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359 articles for “Algorithm Performance”
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SoloRider: An Autonomous Self-Balancing Electric Bike for Sustainable Urban Mobility
Abstract: Rapid urbanization has intensified challenges such as traffic congestion, parking inefficiency, and environmental degradation. While autonomous vehicle research predominantly focuses on four-wheel platforms, lightweight two-wheelers remain comparatively underexplored. Two-wheelers are a great option for sustainable urban transportation because of their many benefits, including their small size, lower energy consumption, better manoeuvrability, and lesser infrastructure requirements. This paper presents SoloRider, a conceptual autonomous self- balancing electric two-wheeler de- signed for sustainable …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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A Critique of Advanced Instrumentation for Supervising and Regulating Renewable Energy Systems
Abstract: The integration of renewable strength property into the power grid necessitates modern-day tracking and manipulate systems to ensure highest best average overall performance, reliability, and performance. This paper offers a comprehensive analysis of advanced instrumentation applied for monitoring and controlling renewable strength systems. Beginning with an outline of renewable energy assets and their importance in addressing environmental worries and electricity sustainability, the compare delves into the challenges inherent in monitoring …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–12 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Investigation of Mechanical Properties of Banana, Linen and Their Hybrid Reinforced Composite Laminates in Adverse Condition and Analyze Using ML
Abstract: This research investigates the mechanical performance of composite laminates reinforced with banana and linen fibers, focusing on both individual and hybrid fiber combinations. The primary objective is to assess how these natural fiber composites behave under extreme environmental conditions, particularly high humidity and fluctuating temperatures, which are common in aerospace and automotive applications.Key mechanical properties—tensile strength, flexural strength, and impact resistance—are experimentally evaluated to assess the performance and long-term reliability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 25–31 Read article
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Verilog-Based Image Processing on Field Programmable Gate Arrays: Design and Implementation
Abstract: Integrated circuits known as Field Programmable Gate Arrays (FPGAs) are frequently offered for sale off the shelf. They are known as "field programmable" because, following manufacture, they enable users to modify the hardware to satisfy particular use case needs. This makes it possible to update features and correct bugs in-place, which is very helpful for remote deployments. Configurable logic blocks (CLBs) and a series of programmable interconnects are features of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 3, 2024 · pp. 13–26 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
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Development and Experimental Investigation of a Light Weight Hybrid Electric Vehicle Using Lithium-Ion Battery and EDLC Supercapacitor Integration
Abstract: Lightweight hybrid electric vehicles (HEVs) have gained significant attention as an environmentally friendly and efficient mode of transportation. However, their energy storage systems (ESS) often face challenges such as limited battery lifespan, inadequate power delivery during peak demand, and inefficient energy recovery during braking. This research focuses on the development and experimental evaluation of a hybrid energy storage system (HESS) integrating Lithium-Ion Batteries (LIB) and Electric Double-Layer Capacitors (EDLC) for …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 26–40 Read article
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Dynamics of Prime Gap Sets: An Algorithmic and Set-Theoretic Approach
Abstract: In this paper, we present a theorem and an efficient algorithm for computing all prime numbers up to a given integer X. Our theorem establishes a relationship between the primes up to X and those up to (X+1)2, providing a theoretical foundation for the algorithm. The proposed method improves upon the traditional Sieve of Eratosthenes by dynamically eliminating multiples of primes using only the remaining numbers in the set, thereby …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 20–25 Read article
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Enhancing Control with Embedded Ssvep-Bci
Abstract: Brain–Computer Interface (BCI) technology establishes a direct communication link between the human brain and external devices without relying on muscular activity. Among various BCI paradigms, the Steady-State Visually Evoked Potential (SSVEP)-based approach has gained significant attention due to its high signal-to-noise ratio, minimal user training, and suitability for real-time applications. However, implementing such systems on embedded hardware presents challenges such as limited computational resources, signal noise, and latency in processing. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 41–52 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 Read article
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Alternating Inertia-Based Virtual Synchronous Machine Control for Improved Frequency Regulation of Energy Storage Systems
Abstract: The rapid integration of renewable energy sources (RESs), particularly solar photovoltaic and wind energy systems, has significantly increased the penetration of power electronic converter-based distributed generators (DGs) in modern power systems. While these technologies provide substantial environmental, economic, and sustainability benefits, their widespread deployment has introduced new operational challenges. One of the major concerns is the reduction of system inertia and damping due to the replacement of conventional synchronous generators …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Rainwater Measuring Algorithm in O(1) Time Complexity
Abstract: The Rain Terraces Time Complexity Data Structure Algorithm (RTTCDSA) introduces a novel method for managing temporal data efficiently, inspired by the natural flow of rainwater on terraced landscapes. This study presents the conceptual framework and implementation details of RTTCDSA, which leverages principles of temporal dynamics and landscape morphology to organize and query temporal data with optimal time complexity. RTTCDSA employs a hierarchical structure akin to terraced landscapes, facilitating rapid traversal …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 26–32 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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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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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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An Overview of Privacy-Preserving Data Encryption Techniques in Mobile Cloud Computing for Big Data
Abstract: With the introduction of mobile cloud computing (MCC), data processing, storage, and sharing have undergone a radical transformation that has greatly improved organizational effectiveness and quality of life. But there are also serious worries about data security and privacy due to the increasing usage of mobile devices and cloud computing, particularly when managing large amounts of data from many sources like sensors and cellphones. The privacy issues surrounding MCC are …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article