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Search results for: ALGORITHM
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
PublicationAbstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...
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Mean Crossover in evolutionary path planning method for maritime collision avoidance
PublicationAbstract: This paper presents the use of mean crossover genetic operator for path planning using evolutionary algorithm for collision avoidance on sea. Mean crossover ensures widening of the possible solutions' set that can be achieved in comparison to exchange crossover variant. The research shown, that the mean crossover allows to achieve results independent from the initial generation and quicker transition of thealgorithm from...
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Automatic assessment of the motor state of the Parkinson's disease patient --a case study
PublicationThis paper presents a novel methodology in which the Unified Parkinson's Disease Rating Scale (UPDRS) data processed with a rule-based decision algorithm is used to predict the state of the Parkinson's Disease patients. The research was carried out to investigate whether the advancement of the Parkinson's Disease can be automatically assessed. For this purpose, past and current UPDRS data from 47 subjects were examined. The results...
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Evaluation of the Possibility of Identifying a Complex Polygonal Tram Track Layout Using Multiple Satellite Measurements
PublicationWe present the main assumptions about the algorithmization of the analysis of measurement data recorded in mobile satellite measurements. The research team from the Gda´nsk University of Technology and the Maritime University in Gdynia, as part of a research project conducted in cooperation with PKP PLK (Polish Railway Infrastructure Manager), developed algorithms supporting the identification and assessment of track axis layout....
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Expedited simulation-driven design optimization of UWB antennas by means of response features
PublicationIn this work, a method for fast design optimization of broadband antennas is considered. The approach is based on a feature-based optimization (FBO) concept where reflection characteristics of the structure at hand are formulated in terms of suitably defined feature points. Redefinition of the design problem allows for reducing the design optimization cost, because the dependence of feature point coordinates on antenna dimensions...
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Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data
PublicationObjective monitoring of the real estate value is a requirement to maintain balance, increase security and minimize the risk of a crisis in the financial and economic sector of every country. The valuation of real estate is usually considered from two points of view, i.e. individual valuation and mass appraisal. It is commonly believed that Automated Valuation Models (AVM) should be devoted to mass appraisal, which requires a large...
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Evaluation of the Possibility of Identifying a Complex Polygonal Tram Track Layout Using Multiple Satellite Measurements
PublicationWe present the main assumptions about the algorithmization of the analysis of measurement data recorded in mobile satellite measurements. The research team from the Gda´nsk University of Technology and the Maritime University in Gdynia, as part of a research project conducted in cooperation with PKP PLK (Polish Railway Infrastructure Manager), developed algorithms supporting the identification and assessment of track axis layout....
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Grid-Forming Operation of Energy-Router Based on Model Predictive Control with Improved Dynamic Performance
PublicationThe focus of this study is on the grid-forming operation of the Energy Router (ER) based on Model Predictive Control (MPC). ER is regarded as a key component of microgrids. It is a converter that interfaces the microgrid (s) with the utility grid. The ER has a multiport structure and bidirectional energy flow control. The ER concept can be implemented in Nearly Zero-Energy Buildings (NZEB) to provide flexible energy control. A...
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Collision Risk-Informed Weather Routing for Sailboats
PublicationSelected COLREG rules, good seamanship and sheer common sense indicate that it is in a sailboat's interest to follow collision-free routes without relying on large power-driven ships to give way. Until now, however, no method has integrated a sailboat's weather routing with collision risk monitoring and collision avoidance. Therefore, a new deterministic approach to combine the above features within one method is introduced here....
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublicationSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Using MusicXML to evaluate accuracy of OMR Systems
PublicationIn this paper a methodology for automatic accuracy evaluation in optical music recognition (OMR) applications is proposed. Presented approach assumes using ground truth images together with digital music scores describing their content. The automatic evaluation algorithm measures differences between the tested score and the reference one, both stored in MusicXML format. Some preliminary test results of this approach are presented...
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Parallel tabu search for graph coloring problem
PublicationTabu search is a simple, yet powerful meta-heuristic based on local search that has been often used to solve combinatorial optimization problems like the graph coloring problem. This paper presents current taxonomy of patallel tabu search algorithms and compares three parallelization techniques applied to Tabucol, a sequential TS algorithm for graph coloring. The experimental results are based on graphs available from the DIMACS...
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Macromodels for efficient FEM simulations of waveguides and resonators
PublicationThis paper introduces a novel technique for enhancing the efficiency of the finite element method (FEM) by incorporating special modules, called macromodels, into the standard eigenvalue formulation. The number of unknowns in the separated macromodel subdomain can be significantly reduced by orthogonal projection, using the efficient nodal order reduction algorithm. The idea of macromodels implementation is demonstrated on a simple...
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Spectral Analysis of Capital Markets
PublicationIn this paper the problem of cycles existence in capital markets is addressed. A spectral analysis algorithm, which reduces signal-to-noise ratio, is proposed to derive cycle periodograms for the yield function of DJIA, WIG~20, and NIKKEI 225 indices. Peaks of the the periodograms provide premises to postulate the existence of some possible cycles. The 3.5 year periodicity in all 3 indices, which can be related to Kitchin cycle...
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Self-tuning adaptive frequency tracker
PublicationAn automatic gain tuning algorithm is proposed for a recently introduced adaptive notch filter. Theoretical analysis and simulations show that, under Gaussian random-walk type assumptions, the proposed extension is capable of adjusting adaptation gains of the filter so as to minimize the mean-squared frequency tracking error without prior knowledge of the true frequency trajectory. A simplified one degree of freedom version of...
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A New Approach to Stability Evaluation of Digital Filters
PublicationIn this paper, a new numerical method of evaluating digital filter stability is presented. This approach is based on novel root-finding algorithms at the complex plane using the Delaunay triangulation and Cauchy's Argument Principle. The presented algorithm locates unstable zeros of the characteristic equation with their multiplicities. The proposed method is generic and can be applied to a vast range of systems. Verification of...
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Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
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Multichannel self-optimizing active noise control scheme
PublicationThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. The proposed cancellation scheme is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants. In the important benchmark case - for disturbances with randomwalk-type amplitude...
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Quaternion Encryption Method for Image and Video Transmission
PublicationQuaternions are hyper-complex numbers of rank 4. They are often applied to mechanics in 3D space and are considered to be one of the best ways of representing rotations. In this paper a quaternion encryption method, based on algorithm by Nagase et al. (2004) has been proposed. According to a computer-based simulation the results of the performed research yield a high level of security, which is additionally strengthened by the...
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Application of Intuitionistic Fuzzy Sets to the assessment of technical university students
PublicationThe article proposes application of artificial intelligence methods to assess students of technical universities. The level of achieved educational goals can be assessed using measurements based on the idea of Fuzzy Intuitionistic Sets (IFS). A classification algorithm was developed and an exemplary distribution of the criteria values using IFS was presented. The application of the proposed approach in online education can enrich...
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Wykorzystanie metody Neldera-Meada do identyfikacji wartości parametrów niequasi-statycznego modelu małosygnałowego tranzystora MOS
PublicationW artykule zaprezentowano wyniki zastosowania metody sympleksu Neldera-Meada do ekstrakcji wartości parametrów niequasi-stycznego modelu małosygnałowego tranzystora MOS. Przedstawiono równoważny elektryczny schemat zastępczy i model matematyczny nowego modelu małosygnałowego MOSFETa dla częstotliwości mikrofalowych. Opisano zaimplementowany algorytm i otrzymane rezultaty badań.
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Automatic evaluation of information credibility in Semantic Web and Knowledge Grid
PublicationThis article presents a novel algorithm for automatic estimation of information credibility. It concerns information collected in Knowledge Grid and Semantic Web. Possibilities to evaluate the credibility of information in such structures are much greater than those available for WWW sites which use natural language. The rating system presented in this paper estimates credibility automatically on the basis of the following metrics:...
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Performance of data transmission in UMTS with turbo code about decreased number of states
PublicationIn the paper a structure of turbo encoder and decoder about decreased number of states has been described. The simulation results of transmission performance based on turbo coding without the reduction of the number of iterations for the uplink and downlink of WCDMA/FDD interface have been presented. The SOVA algorithm for turbo decoding has been used. The investigations have been carried out for Outdoor to Indoor & Pedestrian...
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Multiscaled Hybrid Features Generation for AdaBoost Object Detection
PublicationThis work presents the multiscaled version of modified census features in graphical objects detection with AdaBoost cascade training algorithm. Several experiments with face detector training process demonstrate better performance of such features over ordinal census and Haar-like approaches. The possibilities to join multiscaled census and Haar features in single hybrid cascade of strong classifiers are also elaborated and tested....
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Adaptive CAD-Model Construction Schemes
PublicationTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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Assessing Word Difficulty for Quiz-Like Game
PublicationMappings verification is a laborious task. Our research aims at providing a framework for manual verification of mappings using crowdsourcing approach. For this purpose we plan on implementing a quiz like game. For this purpose the mappings have to be evaluated in terms of difficulty to better present texts in respect of game levels. In this paper we present an algorithm for assessing word difficulty. Three approaches...
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Measuring pulse rate with a webcam — A non-contact method for evaluating cardiac activity
PublicationIn this paper the simple and robust method of measuring the pulse rate is presented. Elaborated algorithm allows for efficient pulse rate registration directly from face image captured from webcam. The desired signal was obtained by proper channel selection and principal component analysis. A developed non-contact method of heart rate monitoring is shown in the paper. The proposed technique may have a great value in monitoring...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublicationUtilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response...
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A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor
PublicationThis paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure....
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Rapid multi-criterial design of microwave components with robustness analysis by means of knowledge-based surrogates
PublicationManufacturing tolerances and uncertainties concerning material parameters, e.g., operating conditions or substrate permittivity are detrimental to characteristics of microwave components. The knowledge of relations between acceptable parameter deviations (not leading to violation of design specifications) and the nominal performance (not considering uncertainties), and is therefore indispensable. This paper proposes a multi-objective...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC
PublicationThis paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In...
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Evaluation of Connectivity Gaps Impact on TCP Transmissions in Maritime Communications
PublicationMany organizations and research working groups, including among others IEEE, ITU, ETSI and IMO are currently working towards improvements in communication of different types of vehicles (cars, trains, planes and vessels) and upgrading utilities and services offered to their crews and passengers travelling all over the world. The paper deals with selected aspects of the TCP protocol connectivity in maritime wireless networks. The...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Analysis of circular polarization antenna design trade‐offs using low‐cost EM‐driven multiobjective optimization
PublicationCircular polarization (CP) antennas are vital components of modern communication systems. Their design involves handling several requirements such as low reflection and axial ratio (AR) within the frequency range of interest. Small size is an important criterion for antenna mobility which is normally achieved as a by‐product of performance‐oriented modifications of the structure topology. In this work, multiobjective optimization...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Matrix Strengthening the Identification of Observations with Split Functional Models in the Squared Msplit(q) Estimation Process
PublicationThis article addresses the issue of raising the level of identification of observations with either single or more split functional models in the squared Msplit(q) estimation process. The theoretical part of the study presents the theoretical grounds for the classical method for estimating parameters in a split functional model and proposes a modification of the computational algorithm to increase the quality of the determinations...
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General Provisioning Strategy for Local Specialized Cloud Computing Environments
PublicationThe well-known management strategies in cloud computing based on SLA requirements are considered. A deterministic parallel provisioning algorithm has been prepared and used to show its behavior for three different requirements: load balancing, consolidation, and fault tolerance. The impact of these strategies on the total execution time of different sets of services is analyzed for randomly chosen sets of data. This makes it possible...
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New Approach to Arc Fitting for Railway Track Realignment
PublicationThis article presents a new method of arc fitting for railway track realignment. The theoretical foundations are presented, along with a detailed algorithm of the iterative computational process. This method is based on solving a set of linearized pseudo-observation equations. The formulas of the functional model of the fitting problem were derived, and a special form of objective function is proposed. An iterative method for optimization...
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On cooperative image denoising
PublicationIn this paper we suggest how several competing image denoising algorithms, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable denoising algorithm. The proposed fusion mechanism allows one to combine practically all kinds of noise reduction tools. It also allows one to account for the distribution of measurement noise, and in particular - to cope with heavy-tailed...
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Propagation in the Open Cylindrical Guide of Arbitrary Cross Section With the Use of Field Matching Method
PublicationA simple solution to propagation problem in open waveguides and dielectric fibers of arbitrary convex cross section is presented. The idea of the analysis is based on the direct field matching technique involving the usage of the field projection at the boundary on a fixed set of orthogonal basis functions. A complex root tracing algorithm is utilized to find the propagation coefficients of the investigated guides. Different convex...
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Towards an efficient multi-stage Riemann solver for nuclear physics simulations
PublicationRelativistic numerical hydrodynamics is an important tool in high energy nuclear science. However, such simulations are extremely demanding in terms of computing power. This paper focuses on improving the speed of solving the Riemann problem with the MUSTA-FORCE algorithm by employing the CUDA parallel programming model. We also propose a new approach to 3D finite difference algorithms, which employ a GPU that uses surface memory....
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Automatic Discovery of IaaS Cloud Workload Types
PublicationThe paper presents an approach to automatic discovery of workloads types. We perform functional characteristics of the workloads executed in our cloud environment, that have been used to create model of the computations. To categorize the resources utilization we used K-means algorithm, that allow us automatically select six types of computations. We perform analysis of the discovered types against to typical computational benchmarks,...