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Search results for: algorithms
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Highly Precised and Efficient Robot-Based ESPAR Antenna Measurements in Realistic Environments
PublicationIn this paper, we present a novel approach utilizing a small Unmanned Surface Vehicle (USV) equipped with Global Navigation Satellite System (GNSS) technology to facilitate large-scale outdoor automated measurements. The system employs dedicated software and measurement scripts to autonomously navigate the robot along predefined routes, stopping at multiple points for data collection. This method minimizes observational error and...
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TR-Based Antenna Design with Forward FD: The Effects of Step Size on the Optimization Performance
PublicationNumerical methods are important tools for design of modern antennas. Trust-region (TR) methods coupled with data-efficient surrogates based on finite differentiation (FD) represent a popular class of antenna design algorithms. However, TR performance is subject to FD setup, which is normally determined a priori based on rules-of-thumb. In this work, the effect of FD perturbations on the performance of TR-based design is evaluated...
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Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
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The Effect of Minimum Actuation Limit in Shape Control of a Single-Layer Dome Frame
PublicationThis paper describes the significance of the minimum actuation limit per actuator while controlling the shape of a single-layer frame dome. The algorithms that perform optimum shape controlling allow the user to assign the minimum allowable actuation per actuator, which means the actuators with an actuation of less than the assigned amount are assumed to be passive; thus, they are excluded. In this study, the deformed shape of...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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The Quick Measure of a Nurbs Surface Curvature for Accurate Triangular Meshing
PublicationNURBS surfaces are the most widely used surfaces for three-dimensional models in CAD/CAE programs. As a model for FEM calculation is prepared with a CAD program it is inevitable to mesh it finally. There are many algorithms for meshing planar regions. Some of them may be used for meshing surfaces but it is necessary to take the curvature of the surface under consideration to avoid poor quality mesh. The mesh must be denser in the...
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Measurements of transmission properties of Acoustic Communication Channels
PublicationTough transmission properties of shallow water acoustic channels (SWAC) highly limit the use of underwater acoustic communication (UAC) systems. An adaptive matching of modulation and signaling schemes to instantaneous channel conditions is needed for reliabledata communications. This creates, however, unique challenges for designers when compared to radio transmission systems. When communication system elements are in move, the...
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublicationThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Rotor Blade Geometry Optimisation in Kaplan Turbine
PublicationThe paper presents the description of method and results of rotor blade shape optimisation. The rotor blading constitutes a part ofturbine flow path. Optimisation consists in selection of the shape that minimises ratio of polytrophic loss. Shape of the blade isdefined by the mean camber line and thickness of the airfoil. Thickness is distributed around the camber line based on the ratio ofdistribution. Global optimisation was done...
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Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture
PublicationDynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...
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Camera Orientation-Independent Parking Events Detection
PublicationThe paper describes the method for detecting precise position and time of vehicles parking in a parking lot. This task is trivial in case of favorable camera orientation but gets much more complex when an angle between the camera viewing axis and the ground is small. The method utilizes background subtraction and object tracking algorithms for detecting moving objects in a video stream. Objects are classified into vehicles and...
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From the multiple frequency tracker to the multiple frequency smoother
PublicationThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
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Crowdsourcing-Based Evaluation of Automatic References Between WordNet and Wikipedia
PublicationThe paper presents an approach to build references (also called mappings) between WordNet and Wikipedia. We propose four algorithms used for automatic construction of the references. Then, based on an aggregation algorithm, we produce an initial set of mappings that has been evaluated in a cooperative way. For that purpose, we implement a system for the distribution of evaluation tasks, that have been solved by the user community....
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Mathematical modeling of hydrogen production performance in thermocatalytic reactor based on the intermetallic phase of Ni3Al
PublicationThe main goal of the following work is to adjust mathematical modelling for mass transfer, to specific conditions resulting from presence of chemical surface reactions in the flow of the mixture consisting of helium and methanol. The thermocatalytic devices used for decomposition of organic compounds incorporate microchannels coupled at the ends and heated to 500 oC at the walls regions. The results of the experiment were compared...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublicationTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Modeling the impact of rotor movement on non-linearity of motor currents waveforms in high-speed PMSM drives
PublicationMotor current measurement techniques as well as predictive control algorithms for electric drives rely on an assumption of linear motor currents changes resulting from constant inverter output voltages. Recent research has reported that this assumption does not hold in motors with short electrical time constant, and in drives whose rotor position advances substantially during a control period. This paper proposes a simulation model...
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Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions
PublicationAbility to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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Spatial Calibration of a Dual PTZ-Fixed Camera System for Tracking Moving Objects in Video
PublicationA dual camera setup is proposed, consisting of a fixed (stationary) camera and a pan-tilt-zoom (PTZ) camera, employed in an automatic video surveillance system. The PTZ camera is zoomed in on a selected point in the fixed camera view and it may automatically track a moving object. For this purpose, two camera spatial calibration procedures are proposed. The PTZ camera is calibrated in relation to the fixed camera image, using interpolated...
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Acoustic Processor of the MCM Sonar
PublicationThis paper presents the concept of an acoustic processor of the mine countermeasure sonar. Developed at the Department of Marine Electronics Systems, Gdansk University of Technology, the acoustic processor is an element of the MG-89, a modernised underwater acoustic station. The focus of the article is on the modules of the processor. They are responsible for sampling analogue signals and implementing the algorithms controlling...
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Retention modeling of some saccharides separated on an amino column.
PublicationUsing an amino column (Supelcosil LC-NH2) and different mixtures of acetonitrile-water, quantitative structure-retention relationship models are discussed. These models are based on computed molecular descriptors representing numerically structured features of some saccharides. The obtained results are underlining the lipophilicity/hydrophilicity balance, and how this is controlling the separation of the saccharides. The resulting...
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Improving listeners' experience for movie playback through enhancing dialogue clarity in soundtracks
PublicationThis paper presents a method for improving users' quality of experience through processing of movie soundtracks. The dialogue clarity enhancement algorithms were introduced for detecting dialogue in movie soundtrack mixes and then for amplifying the dialogue components. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity...
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Efficiency of gas mixtures detection by resistive gas sensors
PublicationResistive gas sensors are very popular and are commonly used to detect various gases and their mixtures. Theeir main disadvantage is very limited selectivity. Practical use of gas sensors in environenmental applications requires determination of concentration of a few mixed gases at the same time. We would like to present recent results of gas detection improvement by utilizing a single gas sensor and additional measurements to...
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublicationSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublicationIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Information System for Drivers Within the Integrated Traffic Management System - TRISTAR
PublicationAdvanced traveler information systems (ATIS) for drivers are a very important element of modern traffic management. In recent years ITS infrastructure is being developed also in Poland. It allows for delivering to drivers information related to the conditions in the road network through, inter alia, dedicated Variable Message Signs (VMS). Such information enables drivers to take decisions, contributing to improving the efficiency...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublicationEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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A new diagnostic method for evaluation of cardiosurgery wound healing
PublicationOne of important and still unsolved problems in medicine is the question of objective and quantitative evaluation of post-surgery wound healing. The aim of this research is to analyse possibility and value of using the newly elaborated infrared imaging procedure – Active Dynamic Thermography (ADT) – for quantitative description of wound healing processes in cardiosurgery. Both, classical thermal figures of merit as well as ADT...
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Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublicationThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Eventual Convergence of the Reputation-Based Algorithm in IoT Sensor Networks
PublicationUncertainty in dense heterogeneous IoT sensor networks can be decreased by applying reputation-inspired algorithms, such as the EWMA (Exponentially Weighted Moving Average) algorithm, which is widely used in social networks. Despite its popularity, the eventual convergence of this algorithm for the purpose of IoT networks has not been widely studied, and results of simulations are often taken in lieu of the more rigorous proof....
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Single-phase power electronics transformer with active functions for smart grid
PublicationThis paper presents the control of one cell of a modular single-phase power electronics transformer with active functions for meeting the smart grid concept. In this way, the converter could be used not only as a conventional transformer but also for grid such as reactive power, harmonic elimination and energy storage. The topology of the cell is composed by a bidirectional converter with three stages: a half bridge in the input...
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Simulation Environment in Python for Ship Encounter Situations
PublicationTo assess the risk of collision in radar navigation distance-based safety measures such as Distance at the Closest Point of Approach and Time to the Closest Point of Approach are most commonly used. Also Bow Crossing Range and Bow Crossing Time measures are good complement to the picture of the meeting situation. When ship safety domain is considered then Degree of Domain Violation and Time to Domain Violation can be applied. This...
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Systematic approach to binary classification of images in video streams using shifting time windows
Publicationin the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...
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Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory
PublicationAuthors of this paper take under investigation the optimization of biological processes during the wastewater treatment in sequencing batch reactor (SBR) plant. A designed optimizing supervisory controller generates the dissolved oxygen (DO) trajectory for the lower level parts of the hierarchical control system. Proper adjustment of this element has an essential impact on the efficiency of the wastewater treatment process as well...
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PROJEKTOWANIE WIELOWYMIAROWEGO REGULATORA BACKSTEPPING W UKŁADZIE DYNAMICZNEGO POZYCJONOWANIA STATKU
PublicationW komercyjnych systemach dynamicznego pozycjonowania statku, pomimo znacznego wzrostu poziomu automatyzacji, wykorzystywane jest nadal sterowanie typu PID. Poprawę jakości procesu pozycjonowania może umożliwić wykorzystanie bardziej efektywnych algorytmów, oferujących zaawansowane nieliniowe techniki sterowania. W artykule przedstawiono zagadnienie projektowania regulatora pozycji i kursu dla układu dynamicznego pozycjonowania...
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Obliczanie przesunięć osi toru przy modernizacji łuków parabolicznych na liniach kolejowych
PublicationPodstawowym zadaniem modernizacji linii kolejowych jest właściwe zaprojektowanie nowego układu geometrycznego, który będzie spełniał założone kryteria związane z parametrami eksploatacyjnymi danej linii. Dążąc do spełnienia przyjętych warunków nałożonych na projektowany układ, projektant najczęściej koryguje podstawowe parametry geometryczne, tj. przechyłkę, promień łuku kołowego oraz długości krzywych przejściowych. W artykule...
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Elgold partial: Job offers
Open Research DataThe dataset contains 34 English texts scrapped from the web portals offering job offers. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity...
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Elgold partial: History blogs
Open Research DataThe dataset contains 13 texts from English history blogs. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
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Elgold partial: Scientific papers' abstracts
Open Research DataThe dataset contains 87 Scientific papers' abstracts in English randomly chosen from the folowing scientific disciplines: Biomedicine, Life Sciences, Mathematics, Medicine, Science, Humanities, Social Science.
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Elgold partial: Amazon product reviews
Open Research DataThe dataset contains 34 Amazon product reviews in English. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
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Elgold partial: Automotive blogs
Open Research DataThe dataset contains 34 English texts scrapped from automotive blogs. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and...
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Elgold partial: Movie reviews
Open Research DataThe dataset contains 37 English texts with movie reviews. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
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Nieliniowa statyka 6-parametrowych powłok sprężysto plastycznych. Efektywne obliczenia MES
PublicationGłównym zagadnieniem omawianym w monografii jest sformułowanie sprężysto-plastycznego prawa konstytutywnego w nieliniowej 6-parametrowej teorii powłok. Wyróżnikiem tej teorii jest występujący w niej w naturalny sposób tzw. stopień 6 swobody, czyli owinięcie (drilling rotation). Podstawowe założenie pracy to przyjęcie płaskiego stanu naprężenia uogólnionego na ośrodek typu Cosseratów. Takie podejście stanowi oryginalny aspekt opracowania....
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Tomasz Gzella mgr inż.
People -
Marek Czachor prof. dr hab.
People -
Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublicationNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Analyzing the relationship between sound, color, and emotion based on subjective and machine-learning approaches
PublicationThe aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker’s/singer’s voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed...