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35 articles for “real-world conditions”
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Antibiotics – Challenges in our Post-COVID Era
Abstract: Accidental discovery of the antibiotic properties of penicillin marked a watershed moment in healthcare, transforming the landscape of medicine and saving countless lives of injured and infected. Further research and awareness on the advantages of this “miracle drug” resulted in its bulk production in the 1940s, and played a crucial role in saving lives of thousands during World War II. Subsequent discoveries especially broad-spectrum antibiotics paved the way for further …
Published in International Journal of Antibiotics · Vol. 1, Issue 2, 2024 · pp. 1–5 Read article
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ML-Driven Optimization Framework for the Analysis, Design, and Development of Efficient Wireless Power Transfer Systems for EV Charging
Abstract: The fast uptake of electric vehicles (EVs) has heightened the necessity of effective, dependable and convenient charging systems. The Wireless Power Transfer (WPT) systems can be taken as a potential solution as they allow charging cells without contact, without any risks, and without any overcrowding; the efficiency of the system is strongly influenced by the alignment of coils, the fluctuations of air-gaps, the conditions of the loads, and geometrical arrangements …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Reaching Conditions for Discrete-time Sliding Mode Control: Analysis and Design
Abstract: Sliding mode control (SMC) is a robust control method widely used in engineering due to its ability to handle uncertainties and disturbances effectively. In discrete-time sliding mode control (DSMC), system trajectories are constrained to sliding surfaces in the state space, leading to improved performance and stability. This paper provides an overview of DSMC, focusing on its applications, advantages, and limitations. It discusses the use of DSMC in various engineering fields …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 7–14 Read article
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Fracture Toughness in Advanced Materials: A Comparative Review of Testing Methods and Standards
Abstract: Fracture toughness is a key material property used to assess a material's ability to resist crack propagation, which is vital for ensuring the reliability and durability of structures and components in high-performance applications. It is particularly important in advanced materials such as composites, ceramics, and high-strength alloys, which are increasingly used in demanding industries such as aerospace, automotive, and civil engineering. Fracture toughness testing helps determine the material's behavior under …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 17–21 Read article
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The Effect of Spatial Distribution of Public Amenities on Residential Property Rental Value
Abstract: In major cities around the world, the rental value has indeed been increasing at an unprecedented rate because of the rising demand for residential properties in urban areas. Residential building characteristics, neighborhood characteristics, accessibility factors, and amenities are all factors that influence residential rental value. These amenities lead to rent differentials. The links that exist between residential property rental values and various physical and locational dwelling features, amenities, and so …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 28–37 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Driver Anti-Sleep Alarming and Protection
Abstract: Road accidents due to driver drowsiness is one of the biggest problems worldwide, which kills thousands of people every year. Fatigue slows the reaction time, reduces the concentration, and, most importantly, impairs the judgment, thus making drowsy driving as dangerous as drunk driving. To reduce such accidents, various technologies have been employed to develop driver anti-sleep devices. These include sensor-based detection, camera-based eye monitoring, EEG analysis, and real-time alert systems. …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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The Burden of Empirical Therapy: Analyzing the Predominance of Broad-Spectrum Antibiotic Usage in Lower Respiratory Tract Infections
Abstract: Lower respiratory tract infections (LRTIs) remain one of the leading causes of morbidity and hospitalization worldwide, particularly among older adults, immunocompromised individuals, and patients with chronic respiratory disorders. These infections include conditions such as community-acquired pneumonia, hospital-acquired pneumonia, bronchitis, and acute infective exacerbations of chronic lung disease, all of which often require rapid clinical intervention. Because microbiological confirmation of the causative pathogen frequently takes 48–72 hours, clinicians generally initiate empirical …
Published in International Journal of Antibiotics · Vol. 3, Issue 2, 2026 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article
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Firing a Laser into the Sky Diverts Lightning Offering Greater Protection to Installations
Abstract: Lightning bolts cause thousands of deaths every year worldwide. Since Benjamin Franklin’s invention of lightning rods made almost 300 years ago, the technology has not been changed even today. The same Franklin lightning rods are used on top of the buildings to steer lightning down to the ground so that they don’t pass through the buildings, and damage the structure or electrocute people. Researchers have recently developed a new type …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 1, Issue 2, 2023 · pp. 46–56 Read article
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Conductive Polymers for Electro-Mechanical Systems: Structure–Property Relationships and Mechanical Behavior Under Stress
Abstract: Conductive polymers represent a unique class of functional materials that combine the electrical characteristics of metals with the mechanical flexibility of polymers. These dual properties are critical for the next generation of electro-mechanical systems, including wearable sensors, soft robotics, structural health monitoring (SHM), and biomedical actuators. However, the mechanical performance of conductive polymers under diverse stress conditions—such as elongation, cyclic loading, bending, and impact—remains a key challenge, limiting their long-term …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 25–30 Read article