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404 articles for “complex algorithms”
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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An Algorithm for License Plate Detection using Wavelet Transform
Abstract: As the importance of public transportation system increases, an Automatic License Plate Recognition (ALPR) has turned out to be an important research issue. It is becoming difficult to keep track of each vehicle for purpose of law enforcement and traffic management. ALPR equipped in many intelligent surveillance systems like, road traffic management, security management, automatic toll collection system etc. The basic steps in ALPR were accurate localization of number plate, …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 1, 2015 · pp. 6–13 Read article
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Efficient Partial Update Algorithm over Wireless Networks
Abstract: Adaptive partial update algorithm is developed based on incremental method. The proposed algorithm applies in real time changing environment. The proposed algorithm responds to linear estimation with nodes in cooperative manner and less number of computations. The algorithm has powerful advantage is that it requires less number of coefficient and reduced computational and communication complexity in wireless sensor network. It is efficient because it has power of solving distributed estimation …
Published in Current Trends in Signal Processing · Vol. 6, Issue 3, 2016 · pp. 1–8 Read article
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Unsupervised Probabilistic Debugging
Abstract: We presented an unsupervised probabilistic approach for the debugging of the programs; where the focus is on diagnosing the wrong answers based on the proposed unsupervised semantic parsing algorithm. This approach can be implemented over other programming language. The parsing of the test cases are heuristically employed with the proposed parsing algorithm which reduces the computational complexity and rationally give better performing algorithms.
Published in Recent Trends in Programming languages · Vol. 1, Issue 3, 2014 · pp. 13–15 Read article
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Nanomedicine in Combination with Artificial Intelligence (AI): Transforming Cancer Treatment
Abstract: The convergence of nanomedicine and artificial intelligence (AI) holds transformative potential for advancing cancer treatment, particularly in liver cancer. Nanomedicine enables the development of targeted drug delivery systems, enhanced imaging modalities, and precise therapeutic interventions, while AI facilitates data-driven decision-making, personalized treatment plans, and predictive analytics. This synergistic approach can significantly improve the diagnosis, treatment, and monitoring of liver cancer by optimizing the use of nanoparticle-based therapies. AI-powered algorithms can …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 27–30 Read article
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Comparative Analysis of Metamorphic Testing for Service-oriented Software Applications
Abstract: The result execution correctness is executed by software testing, using test oracles. Test oracle is one of the most common problems in case of software testing but if software testing is applicable, it is too much expensive. In this study, triangle classification problem is solved by metamorphic testing. Indeed, the objective of runtime examination is not tied in with computing the specific number of steps needed for discovering an answer. …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 15–25 Read article
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Collision Avoidance Using Li-Fi Based Inter Vehicle Communication
Abstract: Most countries in the world have an alarming record in number of death/disability due to tremendous number of accidents. Even though road transport in India is very prevalent for various reasons, the rate of road-accidents and fatality in the country is very high. Accidents occur due to the unawareness of the public regarding the same. Researchers have observed that majority of the accidents where solely due to factors involving the …
Published in Journal Of Network security · Vol. 6, Issue 2, 2018 · pp. 22–26 Read article
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Parallelizing Mutations for Genetic Algorithm
Abstract: In the present work, the author has implemented the mutations crossovers of genetic algorithm (GA) over a parallelism environment. This attempt will enable us collect data to build a framework for shared parallelism for the solution of equations in the same verifiable computational time. The data indicate towards the better implementation of a larger computational problem in the parallelized for the better solution in the verifiable execution time.Keywords: Genetic algorithm, …
Published in Recent Trends in Parallel Computing · Vol. 1, Issue 3, 2014 · pp. 7–9 Read article
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Implementation of Load Flow Analysis using NR method
Abstract: Load flow studies are one of the most important aspects of power system analysis and design. This paper presents an optimal analysis technique for load flow analysis using Newton Raphson Algorithm for solving set of nonlinear equations. The main objective of load flow analysis is to evaluate the magnitude and phase angle of voltage at each bus as well as real and reactive power flowing in each transmission line. For …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 3, 2015 · pp. 8–13 Read article
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Study of Real-Time System for Monitoring and Analyzing ECG Using Cell Phone: A Review
Abstract: Health conditions of various patients suffering from cardiac diseases need to be monitored time to time. This is due to the criticality of these conditions which are mainly related to cardiac dis orders. Thus patients need to be followed up on a regular basis. An immediate follow-up can be facilitated in a real environment. A portable device can act suitably as a real environment here in such conditions. A hand-held …
Published in Current Trends in Signal Processing · Vol. 5, Issue 1, 2015 · pp. 7–12 Read article
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3D-IC Partitioning and TSV Sharing Optimization Algorithm
Abstract: Recent technologies are in need of shorter vertical interconnects, thus forcing the integration technology from 2D to 3D. Because more than 50% of dynamic power consumption is due to interconnects. As a solution, 3D integration consists of stacking integrated circuits and connecting them with short vertical interconnects. TSV is used to vertically connect the hardware components in different dies stacked in 3D ICs. But in floor planning TSVs are very …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 3, Issue 2, 2016 · pp. 6–10 Read article
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Generalized Rail Clamping Sequences Based PWM (GRCPWM) Algorithm for Direct Torque Controlled Induction Motor Drive
Abstract: The paper presents Rail Clamping Sequence based Pulse Width Modulation (RCPWM) algorithms applied to Direct Torque Control (DTC) of induction motor drive. This RCPWM based DTC retains all the advantages of conventional DTC (CDTC), moreover it eliminates the complexity involved in SVPWM algorithm and results in reduced current ripple at higher modulation indices and lowers the switching losses at all modulation indices. To validate the proposed method, simulation through MATLAB …
Published in Journal of Control & Instrumentation · Vol. 8, Issue 3, 2017 · pp. 38–59 Read article
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Face And Spoofing Detection Via Genetic Algorithm-Based Feature Selection with MTCNN
Abstract: Face detection and liveness detection in various environments such as different lighting effects, occlusion, complex backgrounds, and different poses and angles play an important role in facial recognition or detection purposes. In this research paper, propose an improved algorithm for face detection and liveness, spoofing detection via genetic algorithm for feature selection, and mtcc detecting the edge of the facial image by Canny filter and spotting the face from the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 17–26 Read article
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Optimization of CMOS Current Mirror Load-based Differential Amplifier using Hybrid Cuckoo Search and Particle Swarm Optimization Algorithm
Abstract: Optimization of CMOS based analog circuits is becoming a practical solution for complex analog modules. There are number of evolutionary algorithms presented to optimize the analog circuits in different reported literatures. During optimization process, the optimal result may not be obtained with only individual algorithm or requires a more time. Therefore the hybrid algorithm of two or more algorithms is more effective method to obtain the goal. The Particle Swarm …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 71–78 Read article
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Matrix Factorization and Tensor Decomposition at Scale: Mathematical Foundations and Computational Approaches
Abstract: Matrix factorization and tensor decomposition techniques have emerged as fundamental tools in machine learning and data science for handling high dimensional data efficiently. This paper presents a comprehensive analysis of scalable matrix factorization and tensor decomposition methods, focusing on their mathematical foundations, computational complexity, and practical applications. We examine key algorithms including Singular Value Decomposition (SVD), Non-negative Matrix Factorization (NMF), CP decomposition, and Tucker decomposition, with particular emphasis on their …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 56–59 Read article
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Using Elliot Wave Theory and Fibonacci Retracement and in Algorithmic Trading
Abstract: The analysis technique used in predicting stock prices consists of Fundamental analysis and Technical analysis. These analyses are complex in nature and usually unreliable. The algorithmic trading systems offered today consists of primitive technical analysis techniques such as, simple moving averages, exponential moving average, moving averages convergence and diversions and volume weighted average price. The primitive nature of this techniques makes them very unreliable and has a low success rate. …
Published in Trends in Machine design · Vol. 7, Issue 3, 2020 · pp. 22–29 Read article
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Dynamic Priority-based Adaptive Scheduling (DPAS) for Modern Operating Systems
Abstract: Dynamic Priority-based Adaptive Scheduling (DPAS) is an innovative CPU scheduling algorithm designed to optimize system performance and resource utilization in modern computing environments. As computing systems become increasingly complex and diverse, traditional static scheduling algorithms often struggle to adapt efficiently to the dynamic nature of workloads. DPAS addresses this challenge by introducing a dynamic and adaptive approach to process prioritization and resource allocation. DPAS leverages real-time feedback, machine learning, and …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 2, 2023 · pp. 6–15 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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Trends, Challenges, and the Future of Unmanned Aerial Systems
Abstract: The rapid evolution of unmanned aerial vehicles (UAVs), commonly referred to as drones, has transformed numerous domains — from military surveillance and logistics to precision agriculture and atmospheric research. This paper examines the current state of drone technology, industry trends, regulatory frameworks, socio-economic impacts, ethical considerations, and future research directions. With contributions from multidisciplinary studies, this review emphasizes emerging technologies, performance metrics, risk factors, and opportunities for innovation. In recent …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 27–33 Read article