Search results for: SINGLE MACHINE
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Testing of Technical Fabrics under Fast Camera Control
PublicationThe dynamic development of measurement and recording techniques has been changing the way one conceives material strength. In this study, two different methods of evaluating the strength of fabrics are compared. The first is the typical and commonly used technique based on the use of a testing machine. The second method uses the so-called “fast camera” to monitor the entire process of the destruction of a fabric sample and analyse...
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Dynamics Conscious Approach to Tribometer Design and Tribo-testing
PublicationIn the paper findings are discussed on the issue of dynamic characteristics of a tribometer as a factor influencing the result of the tribological experiment. An advanced approach to tribo-testing is attempted with integrated dynamic analysis of the tribometer and the sliding pair. The fundamental idea is explored of the tribometer being regarded as any machine in which friction is inflicted with all the resulting consequences...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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The methodology for determining of the value of cutting power for cross cutting on optimizing sawing machine
PublicationIn the article the methodology of forecasting the energy effects of the cross-cutting process using the classical method, which takes into account the specific cutting resistance, is presented. The values of cutting power for the cross-cutting process of two types of wood (softwood and hardwood) were forecasted for the optimizing sawing machine with using presented methodology. The cross-cutting process with high values of feed...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublicationMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Sensorless five-phase induction motor drive with third harmonic injection and inverter output filter
PublicationThe paper presents a sensorless control approach for a five-phase induction motor drive with third harmonic injection and inverter output filter. In the case of the third harmonic injection being utilised in the control, the physical machine has to be divided into two virtual machines that are controlled separately and independently. The control system structure is presented in conjunction with speed and rotor flux observers that...
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Measurement of mass flow of viscous liquid through a Cylindrical Orifice under laminar flow (CylOr)
Open Research DataThe data was obtained as part of the project "Measurement of mass flow of viscous liquid through a Cylindrical Orifice under laminar flow (CylOr)", in which flow tests of hydraulic oil through a cylindrical orifice with a thickness of l = 25 mm and a throat b = 0.5 (diameter pipes D = 50 mm, orifice diameter d = 25 mm) on the test stand at the Department...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Modélisation d'ordre non entier des machines synchrones. Modèle fréquentiel non linéaire, identification des paramètres, calcul de la réponse temporelle.
PublicationDans les réseaux d'énergie électrique contemporains, on assiste à une diversification considérable des différentes sources d'énergie. L'énergie produite est transformée par une grande quantité de dispositifs électriques pour être finalement acheminée à diverses installations électriques. Il devient donc primordial d'améliorer les modèles des différents composants électriques afin de pouvoir prévoir les interactions entre eux et...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Scheduling of compatible jobs on parallel machines
PublicationThe dissertation discusses the problems of scheduling compatible jobs on parallel machines. Some jobs are incompatible, which is modeled as a binary relation on the set of jobs; the relation is often modeled by an incompatibility graph. We consider two models of machines. The first model, more emphasized in the thesis, is a classical model of scheduling, where each machine does one job at time. The second one is a model of p-batching...
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Possibility of Fault Detection in Sensorless Electric Drives
PublicationThe work presents a fault detection method for an induction motor drive system with inverter output filter. This approach make use of a load torque state observer, which complete structure is presented along with the used control structure. Moreover, the demonstrated drive system operates without rotor speed measurement in conjunction with the multiscalar control. The verification of the demonstrated idea was performed on an experimental...
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A Review of Reduction Methods of Impact of Common-Mode Voltage on Electric Drives.
PublicationIn this survey paper, typical solutions that focus on the reduction in negative effects resulting from the common-mode voltage influence in AC motor drive applications are re-examined. The critical effectiveness evaluation of the considered methods is based on experimental results of tests performed in a laboratory setup with an induction machine fed by an inverter. The capacity of a common-mode voltage level reduction and voltage...
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublicationThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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Sensorless Disturbance Detection for Five Phase Induction Motor with Third Harmonic Injection
PublicationThe paper presents a sensorless disturbance detection procedure that was done on a five phase induction motor with third harmonic injection. A test bench was developed where a three phase machine serves as disturbance generator of different frequencies. The control of the machines is based on multi scalar variables that ensures an independent control of the motor EMF and the rotor flux. For disturbance identification a speed observer...
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...
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The forecasted values of cutting power for sawing on band sawing machines for Polish Scots pine wood (Pinus sylvestris L.) in a function of its provenance.
PublicationIn this paper the predicted values of cutting power for band sawing machine (EB 1800, f. EWD), which is used in the Polish sawmills, were showed. The values of cutting power were forecasted for Scots pine (Pinus sylvestris L.) wood of five provenances from Poland. These values were determined using an innovative method of predicting the cutting power, which takes into account of elements of fracture mechanics. The resulting predictions...
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Mechanical properties of the human stomach under uniaxial stress action
PublicationThe aim of this study was to estimate the range of mechanical properties of the human stomach in order to use the collected data in numerical modelling of surgical stapling during resections of the stomach. The biomedical tests were conducted in a self-developed tensile test machine. Twenty-two fresh human stomach specimens were used for the experimental study of its general strength. The specimens were obtained from morbidly obese...
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The Use of an Autoencoder in the Problem of Shepherding
PublicationThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublicationThe aim of the article is to present an algorithm of Support Vector Machine created to forecast the impact of traffic-induced vibrations on residential buildings. The method is designed to classify the object into one of two classes. The classification into the first class means that there is no impact of vibrations on the building, while classification to the second class indicates the possible influence and suggests the execution...
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Parametrical 3D model of an asynchronous motor - AutoCAD application.
PublicationA computer program for automatic drawing of 3D models of squirrel-cage induction motors is presented in this paper. The created model of a machine is of parametrical nature, which means that the user defines geometry of particular elements (shaft, stator core, bearing, windings etc.) on the basis dimensions and some other parameters e.g. type of bearing, kind of winding, number of slots. This program is useful for 3D modelling...
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SELECTION OF DIAGNOSTIC FUNCTIONS IN A WHEELED TRACTOR
PublicationIn a classical approach to damage diagnosis, the technical condition of an analyzed machine is identified based on the measured symptoms, such as performance, thermal state or vibration parameters. In wheeled tractor the fundamental importance has monitoring and diagnostics during exploitation concerning technical inspection and fault element localizations. The main functions of a diagnostic system are: monitoring tractor components...
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AffecTube — Chrome extension for YouTube video affective annotations
PublicationThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Augmenting digital documents with negotiation capability
PublicationActive digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...
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Improving all-reduce collective operations for imbalanced process arrival patterns
PublicationTwo new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Scientific research in the Department of Machine Design and Automotive Engineering
PublicationShort descriptions of various research subjects taken up at the Department of Machine Design and Automotive Engineering are included in the paper. The subjects cover a wide range of bearing systems and tribology research and the research on tires and road surfaces. A third field of activity is biomedical engineering – with the attempts to improve methods of modelling biological materials in FEM calculations. The Department has...
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THE PHASE SHIFTERS INFLUENCE ON THE POWER SYSTEM STABILITY
PublicationThe paper presents the effect of phase shifters as FACTS devices on the possibility of improving the angle stability. Presented results obtained by the dynamic simulation performed on the mathematical model of the three machine system cooperating with the 400 kV network. The generative blocks models include turbine models with their controllers and models of synchronous generators with their excitation systems and voltage regulation....
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Five-phase squirrel-cage motor. Construction and drive properties
PublicationThis paper presents the simulation and experimental results of a five-phase squirrel-cage induction motor. The new machine has been designed to operate in a drive system with third harmonic rotor flux injection in order to improve the motor torque utilization. The motor structure, the mathematical model as well as the laboratory prototype have been described. The motor speed-torque characteristics and transients are elaborated...
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Induction machine behavioral modeling for prediction of EMI propagation.
PublicationThis paper presents the results of wideband behavioral modeling of an induction machine (IM). The proposed solution enables modeling the IM differential- and common-mode impedance for a frequency range from 1 kHz to 10 MHz. Methods of parameter extraction are derived from the measured IM impedances. The developed models of 1.5 kW and 7.5 kW induction machines are designed using the Saber Sketch scheme editor and simulated in the...
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Diagnosis of bearing damage in induction motors by instantaneous power analysis
PublicationResearch of the machine with simulated bearing damages has been carried out, where variable load torque, simulating bearing damage, was introduced. The results show that components which can be used for bearings diagnosis appear in the spectrum of the product of current and supply voltage instantaneous values. These components are easier to identify than the components of current spectrum, which have been used so far in diagnostic...
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Cutting power estimation of the bandsawing process of beech wood (Fagus sylvatica L.) dried in three operating modes
PublicationIn this paper the predicted values of cutting power for bandsawing machine (ST100R, f. Stenner), which is located at the sawmill company Complex in Dziemiany, were presented. The values of cutting power were forecasted for beech wood (Fagus sylvatica L.), from the northern part of Pomerania region in Poland, which was dried in three operating modes: BKP - air drying at 25oC, BKS - air-steam mixture drying at 80oC, BKW - steam drying...
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ANALYSIS OF THE LOAD-CARRYING CAPACITY OF A HYDRODYNAMIC WATER-LUBRICATED BEARING IN A HYDROELECTRIC POwER PLANT
PublicationThe paper presents an analysis of the load-carrying capacity of a historic hydrodynamic water-lubricated radial bearing of an unconventional segment design installed in the Braniewo Hydroelectric Power Plant. The aim of the calculations was to determine whether the bearing operates in the conditions of hydrodynamic or mixed lubrication, as well as to establish the optimal geometry of the axial grooves allowing for the highest load-carrying...
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Failure of cold-formed beam: How does residual stress affect stability?
PublicationIn machine industry, stresses are often calculated using simple linear FEM analysis. Occasional failures of elements designed in such a way require recomputation by means of more sophisticated methods, eg. including plasticity and non-linear effects. It usually leads to investigation of failure causes and improvement of an element in order to prevent its unwanted behavior in the future. The study presents the case where both linear...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublicationWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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A Study on Emission of Airborne Wear Particles from Car Brake Friction Pairs
PublicationThe emission of airborne wear particles from friction material / cast iron pairs used in car brakes was investigated, paying special attention to the influence of temperature. Five low-metallic materials and one non-asbestos organic material were tested using a pin-on-disc machine. The machine was placed in a sealed chamber to allow airborne particle collection. The concentration and size distribution of 0.0056 to 10 μm particles...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublicationHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
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An electric ring thruster as auxiliary manoeuvring propulsion system for watercraft - construction analysis
PublicationThe reported project aimed at examining properties and purposefulness of use of modern electromagneticbearings for a screw propeller in a prototype version of a synchronous ring motor with rare earths magnets.Bearings of this type generate electromagnetic forces which keep the rotor in a state of levitation. Therotating machine with magnetic bearings can work in any environment which reveals diamagnetic properties(air, vacuum,...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Approximation algorithms for job scheduling with block-type conflict graphs
PublicationThe problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model stems from a well-established line of research combining scheduling theory...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Polyarmonic model of synchronous generator for analysis of autonomous power generation systems
PublicationAbstract: This paper presents the polyharmonic modelling of synchronous generator (SG) in machine variables. The simple geometry and windings physical layout has been used for inductance calculations of a salient-pole SG. The main advantage of this model is the ease of describing an autonomous power generation system (APGS) in terms of its topology and thus providing effective analysis at the static and dynamic states, both for...
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Scheduling of identical jobs with bipartite incompatibility graphs on uniform machines. Computational experiments
PublicationWe consider the problem of scheduling unit-length jobs on three or four uniform parallel machines to minimize the schedule length or total completion time. We assume that the jobs are subject to some types of mutual exclusion constraints, modeled by a bipartite graph of a bounded degree. The edges of the graph correspond to the pairs of jobs that cannot be processed on the same machine. Although the problem is generally NP-hard,...
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublicationThe aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...