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Search results for: ALGORITHMS
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Optimal design and control tuning of the power generation interfaces using genetic algorithms
PublicationReferat przedstawia zastosowania algorytmów genetycznych do rozwiązywania klasycznych problemów w elektrotechnice. Zostały one zastosowane do optymalizacji parametrów regulatora VSC w celu zmniejszenia strat mocy i dostrajania tych parametrów w stanach przejściowych. Wyniki rozważań zostały potwierdzone za pomocą badań symulacyjnych.
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Intelligent acquisition of audio signals, employing neutral networks and rough set algorithms
PublicationAlgorytmy oparte na sztucznych sieciach neuronowych i metodzie zbiorówprzybliżonych zostały zastosowane do lokalizacji sygnałów fonicznych obar-czonych pasożytniczym szumem i rewerberacjami. Informacja o kierunku napły-wania dźwięku była uzyskiwana na wyjściach tych algorytmów na podstawie re-prezentacji parametrycznej. Przedstawiono wyniki eksperymentalne i przepro-wadzono ich dyskusję.
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Some Artificial Intelligence Driven Algorithms For Mobile Edge Computing in Smart City
PublicationSmart mobile devices can share computing workload with the computer cloud that is important when artificial intelligence tools support computer systems in a smart city. This concept brings computing on the edge of the cloud, closer to citizens and it can shorten latency. Edge computing removes a crucial drawback of the smart city computing because city services are usually far away from citizens, physically. Besides, we introduced...
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Algorithms and Data Structures 2022
e-Learning CoursesWETI, DS, Algorithms and Data Structures
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Performance Evaluation of Selected Parallel Object Detection and Tracking Algorithms on an Embedded GPU Platform
PublicationPerformance evaluation of selected complex video processing algorithms, implemented on a parallel, embedded GPU platform Tegra X1, is presented. Three algorithms were chosen for evaluation: a GMM-based object detection algorithm, a particle filter tracking algorithm and an optical flow based algorithm devoted to people counting in a crowd flow. The choice of these algorithms was based on their computational complexity and parallel...
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An Approach to Bass Enhancement in Portable Computers Employing Smart Virtual Bass Synthesis Algorithms
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The developed algorithms are related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt and to the type of a portable device in use. To find optimum synthesis parameters of the VBS algorithms, subjective listening tests based on a parametric procedure...
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Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
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Task Scheduling – Review of Algorithms and Analysis of Potential Use in a Biological Wastewater Treatment Plant
PublicationThe idea of task scheduling is to increase the efficiency of a system by minimising wasted time, evenly loading machines, or maximising the throughput of machines. Moreover, the use of appropriate scheduling algorithms often leads to a reduction in the energy costs of the process. Task scheduling problems are found in a variety of industrial areas, and their scale changes significantly depending on the problem. This review shows...
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublicationThe problem of noncausal identification of a time-varying linear system subject to both smooth and occasional jump-type changes is considered and solved using the preestimation technique combined with the basis function approach to modeling the variability of system parameters. The proposed estimation algorithms yield very good parameter tracking results and are computationally attractive.
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Optimal Placement of Phasor Measurement Unit in Power System using Meta-Heuristic Algorithms
PublicationThe phasor measurement units (PMUs) play an important and vital role in power system monitoring and controlling, since they provide the power system phasors stamped with a common real time reference through a global positioning system (GPS). Indeed, from economical point of view it is not possible to set PMUs in all system buses due to the high cost and the requirement of more complex communication...
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A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware
PublicationThe paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The...
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Evaluation of Vehicle Routing Problem Algorithms for Transport Logistics Using Dedicated GIS System
PublicationThe development and research related to optimization of fleet management is of high interest among many industrial and scientific entities related to logistics and transport. Optimal distribution of transportation resources leads to significant cost reduction. In this context, scientific research related to so called Vehicle Routing Problem (VRP) which relies on determining the shortest transport routes for a strictly limited number...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
PublicationWastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it is difficult to design an efficient, optimal control system. The problem regarding biochemical reactions inside Sequential Batch Reactor...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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On Improved-Reliability Design Optimization of High-Frequency Structures Using Local Search Algorithms
PublicationThe role of numerical optimization has been continuously growing in the design of high-frequency structures, including microwave and antenna components. At the same time, accurate evaluation of electrical characteristics necessitates full-wave electromagnetic (EM) analysis, which is CPU intensive, especially for complex systems. As rigorous optimization routines involve repetitive EM simulations, the associated cost may be significant....
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Application of Graph Theory Algorithms in Non-disjoint Functional Decomposition of Specific Boolean Functions
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Replica Exchange and Multicanonical Algorithms with the Coarse-Grained United-Residue (UNRES) Force Field
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Efficient parallel algorithms in global optimization of potential energy functions for peptides, proteins, and crystals
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The Speedup Analysis in GEM Detector Based Acquisition System Algorithms with CPU and PCIe Cards
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Comparisons of envelope morphological filtering methods and various regular algorithms for surface texture analysis
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Comparison of construction algorithms for minimal, acyclic, deterministicfinite state automata from sets of strings.
PublicationArtykuł porównuje różne metody tworzenia minimalnych, acyklicznych, deterministycznych automatów skończonych ze zbiorów słów. Wdrożone i porównane zostały metody przyrostowe, prawie przyrostowe i nieprzyrostowe.
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Optimizing acoustic field intesity algorithms using the sound ray surface density method.
PublicationW artykule przedstawiono zagadnienia optymalizacji algorytmów komputerowych obliczeń rozkładów natężeń pola akustycznego w akwenie w zależności od za- mierzonych warunków hydrologicznych pod kątem skrócenia czasu obliczń.
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Evaluation of propagation parameters of open guiding structures with the use of complex root finding algorithms
PublicationAn efficient complex root tracing algorithm is utilized for the investigation of electromagnetic wave propagation in open guiding structures. The dispersion characteristics of propagated and leaky waves are calculated for a couple of chosen waveguides. The efficiency of the root tracing algorithm is discuses and compared to a global root finding algorithm.
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublicationThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
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Comparison of Two Nonlinear Predictive Control Algorithms for Dissolved Oxygen Tracking Problem at WWTP
PublicationThe wastewater treatment plant is classified as a complex system, due to its nonlinear dynamics, large uncertainty of disturbance inputs, multiple time scales in the internal process dynamics, and multivariable structure. The aeration process, in turn, is an important and expensive part of wastewater treatment plant operation. All operating parameters of the aeration in biological processes are to be precisely controlled to provide...
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Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms
PublicationOver the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements
PublicationIn this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine different combinations of Peano and Hilbert with the already known swarm...
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Better polynomial algorithms for scheduling unit-length jobs with bipartite incompatibility graphs on uniform machines
PublicationThe goal of this paper is to explore and to provide tools for the investigation of the problems of unit-length scheduling of incompatible jobs on uniform machines. We present two new algorithms that are a significant improvement over the known algorithms. The first one is Algorithm 2 which is 2-approximate for the problem Qm|p j = 1, G = bisubquartic|Cmax . The second one is Algorithm 3 which is 4-approximate for the problem Qm|p...
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Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment
PublicationIn the paper we present parallel implementations as well as execution times and speed-ups of three different algorithms run in various environments such as on a workstation with multi-core CPUs and a cluster. The parallel codes, implementing the master-slave model in C+MPI, differ in computation to communication ratios. The considered problems include: a genetic algorithm with various ratios of master processing time to communication...
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Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms
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Optimization of FFF Process Parameters by Naked Mole-Rat Algorithms with Enhanced Exploration and Exploitation Capabilities
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Investigation of Performance and Energy Consumption of Tokenization Algorithms on Multi-core CPUs Under Power Capping
PublicationIn this paper we investigate performance-energy optimization of tokenizer algorithm training using power capping. We focus on parallel, multi-threaded implementations of Byte Pair Encoding (BPE), Unigram, WordPiece, and WordLevel run on two systems with different multi-core CPUs: Intel Xeon 6130 and desktop Intel i7-13700K. We analyze execution times and energy consumption for various numbers of threads and various power caps...
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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with moving measurment window
PublicationW artykule rozważana jest łączna estymacja przedziałowa zmiennych i parametrów w złożonej sieci dynamicznej w oparciu niepewne modele parametryczne i ograniczoną liczbę pomiarów. Opracowany został rekursywny algorytm estymacji z przesuwnym oknem pomiarowym, odpowiedni dla monitorowania sieci on-line. Okno pomiarowe pozwala na stabilizowanie klasycznego algorytmu rekurencyjnego estymacji i znacznie poprawienie obcisłości estymat....
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublicationSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Investigation of Performance and Energy Consumption of Tokenization Algorithms on Multi-core CPUs Under Power Capping
PublicationIn this paper we investigate performance-energy optimization of tokenizer algorithm training using power capping. We focus on parallel, multi-threaded implementations of Byte Pair Encoding (BPE), Unigram, WordPiece, and WordLevel run on two systems with different multi-core CPUs: Intel Xeon 6130 and desktop Intel i7-13700K. We analyze execution times and energy consumption for various numbers of threads and various power caps and...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublicationThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublicationThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Increasing the Geometrical and Interpretation Quality of Unmanned Aerial Vehicle Photogrammetry Products Using Super-Resolution Algorithms
PublicationUnmanned aerial vehicles (UAVs) have now become very popular in photogrammetric and remote-sensing applications. Every day, these vehicles are used in new applications, new terrains, and new tasks, facing new problems. One of these problems is connected with flight altitude and the determined ground sample distance in a specific area, especially within cities and industrial and construction areas. The problem is that a safe flight...
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Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks
PublicationThis study analyzes two forecasting models based on the application of fuzzy logic and evaluates their effectiveness in predicting visitor expenditure and length of stay at a popular theme park. The forecasting models are based on a set of more than 600 decision rules constructed in the form of a complex series of IF-THEN statements. These algorithms store expert knowledge. A descriptive instrument that records the individual visitor's...
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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublicationML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
PublicationThis paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of the art and highlights the challenges and opportunities in this topic. By incorporating the best practices identified in this review, we established guidelines for the development of CMB detection...
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Effects of scatter plot initial solutions on regular grid facility layout algorithms in typical production models
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Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
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