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Search results for: lsvm
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Multicomponent ionic liquid CMC prediction
PublicationWe 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
PublicationDo 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
PublicationElectrocatalytic 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
PublicationThis 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
PublicationA 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
PublicationEndüstri 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
PublicationHearing 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
PublicationThis 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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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublicationThis 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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Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA 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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Composite (La, Sr)MnO3-YSZ cathode for SOFC
PublicationW 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
PublicationReferat 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
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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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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New method using bilinear transformation for parameter identification ofanticorossion coatings.
PublicationArtykuł 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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Neural networks and deep learning
PublicationIn 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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Support Vector Machine Applied to Road Traffic Event Classification
PublicationThe 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
PublicationThe 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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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn 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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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...
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Algorytmy klasyfikacji i uczenia w rozpoznawaniu treści
PublicationZadanie 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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Determination of the ionic conductivity of Sr-doped lanthanum manganite by modified Hebb–Wagner technique
PublicationThe 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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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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
PublicationA 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
PublicationConsidering 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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Visual Lip Contour Detection for the Purpose of Speech Recognition
PublicationA 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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THE DETERMINATION OF ABRASION RESISTANCE OF SELECTED BIOMATERIALS FOR THE FRICTION PAIRS IN THE HIP JOINT ENDOPROSTHESIS
PublicationThe 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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Viewpoint independent shape-based object classification for video surveillance
PublicationA 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
PublicationThe 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
PublicationThis 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
PublicationThis 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
PublicationAn 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
PublicationAn 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
PublicationOther 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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A Direct Modulation for Matrix Converters based on the Onecycle Atomic operation developed in Verilog HDL.
PublicationThis 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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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe 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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Subspace Algorithms for Face Verification
PublicationW 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
PublicationThe paper describes the method for detecting precise position and time of vehicles parking in a parking lot. This task is trivial in case of favorable camera orientation but gets much more complex when an angle between the camera viewing axis and the ground is small. The method utilizes background subtraction and object tracking algorithms for detecting moving objects in a video stream. Objects are classified into vehicles and...
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Rozpoznawanie chorób układu pokarmowego z wykorzystaniem technik sztucznej inteligencji
PublicationCelem 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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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publicationis 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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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublicationThe 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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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart 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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ANALIZA PARAMETRÓW SYGNAŁU MOWY W KONTEKŚCIE ICH PRZYDATNOŚCI W AUTOMATYCZNEJ OCENIE JAKOŚCI EKSPRESJI ŚPIEWU
PublicationPraca 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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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis 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...
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Buzz-based recognition of the honeybee colony circadian rhythm
PublicationHoneybees 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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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe 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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Paremetrization of sounds for recognizing hazarodus events
PublicationNowoczesne 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
PublicationWikipedia- 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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Detection of Denatonium Benzoate (Bitrex) Remnants in Noncommercial Alcoholic Beverages by Raman Spectroscopy
PublicationIllegal 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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Sleep Apnea Detection by Means of Analyzing Electrocardiographic Signal
PublicationObstructive 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...