessity for effective student attendance management systems by proposing a smart attendance management system utilizing biometric technology. It is well recognised that manually recording attendance is time-consuming and error prone. In this study, we propose a Facial Biometrics attendance system that automates attendance process without requiring human intervention. The system consists of a camera placed in the classroom to take pictures of the pupils. Subsequently, the …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 36–44 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article