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1080 articles for “time efficient”
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Face Recognition Attendance System Using Local Binary Pattern Histogram Algorithm
Abstract: Maintaining accurate and tamper-proof attendance records in educational and corporate environments has long been a challenge due to the limitations of manual and biometric systems. This study introduces the development and deployment of a contactless, automated attendance system that utilizes facial recognition through the local binary pattern histogram (LBPH) algorithm. The primary goal is to offer a secure and efficient substitute for conventional attendance methods by harnessing the power of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 29–34 Read article
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Design, Development, and Performance Analysis of an Intelligent IoT-Based Home Automation System
Abstract: Without a doubt, the incorporation of Internet of Things (IoT) technology into what used to be traditional homes has turned them into smart houses. Appliances are controlled and monitored in the distance. With a security of 99.9% it is unproblematic to break in these terminals and your energy synchronously may go down two points any time fifty times." "Home automation systems allow automatic control of electrical appliances, environmental conditions and …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 23–30 Read article
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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Adaptive Machine Learning Framework for Navigation Control of Autonomous Drones
Abstract: The rise of autonomous drones has expanded UAV applications across sectors like surveillance, delivery, agriculture, and rescue operations. However, traditional navigation systems face limitations in adapting to dynamic environments. This study proposes an AI-driven adaptive navigation framework that leverages real-time sensor data, reinforcement learning, and adaptive control strategies to enhance drone autonomy, scalability, and security. The system processes mission inputs, environmental data (from LiDAR, cameras, GPS, and weather sensors), and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article
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Automated Fault Identification and Tracking in Power Transmission Networks Using GPS
Abstract: Power transmission lines are vulnerable to faults caused by environmental factors, aging infrastructure, and external disturbances such as falling trees or animal contact. Prompt and accurate detection and location of these faults are essential to ensure uninterrupted power delivery, reduce equipment damage, and minimize downtime. This project presents an automatic fault detection and location system using GPS technology integrated with a microcontroller-based sensing module. The proposed system continuously monitors voltage …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 37–43 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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IoT-enhanced Real-time Monitoring and Hazard Detection
Abstract: This research explores the innovative application of internet of things (IoT) technology within occupational health and safety management systems (OHSMS) to substantially improve real-time monitoring and hazard detection in industrial settings. IoT sensors and wearable devices are deployed to enable continuous and thorough collection of data on environmental conditions, equipment status, and worker health. Real-time data analysis facilitated by IoT technology allows for the rapid identification and mitigation of potential …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 20–24 Read article
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Optimization of Process Parameters for Cu90Ni10 Alloy Processed by Wire Arc Additive Manufacturing (WAAM) Using an L9 Orthogonal Array
Abstract: Abstract Wire Arc Additive Manufacturing (WAAM) has gained significant attention in recent years as a promising technique for producing complex metallic components. This study focuses on the processing of Cu90Ni10 alloy using WAAM and employs an L9 orthogonal array to optimize the mechanical properties of the resulting components. Cu90Ni10 alloy is known for its excellent corrosion resistance and electrical conductivity, making it a critical material in various industries, including aerospace …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 292–301 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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OpenCV, AI, and Haar Cascade File: A Review
Abstract: Real-time image processing applications using OpenCV encompass a diverse and crucial array of tasks in modern technology. OpenCV's robust capabilities enable the implementation of object detection and tracking, which are vital for surveillance systems to monitor and analyze activities in real time. In the realm of security, face recognition technology, powered by OpenCV, provides accurate and efficient identification and authentication, enhancing safety measures. Gesture recognition, another significant application, facilitates intuitive …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 39–46 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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Advancements in O-Glycosylation Techniques with Diverse Donor Molecules
Abstract: Since the early stages of carbohydrate chemistry, numerous researchers have employed alkynyl glycosyl donors as key reagents in glycosylation reactions. These donors have played a crucial role in facilitating the synthesis of glycosidic bonds, an essential aspect of carbohydrate-based compounds. Over time, various modifications and improvements have been introduced by different research groups to enhance the efficiency, selectivity, and sustainability of glycosylation processes. A major focus has been on designing …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 7–28 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article
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Metamaterial-Based Thermal Shielding Structures for Reusable Hypersonic Space Transportation Systems
Abstract: The rapid development of reusable hypersonic space transportation systems has intensified the need for advanced thermal protection technologies capable of withstanding extreme aerodynamic heating conditions encountered during atmospheric re-entry and sustained hypersonic flight. Conventional thermal shielding materials often suffer from high structural weight, limited adaptability, thermal fatigue, and degradation under repeated thermal cycling. This study proposes a novel Metamaterial-Based Thermal Shielding Structure for Reusable Hypersonic Space Transportation Systems, integrating engineered …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Utilizing AWS Advanced Services for Modernizing and Refactoring Legacy Systems to Achieve Cloud-Native Capabilities
Abstract: Updating and restructuring outdated systems is essential for organizations seeking to harness the scalability, adaptability, and robustness offered by cloud-native architectures. Legacy systems can obstruct innovation because of their rigid structure, expensive maintenance, and inability to scale effectively. Amazon Web Services (AWS) provides a comprehensive suite of advanced services that enable the efficient transformation of such systems into modern, cloud-native solutions. This paper explores strategies and best practices for utilizing …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 44–65 Read article
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Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article