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432 articles for “efficiency algorithm”
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Crypto Talk Voice Shield: Secure Speech Communication System Using Arduino
Abstract: In the rapidly evolving landscape of communication security, this study presents a system designed around Arduino Uno technology, specifically engineered for the secure encoding, transmission, and decoding of speech data. By integrating advanced encryption algorithms, the system ensures that speech data is transmitted in segmented bit chunks, each enveloped in multiple layers of security to prevent unauthorized access or interception. This multi-tiered encryption approach establishes a highly secure communication channel, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 23–30 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 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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E-Commerce Study Using AR/VR and Ethical Convergence of Commerce
Abstract: The landscape of E-commerce is undergoing a fundamental transformation, shifting from a platform-centric model of transactional exchange to an immersive, ecosystem-driven experience. This analysis examines the critical trends and disruptive forces that define the immediate and long-term trajectory of digital commerce. The study identifies three foundational pillars driving future growth: Hyper-Personalization via Generative AI, Spatial Commerce (AR/VR Integration), and Sustainable Supply Chain Resilience. Future E-commerce will be characterized by the …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 20–26 Read article
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VHDL-Based Strategies for Protecting IoT Devices from Power and Electromagnetic Side-Channel Attacks: A Study
Abstract: The environment of the Internet of Things (IoT) is rapidly developing, linking billions of devices across a wide variety of disciplines. Furthermore, despite the fact that it provides an unprecedented level of convenience and efficiency, this interconnection also presents a fertile ground for security weaknesses. Side-channel attacks, also known as SCAs, are one of the dangers that pose a considerable risk. These attacks specifically target the cryptographic implementations that are …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 30–40 Read article
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Thermal Performance of Concentrating Solar Panels
Abstract: The study shows a detailed analysis of the thermal performance of concentrating solar panels and the temperature increase due to concentrated solar radiation. This work proposes a configuration to reduce temperature rise, maintain good panel efficiency, and increase output power. The configuration is based on a sandwich structure including a phase change material (PCM), which absorbs the thermal energy excess generated by the concentrated solar radiation onto the PV panel. …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–10 Read article
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Design of Biped Robots: A Review
Abstract: Biped robots, inspired by the human’s kinematic structure, have seen remarkable evolution from early mechanical automata to today’s sophisticated machines capable of performing complex tasks. Their design aims to achieve efficient and stable movement on two legs. This paper examines the current advancements and historical progress in the development of bipedal robots. The authors investigate the implementation of these robots in various fields, like healthcare, entertainment, search and rescue operations, …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 36–46 Read article
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Neuroinformatics and Its Impact on the Future of Brain-Computer Interface Technology
Abstract: Neuroinformatics, a multidisciplinary field combining neuroscience, information technology, and data science, plays a crucial role in advancing brain-computer interface (BCI) technology. By leveraging large-scale neural data, machine learning algorithms, and computational models, neuroinformatics enhances our understanding of brain function and improves the design and development of BCIs. The integration of neuroinformatics into BCI systems offers new possibilities for interpreting complex brain signals, facilitating real-time communication between the brain and external …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 9–18 Read article
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Review on to Design High Speed and Area Three Oprend Binary Adder Using MDCLCG Architecture
Abstract: The three operands binary adder is a basic function used in the creation of modular arithmetic in various algorithms, such as the pseudorandom bit generator and cryptography. The CS3A carry save adder is commonly used to perform this operation. Nevertheless, the operation's outcome delayed the transmission of O(n) because of the ripple carry step. A dual-optoic adder for parallel prefix computation, such as the Han-Carlson method, can be used to …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 14–22 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Self-Driving Cars and Computer Vision: Enhancing Computer Vision for Autonomous Vehicle Navigation
Abstract: Autonomous vehicles, commonly known as self-driving cars, are transforming the transportation sector by aiming to enhance road safety, ease traffic congestion, and boost overall efficiency. Central to the operation of these vehicles is computer vision, which enables them to perceive and understand their environment. This paper examines how computer vision contributes to the navigation of autonomous vehicles and highlights its continuous developments. Specifically, it examines key challenges such as real-time …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 1–10 Read article
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A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
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Electronic Circuitry and Material Integration for Enhanced Gas Detection Windows
Abstract: Liquefied Petroleum Gas (LPG) and propane, being flammable mixtures of hydrocarbon gases, are widely used as fuel in various applications such as homes, hostels, and industries. Our main objective for this project is to design and fabricate a gas sensing window that will autonomously open upon detecting any leakage of gases like LPG, CO2, alcohol, propane, etc. The heart of our system is the MQ-9 gas sensor, known for its …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 3, 2024 · pp. 14–24 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Smart Attendance System Using Face Recognition with OpenCV
Abstract: In the past, the conventional method of recording student attendance relied heavily on teachers manually marking entries in a physical register. While simple, this approach is not only time-consuming but also highly vulnerable to errors such as accidental omissions, incorrect entries, or even malpractice in the form of proxy attendance. Moreover, traditional registers lack real-time accessibility, making it difficult to analyze or monitor data instantly. To address these limitations, modern …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 30–39 Read article
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Automatic Exam Seating Generator: SmartSeat
Abstract: The Automatic Exam Seating Arrangement System streamlines exam seating for institutions. It leverages algorithms to automate the tedious guide system. This avoids remaining minute rushes and confusion in locating the right venue. The device provides an application for admins and college students with examination timetables, timing and batch details to successfully control the seating process. Admins input parameters like student numbers and seating potential. Intelligent algorithms generate the greatest plans …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article