Filtry
wszystkich: 148
wybranych: 126
Wyniki wyszukiwania dla: lsvm
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Selecting Features with SVM
PublikacjaA common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...
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ARIMA vs LSTM on NASDAQ stock exchange data
PublikacjaThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Using LSTM networks to predict engine condition on large scale data processing framework
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublikacjaIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
PublikacjaDevices capable of tracking the user’s gaze have become significantly more affordable over the past few years, thus broadening their application, including in-home and office computers and various customer service equipment. Although such devices have comparatively low operating frequencies and limited resolution, they are sufficient to supplement or replace classic input interfaces, such as the keyboard and mouse. The biometric...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublikacjaIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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Text Documents Classification with Support Vector Machines
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Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublikacjaThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
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Autocovariance based weighting strategy for time series prediction with weighted LS-SVM
PublikacjaPrzedstawiono metodę konstrukcji algorytmów z funkcją jądra, a także dwa algorytmy uzyskane poprzez użycie różnych funkcji straty. Zaproponowano kowariacyjną strategię ważenia algorytmów z kwadratową funkcją straty do problemu predykcji chaotycznych przebiegów czasowych.
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Ewolucyjny dobór funkcji jądra SVM wspólnego dla zbioru podobnychzadań klasyfikacyjnych
PublikacjaPraca przedstawia ewolucyjną metodę kształtowania funkcji jądra wmetodzie SVM wspólnego dla zbioru podobnych zadań klasyfikacyjnych(z tej samej dziedziny) z wykorzystaniem aproksymatora neuronowego.Pokazano możliwość wbudowania funkcji ekstrakcji cech do funkcji jądraSVM za pomocą prostego łączenia aproksymatorów standardowej funkcjijądra i ekstraktora. Opisane zostały również teoretyczne podstawy metodywektorów wspierających (SVM).
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm
PublikacjaThis paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration...
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Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach
PublikacjaIn this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely on received signal strength...
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Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach
PublikacjaIn this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely...
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WYKORZYSTANIE SIECI NEURONOWYCH I METODY WEKTORÓW NOŚNYCH SVM W PROCESIE ROZPOZNAWANIA AKTYWNOŚCI RUCHOWEJ PACJENTÓW DOTKNIĘTYCH CHOROBĄ PARKINSONA
PublikacjaChoroba Parkinsona (ang. PD - Parkinson Disease) zaliczana jest do grupy chorób neurodegeneracyjnych. Jest to powoli postępująca choroba zwyrodnieniowa ośrodkowego układu nerwowego. Jej powstawanie związane jest z zaburzeniem produkcji dopaminy przez komórki nerwowe mózgu. Choroba manifestuje się zaburzeniami ruchowymi. Przyczyna występowania tego typu zaburzeń nie została do końca wyjaśniona. Leczenie osób dotkniętych PD oparte...
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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
PublikacjaIntroduction: 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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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Characteristics of La0.8Sr0.2Ga0.8Mg0.2O3-delta -supported micro-tubular solid oxide fuel cells with bi-layer and tri-layer electrolytes
PublikacjaIn this study, La0.8Sr0.2Ga0.8Mg0.2O3−δ (LSGM)-supported micro tubular solid oxide fuel cells (T-SOFCs) with two different configurations, one containing an LSGM–Ce0.6La0.4O2−δ (LDC) bi-layer electrolyte (Cell A) and one containing an LDC–LSGM–LDC tri-layer electrolyte (Cell B), were fabricated using extrusion and dip-coating. After optimizing the paste formulation for extrusion, the flexural strength of the dense and uniform LSGM...
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Characteristics of La 0.8 Sr 0.2 Ga 0.8 Mg 0.2 O 3-δ -supported micro-tubular solid oxide fuel cells with LaCo 0.4 Ni 0.6-x Cu x O 3-δ cathodes
PublikacjaIn this study, micro-tubular solid oxide fuel cells (T-SOFCs) with extruded La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) electrolyte as the mechanical support and LaCo0.4Ni0.6O3-δ (LCNO) or LaCo0.4Ni0.4Cu0.2O3-δ (LCNCO) as cathodes were prepared and characterized. Partial substitution of Cu for the Ni-ion positions in the LCNO lattices was found to significantly enhance the densification and accelerate the grain growth. The porosity-corrected...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Space-vector pulsewidth modulation for a seven-level cascaded H-bridge inverter with the control of DC-link voltages
PublikacjaThe control strategy of DC-link voltages for a seven-level Cascaded H-Bridge inverter is proposed in this paper. The DC-link voltage balancing is accomplished by appropriate selection of H-Bridges and control of their duty cycles in Space-Vector Modulation (SVM) algorithm. The proposed SVM method allows to maintain the same voltage level on all inverter capacitors. Regardless of the balancing function, the...
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Space vector modulation in multilevel inverters of the servo drives of the trajectory measurements telescopes
PublikacjaUsing the MatLab/Simulink mathematical model of a three-phase three-level voltage inverter, the influence of the space-vector modulation (SVM) algorithm on the pulsations of the current (torque) of an AC motor in the range of low rotation speeds is considered. It is shown that the SVM of the second kind does not provide a pulsations level comparable to the pulsations of a sinusoidal pulse-width modulation (SPWM), both in the static...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublikacjaHypertensive 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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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Efficiency of gas detection algorithms using fluctuation enhanced sensing
PublikacjaEfficiency of various gas detection algorithms by applying fluctuation enhanced sensing method was discussed. We have analyzed resistance noise observed in resistive WO3- nanowires gas sensing layers. Power spectral densities of the recorded noise were used as the input data vectors for two algorithms: the principal component analysis (PCA) and the support vector machine (SVM). The data were used to determine gas concentration...
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Investigation methods of ionic conductivity measurements in polycrystalline MIEC (mixed ionic-electronic conductor) based on perovskite ceramics
PublikacjaPaper about the measurements of ionic conductivity in LSM and strontium titanate ceramics.
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Effects of La0.8Sr0.2MnO3 and Ag electrodes on bismuth-oxide-based low-temperature solid electrolyte oxygen generators
PublikacjaIn this study, La0.8Sr0.2MnO3 (LSM) was used as the ceramic electrode in a (Bi1.50Y0.50)0.98Zr0.04O3+δ (BYO)-based solid electrolyte oxygen generator (SEOG) and its performance was compared with that of a previously studied high-fire Ag electrode. Among La0.6Sr0.4Co0.2Fe0.8O3, LaNi0.6Fe0.4O3, Cu1.4Mn1.6O4, and LSM materials, only LSM materials did not trigger any chemical reaction or interdiffusion with BYO at temperatures up to...
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Representation of hypertext documents based on terms, Links and text compressibility
PublikacjaOpisano metody reprezentacji dokumentów tekstowych oparte na słowach, wzajemnych powiązaniach i metodach kompresji. Dokonano ich oceny w oparciu o klasyfikator SVM.
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Towards automatic classification of Wikipedia content
PublikacjaArtykuł opisuje podejście do automatycznej klasyfikacji artykułów w Wikipedii. Przeanalizowane zostały reprezentacje tekstu bazujące na treści dokumentu i wzajemnych powiązaniach. Przedstawiono rezultaty zastosowania klasyfikatora SVM.
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Classification of Music Genres Based on Music Separation into Harmonic and Drum Components . Klasyfikacja gatunków muzycznych wykorzystująca separację instrumentów muzycznych
PublikacjaThis article presents a study on music genre classification based on music separation into harmonic and drum components. For this purpose, audio signal separation is executed to extend the overall vector of parameters by new descriptors extracted from harmonic and/or drum music content. The study is performed using the ISMIS database of music files represented by vectors of parameters containing music features. The Support Vector...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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Optimized Space Vector Modulation strategy for five phase voltage source inverter with third harmonic injection
PublikacjaThis paper presents a simple and an effective SVM algorithm for five-phase Voltage-Source Inverters with the possibility to control independently the voltage vectors for fundamental and auxiliary orthogonal subspaces. The essential benefit is that output voltage is generated using only four active voltage vectors with limited numbers of switching. In the proposed solution, four active vectors are arbitrary chosen, independent of...
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High-performance anode-supported solid oxide fuel cells with co-fired Sm0.2Ce0.8O2-δ/La0.8Sr0.2Ga0.8Mg0.2O3−δ/Sm0.2Ce0.8O2-δ sandwiched electrolyte
PublikacjaIn this study, intermediate-temperature solid oxide fuel cells (IT-SOFCs) with a nine-layer structure are constructed via a simple method based on the cost-effective tape casting-screen printing-co-firing process with the structure composed of a NiO-based four-layer anode, a Sm0.2Ce0·8O2-δ(SDC)/La0·8Sr0.2Ga0.8Mg0·2O3−δ (LSGM)/SDC tri-layer electrolyte, and an La0·6Sr0·4Co0·2Fe0·8O3-δ (LSCF)-based bi-layer cathode. The resultant...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Wikipedia Articles Representation with Matrix'u
PublikacjaIn the article we evaluate different text representation methods used for a task of Wikipedia articles categorization. We present the Matrix’u application used for creating computational datasets ofWikipedia articles. The representations have been evaluated with SVM classifiers used for reconstruction human made categories.
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Multicomponent ionic liquid CMC prediction
PublikacjaWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Text categorization with semantic commonsense knowledge: First results
PublikacjaDo przetwarzania tekstów typowo wykorzystuje się reprezentacjeBOW. Podejście takie nie daje jednak dobrych rezultatów w sytuacjigdy podobne dokumenty nie współdzielą ze sobą słów.W artykule zaprezentowano podejście do konstrukcji funkcjijądra dla klasyfikatorów SVM opartego na zewnętrznej bazie wiedzyo pojęciach językowych.
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Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublikacjaElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublikacjaA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Development of an AI-based audiogram classification method for patient referral
PublikacjaHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Detection of Delamination in Laminate Wind Turbine Blades Using One-Dimensional Wavelet Analysis of Modal Responses
PublikacjaThis paper demonstrates the effectiveness of a nondestructive diagnostic technique used to determine the location and size of delamination in laminated coatings of wind turbine blades. This is realized based on results of numerical and experimental investigations obtained by the use of the finite element method (FEM) and laser scanning vibrometry (LSV). The proposed method is based on the one-dimensional continuous wavelet transform...
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Dangerous sound event recognition using Support Vector Machine classifiers
PublikacjaA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublikacjaThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
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Composite (La, Sr)MnO3-YSZ cathode for SOFC
PublikacjaW pracy przedstawiono właściwości elektryczne kompozytów (La,Sr)MnO3-YSZ. Materiały te dzieki swoim włąściwościom mogą staniwć dobry materiał na katody ogniw paliwowych. Przedstawiono też wyniki badań ogniwa paliwowego pracującego z paliwem wodorowym zbudowanego na bazie katody z kompozytu LSM-YSZ i anody Ni-YSZ. Uzyskano gęstośc mocy 0.26 W cm−2 przy temperaturze 850°C.
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Modelowanie trakcyjnego układu napędowego z silnikiem ipm ze sterownikiem cyfrowym w środowisku matlab/simulink
PublikacjaReferat przedstawia model symulacyjny trakcyjnego układu napędowego z silnikiem IPM. Omówiono strukturę układu oraz algorytm sterowania momentem silnika. Opisano model symulacyjny uwzględniający technikę modulacji napięć wyjściowych falownika typu SVM oraz dyskretne działanie sterownika cyfrowego. Przedstawiono wybrane wyniki symulacyjne i skonfrontowano je z otrzymanymi z rzeczywistego układu napędowego. Opisano przyczyny różnic...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(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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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublikacjaThis 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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Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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New method using bilinear transformation for parameter identification ofanticorossion coatings.
PublikacjaArtykuł przedstawia nową metodę diagnostyki powłok antykorozyjnych z wykorzystaniem przekształcenia biliniowego. Możliwa jest identyfikacja parametrów schematu zastępczego powłoki na podstawie pomiaru impedancji obiektu na kilku, optymalnie dobranych częstotliwościach pomiarowych. Podano zasady doboru optymalnych częstotliwości pomiarowych. Ich liczba jest równa liczbie elementów schematu zastępczego. Opracowany algorytm identyfikacji...
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Support Vector Machine Applied to Road Traffic Event Classification
PublikacjaThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublikacjaThe 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...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublikacjaIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Determination of the ionic conductivity of Sr-doped lanthanum manganite by modified Hebb–Wagner technique
PublikacjaThe Hebb–Wagne rpolarization method with the electron blocking electrode has been discussed in this paper in aim to determine a partial ionic conductivity of Sr-doped lanthanum manganite.The “limiting current” in the proposed system was measured using the two-point DC technique with additional Pt electrode between LSM and blocking electrode.The electrochemical model based on bulk diffusion processes and Boltzmann statistics has...
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Algorytmy klasyfikacji i uczenia w rozpoznawaniu treści
PublikacjaZadanie klasyfikacji treści może zostać podzielone na dwa etapy: ekstrakcji cech istotnych dla podziału na klasy oraz etapu klasyfikacji na podstawie cech wyznaczonych w poprzednim etapie. Dzięki takiemu podziałowi, możliwe jest użycie w drugim etapie standardowych algorytmów budowy (uczenia) klasyfikatorów, takich klasyfikator bayesowski, drzewa decyzyjne, sztuczne sieci neuronowe czy metoda wektorów wspierających (SVM). Przy...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Novel 2-(2-alkylthiobenzenesulfonyl)-3-(phenylprop-2-ynylideneamino)guanidine derivatives as potent anticancer agents – Synthesis, molecular structure, QSAR studies and metabolic stability
PublikacjaA series of new 2-(2-alkylthiobenzenesulfonyl)-3-(phenylprop-2-ynylideneamino)guanidine derivatives have been synthesized and evaluated in vitro by MTT assays for their antiproliferative activity against cell lines of colon cancer HCT-116, cervical cancer HeLa and breast cancer MCF-7. The obtained results indicated that these compounds display prominent cytotoxic effect. The best anticancer properties have been observed for derivatives...
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Performance assessment of OpenMP constructs and benchmarks using modern compilers and multi-core CPUs
PublikacjaConsidering ongoing developments of both modern CPUs, especially in the context of increasing numbers of cores, cache memory and architectures as well as compilers there is a constant need for benchmarking representative and frequently run workloads. The key metric is speed-up as the computational power of modern CPUs stems mainly from using multiple cores. In this paper, we show and discuss results from running codes such as:...
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THE DETERMINATION OF ABRASION RESISTANCE OF SELECTED BIOMATERIALS FOR THE FRICTION PAIRS IN THE HIP JOINT ENDOPROSTHESIS
PublikacjaThe key requirement for the modern endoprosthesis is high durability of the friction components, which results in long and trouble-free operation in the human body. The durability of currently used endoprosthesis is often limited by tribological wear processes of friction components (e.g. between the head and the acetabular component in a hip joint endoprosthesis) [8, 19, 23, 24]. In order to compare the tribological wear, tribological...
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Visual Lip Contour Detection for the Purpose of Speech Recognition
PublikacjaA method for visual detection of lip contours in frontal recordings of speakers is described and evaluated. The purpose of the method is to facilitate speech recognition with visual features extracted from a mouth region. Different Active Appearance Models are employed for finding lips in video frames and for lip shape and texture statistical description. Search initialization procedure is proposed and error measure values are...
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Viewpoint independent shape-based object classification for video surveillance
PublikacjaA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
PublikacjaThis paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Audio-visual surveillance system for application in bank operating room
PublikacjaAn audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublikacjaAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Subspace Algorithms for Face Verification
PublikacjaW rzeczywistych zastosowaniach problem weryfikacji wydaje się ważniejszy od klasyfikacji. Na ogół dysponujemy jedynie niewielkim zbiorem obrazów uczących reprezentujących daną osobę, a naszym zadaniem jest podjęcie decyzji odnośnie tego, czy nowo pozyskana fotografia jest do nich wystarczająco podobna - bez użycia oddzielnego zbioru przykładów negatywnych. W takim przypadku uzasadnione wydaje się zastosowanie metody podprzestrzeni,...
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Camera Orientation-Independent Parking Events Detection
PublikacjaThe 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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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publikacjais evaluated on 9 patients, data analysis methods are described, and experiments of correlating Glasgow Coma Scale with extracted features describing subjects performance in therapeutic exercises exploiting EEG and eyetracker are presented. Performance metrics are proposed, and k-means clusters used to define concepts for mental states related to EEG and eyetracking activity. Finally, it is shown that the strongest correlations...
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Rozpoznawanie chorób układu pokarmowego z wykorzystaniem technik sztucznej inteligencji
PublikacjaCelem pracy jest przedstawienie i ocena algorytmów rozpoznawania chorób w filmach endoskopowych pod kątem możliwości ich zastosowania do budowy systemów automatycznego wykrywania chorób dla rzeczywistego wspomagania badań lekarskich. Porównano efektywność najnowszych algorytmów poprzez pomiar ich skuteczności w zaawansowanym środowisku testowym, zbudowanym w oparciu o materiały z filmów endoskopowych, opracowane we współpracy z...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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A Direct Modulation for Matrix Converters based on the Onecycle Atomic operation developed in Verilog HDL.
PublikacjaThis paper presents a fast direct Pulse Width Modulation (PWM) algorithm for the Conventional Matrix Converters (CMC) developed in Verilog Hardware Description language (HDL). All PWM duty cycle calculations are performed in one cycle by an atomic operation designed as a digital module using FPGA basic blocks. The algorithm can be extended to any number of output phase. The improved version of the discontinuous Direct Analytic...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublikacjaThe efficiency of micellar solubilization is dictated inter alia by the properties of the solubilizate, the type of surfactant, and environmental conditions of the process. We, therefore, hypothesized that using the descriptors of the aforementioned features we can predict the solubilization efficiency, expressed as molar solubilization ratio (MSR). In other words, we aimed at creating a model to find the optimal surfactant and...
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ANALIZA PARAMETRÓW SYGNAŁU MOWY W KONTEKŚCIE ICH PRZYDATNOŚCI W AUTOMATYCZNEJ OCENIE JAKOŚCI EKSPRESJI ŚPIEWU
PublikacjaPraca dotyczy podejścia do parametryzacji w przypadku klasyfikacji emocji w śpiewie oraz porównania z klasyfikacją emocji w mowie. Do tego celu wykorzystano bazę mowy i śpiewu nacechowanego emocjonalnie RAVDESS (Ryerson Audio-Visual Database of Emotional Speech and Song), zawierającą nagrania profesjonalnych aktorów prezentujących sześć różnych emocji. Następnie obliczono współczynniki mel-cepstralne (MFCC) oraz wybrane deskryptory...
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Paremetrization of sounds for recognizing hazarodus events
PublikacjaNowoczesne systemy monitoringu działają na zasadzie automatycznego wykrywania niebezpiecznych zdarzeń na podstawie analizy obrazu z kamer i dźwięku z mikrofonów. W niniejszej publikacji skupiono się na pierwszym etapie rozpoznawania zdarzeń dźwiękowych, jakim jest parametryzacja dźwięku. Podstawą do skutecznego działania systemu jest znalezienie parametrów, których zmienność najlepiej odzwierciedla cechy charakterystyczne dźwięku...
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Automatyczna klasyfikacja artykułów Wikipedii
PublikacjaWikipedia- internetowa encyklopedia do organizacji artykułów wykorzystuje system kategorii. W chwili obecnej proces przypisywania artykułu do odpowiednich kategorii tematycznych realizowany jest ręcznie przez jej edytorów. Zadanie to jest czasochłonne i wymaga wiedzy o strukturze Wikiedii. Ręczna kategoryzacja jest również podatna na błędy wynikające z faktu, że przyporządkowanie artykułu don kategorii odbywa się w oparciu o arbitralną...
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Liveness measurements using optical flow for biometric person authentication
PublikacjaAutomatyczne rozpoznawanie twarzy jest jedną z najpopularniejszych technik biometrycznych, jednak nawet najdokładniejsze algorytmy identyfikacji okażą się bezużyteczne, jeśli będzie można je oszukać, np. używając zdjęcia zamiast rzeczywistej osoby. Dlatego też odpowiedni pomiar żywotności jest niezwykle istotny. W pracy zaprezentowano metodę, która jest w stanie rozróżnić pomiędzy sekwencjami wideo pokazującymi żywe osoby oraz...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Sleep Apnea Detection by Means of Analyzing Electrocardiographic Signal
PublikacjaObstructive sleep apnea (OSA) is a condition of cyclic, periodic ob-struction (stenosis) of the upper respiratory tract. OSA could be associated with serious cardiovascular problems, such as hypertension, arrhythmias, hearth failure or peripheral vascular disease. Understanding the way of connection between OSA and cardiovascular diseases is important to choose proper treatment strategy. In this paper, we present a method for integrated...
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Detection of Denatonium Benzoate (Bitrex) Remnants in Noncommercial Alcoholic Beverages by Raman Spectroscopy
PublikacjaIllegal alcoholic beverages are often introduced into market using cheap technical alcohol, which is contaminated by denatonium benzoate (Bitrex) of very small concentration. Bitrex is the most bitter chemical compound and has to be removed before alcohol consumption. The home-made methods utilize sodium hypochlorite to disintegrate particles of denatonium benzoate in alcohol and to remove bitter taste before trading. In this experimental...
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Rozpoznawanie dynamicznych i statycznych gestów rąk w zastosowaniu do sterowania aplikacjami komputerowymi
PublikacjaW referacie przedstawiono interfejs, metody oraz algorytmy sterowania komputerem za pomocą dynamicznych i statycznych gestów rąk. Komponentami opracowanego rozwiązania są komputer klasy PC wraz z opracowanym interfejsem i oprogramowaniem, kamera internetowa oraz projektor multimedialny. Gesty rozpoznawane są w procesie analizy obrazu wizyjnego pozyskanego z kamery internetowej przymocowanej do projektora oraz analizy obrazu wyświetlanego...
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Rapid Evaluation of Poultry Meat Shelf Life Using PTR-MS
PublikacjaThe use of proton transfer reaction mass spectrometry (PTR-MS) for freshness classification of chicken and turkey meat samples was investigated. A number of volatile organic compounds (VOCs) were selected based on the correlation (> 95%) of their concentration during storage at 4 °C over a period of 5 days with the results of the microbial analysis. In order to verify if the selected compounds are not sample-specific, a number...
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Buzz-based recognition of the honeybee colony circadian rhythm
PublikacjaHoneybees are one of the highly valued pollinators. Their work as individuals is appreciated for crops pollination and honey production. It is believed that work of an entire bee colony is intense and almost continuous. The goal of the work presented in this paper is identification of bees circadian rhythm with a use of sound-based analysis. In our research as a source of information on bee colony we use their buzz that have been...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublikacjaThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...