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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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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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Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms
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Comparison of Algorithms for Profile-Based Alignment of Low Resolution MALDI-ToF Spectra
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Parameters Identification of the Flexible Fin Kinematics Model Using Vision and Genetic Algorithms
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Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms
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Comparative Analysis of Regular Grid Based Algorithms in the Design of Graphical Control Panels
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Algorithms for spatial analysis and interpolation of discrete sets of Critical Infrastructure hazard data
PublicationNowo opracowane zaawansowane narzędzia technologii informacyjnych i komunikacyjnych (TIK) ujawniają swoją przydatność do przewidywania różnego rodzaju zagrożeń oraz minimalizowania związanego z nimi potencjalnego ryzyka. Jednakże większość tych narzędzi operuje jedynie na niektórych typach infrastruktury i zaniedbuje ich przestrzenne interakcje z otoczeniem oraz innymi strukturami. Niniejszy artykuł zawiera propozycje kilku algorytmów...
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Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing
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Gradient based basis function algorithms for identification of quasi periodically varying processes.
PublicationW pracy przedstawiono problem identyfikacji systemów, których parametry zmieniają się w sposób pseudookresowy. Pokazano sposób, w jaki można modelować takie systemy przy zastosowaniu metody harmonicznych funkcji bazowych.Przedstawiono dwa sposoby dekompozycji (struktura szeregowa i równoległa) takich układów na elementy związane z poszczególnymi funkcjami bazowymi. Zaprezentowany został sposób śledzenia częstotliwości funkcji...
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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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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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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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METHOD OF TRAINING THE ENDOSCOPIC VIDEO ANALYSIS ALGORITHMS TO MAXIMIZE BOTH ACCURACY AND STABILITY
PublicationIn the article a new training and testing method of endoscopic video analysis algorithms is presented. Classical methods take into account only eciency of recognizing objects on single video frames. Proposed method additionally considers stability of classiers output for real video input. The method is simple and can be trained on data sets created for other solutions. Therefore, it is easily applicable to existing endoscopic video...
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On the fast BSS transition algorithms in the IEEE 802.11r local area wireless networks
PublicationHandover performance is critical to support multimedia services that are becoming increasingly available over the wireless devices. The high transition delay can be unaccepted for such services or can be a source of disruption on the session. On the other side, IEEE 802.11 standard is being extended with new functionalities. Security and QoS features, included in recent IEEE 802.11-2007 standard, add management frames that are...
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Endoscopy video analysis algorithms and their independence of rotation , brightness , contrast , color and blur
PublicationThe article presents selected image analysis algorithms for endoscopy videos. Mathematical methods that are part of these algorithms are described, and authors’ claims about the characteristics of these algorithms, such as the independence of rotation, brightness, contrast, etc. are mentioned. Using the common test on the real endoscopic image database and a set of image transformations, the validity of these claims was checked...
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Comparison of selected algorithms for scheduling workflow applications with dynamically changing service availability
PublicationThis paper compares the quality and execution times of several algorithms for scheduling service based workflow applications with changeable service availability and parameters. A workflow is defined as an acyclic directed graph with nodes corresponding to tasks and edges to dependencies between tasks. For each task, one out of several available services needs to be chosen and scheduled to minimize the workflow execution time and...
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Application of auto calibration and linearization algorithms to improve sound quality of computer devices
PublicationAn application of auto calibration and linearization algorithms designed for correcting acoustic characteristics of selected computer devices was presented in the paper. The functionality of the algorithms were presented for two kind of computer devices: ultrabook class computer and portable device of All-In-One type. The algorithms were adjusted for the given type of the device on the basis of series of measurements conducted...
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A digital implementation of the PSK transmitter and receiver as multirate algorithms of the digital signal processing
PublicationIn this paper designs of the transmitter and the receiver of PSK signals as three-rate algorithms of the digital signal processing are described. Additionally we show the examples of the transmitter and the receiver of the following signals: BPSK, QPSK. We discussed also an influence of the cascade of the shaping filter and the receiving filter on the intersymbol interference in the received complex envelope.W pracy opisano projektowanie...
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Impact of Shifting Time-Window Post-Processing on the Quality of Face Detection Algorithms
PublicationWe consider binary classification algorithms, which operate on single frames from video sequences. Such a class of algorithms is named OFA (One Frame Analyzed). Two such algorithms for facial detection are compared in terms of their susceptibility to the FSA (Frame Sequence Analysis) method. It introduces a shifting time-window improvement, which includes the temporal context of frames in a post-processing step that improves the...
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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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BIOLOGICAL AGE ASSESSMENT ALGORITHMS BASED ON X-RAY IMAGES OF BONE TISSUE
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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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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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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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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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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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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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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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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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Comparisons of envelope morphological filtering methods and various regular algorithms for surface texture analysis
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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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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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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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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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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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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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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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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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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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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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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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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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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...