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93 articles for “real-world applications”
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Smart Farming Using Mesh Network
Abstract: The increasing demand for food production due to the growth of the world population has led to various challenges in agriculture. Factors such as the reduction of the rural workforce and the rise in production costs have made it necessary to find innovative solutions to enhance productivity and efficiency. Smart farming, which integrates agricultural practices with the Internet of Things (IoT), has become a promising method to tackle these challenges. …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 10–19 Read article
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Dynamic Modeling and Simulation of Multi-Body Mechanical Systems: A Comprehensive Review of Methods, Tools, and Applications
Abstract: The dynamic modeling and simulation of multi-body mechanical systems (MBS) form a cornerstone in modern mechanical engineering, enabling in-depth analysis of the kinematic and kinetic behaviors of interconnected rigid and flexible components. MBS are foundational to a range of critical applications, from automotive suspensions and aerospace mechanisms to robotics and biomechanical structures. As system complexity and performance requirements increase, accurate and scalable modeling techniques are essential for both design validation …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 35–42 Read article
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Breaking Boundaries: A Comprehensive Review of Screenless Display Technology
Abstract: This review explores new ways of showing images without traditional screens. We cover technologies like holography, where images appear to float in space, and retinal projection, which projects images directly onto your eye. We also discuss virtual retinal displays, which draw images on your retina using lasers, and augmented reality (AR), which overlays digital content onto your real-world view.Visual picture, Synaptic interface, Virtual Retinal Display. This primarily elucidates and illustrates …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 34–40 Read article
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Data Representation and Abstraction in Computer Systems: An Interactive Study
Abstract: Data abstraction simplifies data, while data representation stores or encodes it. Data abstraction in programming involves constructing a data type that hides data representation. This lets consumers concentrate on the data’s primary features rather than its implementation. Data abstraction is common in object-oriented programming and database administration. Computers store data in binary format. The smallest binary unit is a bit, or “binary digit”. Bytes typically have eight bits. Data abstraction …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 22–31 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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A Dynamic Text Compression Model for Big Data Applications Using Hadoop
Abstract: In today’s data-driven era, efficiently handling vast amounts of information has become increasingly important. Data compression plays a vital role in this regard — it is essentially a method of encoding information in such a way that significantly reduces the number of bits required to store or transmit a file. By shrinking data to its most compact form, compression techniques help save storage space, reduce bandwidth consumption, and improve the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 2, 2026 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Herbal Medicines and Complementary Therapies: Their Role, Types and Applications
Abstract: Medicinal plants are used in herbal medicine to treat and prevent illnesses. This includes the use of standardized and titrated botanical extracts in addition to common and traditional medicines from different cultures. The safety of a treatment may be suggested by its long history and deep cultural roots in traditional medical systems, but this does not always imply that it is effective. This is especially important in herbal medicine, since …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 40–53 Read article
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A Review of IoT-enabled Smart Street Light Power Management Systems: Challenges and Opportunities
Abstract: In the contemporary world, people expect all their demands to be satisfied. To address this human desire, scientific and technological developments are accelerating. One important factor in the quick development of technology is the Internet of Things (IoT). The goal of smart led street lighting systems is to create and implement cutting-edge IOT developments for energy-saving street lighting. Automation of street lighting is the best way to reduce electrical power …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article