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221 articles for “secure networks”
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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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Exploring the Role of Advanced Shell Scripts for Malware Threat Detection
Abstract: This study investigates the application of advanced shell scripts in detecting malware threats within computer systems. As cyber-attacks become more sophisticated, traditional detection methods frequently prove inadequate, highlighting the need for innovative approaches. The research highlights the effectiveness of shell scripting in automating the monitoring and analysis of system behavior, file integrity, and network traffic. By leveraging patterns and signatures of known malware, the scripts can identify anomalies indicative of …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 6–16 Read article
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Under Voltage and Over Voltage Protection of Electrical Equipment - A Review
Abstract: In our modern, digitally-driven world, the seamless operation of electrical equipment is paramount, spanning industries, households, and infrastructure. However, the reliability of these vital assets is inextricably linked to the quality of electrical power supplied to them. Voltage fluctuations, specifically under voltage and over voltage events, pose significant threats to the integrity and functionality of electrical equipment. This review paper undertakes a comprehensive exploration of under voltage and over voltage …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Interior Design for Disaster Resilience
Abstract: In the age of heightening environment actuated calamities and the thriving intricacy of metropolitan scenes, the basic to implant catastrophe flexibility inside plan resounds with remarkable criticalness. This examination paper embraces a general odyssey, diving into the complicated interchange between inside plan and catastrophe flexibility inside the constructed climate. Drawing upon a tremendous embroidery of insightful writing, exact investigations, and genuine models, the paper fastidiously disentangles the multi-layered methodologies, developments, …
Published in International Journal of Climate Conditions · Vol. 1, Issue 1, 2024 · pp. 01–15 Read article
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The Role of IoT in Shaping Smart Cities with Architectural Perspective
Abstract: The integration of IoT in smart cities is revolutionizing the development of cities through interconnected systems that enhance efficiency, sustainability, and quality of life. Real-time data collection,communication, and processing are facilitated by IoT technology through its layered architecture:sensing, network, and application layers. These interlinked ecosystems help solve such serious problems of urbanization as the efficient allocation of resources, smooth flow of traffic, efficient utilization of energy, and the handling of …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 1–10 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Integrating AI and ML in Tribology: A Review of Current Trends and Future Prospects
Abstract: This review paper explores the growing integration of artificial intelligence (AI) and machine learning (ML) within the field of tribology. Tribology, the study of friction, wear, and lubrication, is crucial for Improving the performance and longevity of mechanical systems. This review explores the role of AI and machine learning techniques, including artificial neural networks (ANNs), support vector machines (SVMs), and physics-informed machine learning (PIML)can be used to solve difficult tribological …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 56–60 Read article
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The Role of IoT in Sustainable Agriculture: Leveraging Big Data for Precision Farming
Abstract: Precision farming combined with the Internet of Things (IoT) is transforming the agricultural industry by boosting productivity and encouraging sustainable practices.. This paper explores the transformative impact of IoT technologies on modern agriculture, focusing on how big data analytics can be leveraged to optimize farming practices, reduce waste, and conserve resources. The Internet of Things (IoT) offers real-time data on a range of agricultural characteristics, including soil moisture, temperature, humidity, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Ecomotion Cityglide Commuter E-Bike
Abstract: The transition from conventional gasoline motorcycles to electric bikes represents a pivotal step in addressing the increasing demand for sustainable transportation solutions in urban environments. This paper meticulously explores the multifaceted aspects of this transition, focusing on the technological advancements, design innovations, and societal implications associated with the adoption of electric bikes. Electric bikes, powered by Brushless DC (BLDC) motors and rechargeable battery packs, offer a suite of benefits over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 43–49 Read article
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Non-Lethal Protection of Farmlands Against Wild Animals and Crop Estimation
Abstract: This paper is an integrated smart system that aims to enhance productivity related to agriculture along with agricultural safety through modern technology. Crop estimation system uses IoT sensors and machine learning algorithms for the analysis of real-time environmental data in terms of soil moisture, temperature, pH levels, and humidity. This data will further be used to provide the optimal crop for cultivation and appropriate fertilizer requirements for prediction of requirements. …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 18–24 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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A Study of Virtual Machines Environment in Cloud Computing
Abstract: The Cloud computing is most widely used technological concept which gives the efficient result in concern to availability and utilizing of resources, processing and management of the data on servers. These capabilities make cloud computing to decorate the programs of it. The concept of virtualization of cloud computing is main feature of this technology which provide a platform to many business application data, academic IT tools and industry to explore …
Published in Recent Trends in Parallel Computing Read article
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Raspberry Pi-based Self-driving Car Technologies: A Review of Hardware and Software Integration
Abstract: An assessment of the state, possibilities, and difficulties of self-driving car technology. Autonomous vehicles (AVs), also referred to as self-driving cars, are automobiles that can navigate and function without the need for human involvement. They make decisions, sense their environment, and traverse routes safely by combining sensors, cameras, radar, lidar, and sophisticated algorithms. The advancement of autonomous vehicles holds the capacity to completely transform the transportation sector by enhancing security, …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Detection of Driver Emotion Using Deep Learning
Abstract: High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers' states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 01–06 Read article
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Significant Advances in Cloud Computing in Information and Communications Technology
Abstract: The critical advances in information and communications technology (ICT) over the last half-century have led to the increasingly common vision that computing will one day become the 5th utility. This computing utility will provide the essential level of computing service considered basic to meet the everyday needs of the general public. To convey this vision, a number of computing models have been proposed, with the most recent being cloud computing. …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 33–38 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Analysis of a Communication Link Performance Across Various Rayleigh Channels in Tropical Climates
Abstract: Tropical regions are characterized by intense and persistent rainfall throughout most of the year, and this environmental condition significantly influences wireless communication performance. The continuous presence of heavy precipitation weakens, scatters, and disrupts radio frequency signals, causing noticeable attenuation during transmission from the source to the destination. As a result, reliable communication becomes challenging, particularly for modern high-speed systems such as 5G networks. To address this limitation and enhance communication …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 06–12 Read article
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Development of a Blockchain-Based System for Drug Counterfeiting and Traceability in the Pharmaceutical Supply Chain
Abstract: Counterfeit drugs present a major risk to public health and pose a substantial threat to the pharmaceutical industry, leading to severe economic losses and risking patient lives. Ensuring the safety and authenticity of the pharmaceutical supply chain is critical to addressing this issue. This study presents a novel approach for enhancing the security and authenticity of the pharmaceutical supply chain through the integration of blockchain technology, decentralized storage, and artificial …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 99–114 Read article