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Search results for: CLASSIFICATION ALGORITHMS
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A new diagnostic method for evaluation of cardiosurgery wound healing
PublicationOne of important and still unsolved problems in medicine is the question of objective and quantitative evaluation of post-surgery wound healing. The aim of this research is to analyse possibility and value of using the newly elaborated infrared imaging procedure – Active Dynamic Thermography (ADT) – for quantitative description of wound healing processes in cardiosurgery. Both, classical thermal figures of merit as well as ADT...
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Categorization of Cloud Workload Types with Clustering
PublicationThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
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Harmony Search for Data Mining with Big Data
PublicationIn this paper, some harmony search algorithms have been proposed for data mining with big data. Three areas of big data processing have been studied to apply new metaheuristics. The first problem is related to MapReduce architecture that can be supported by a team of harmony search agents in grid infrastructure. The second dilemma involves development of harmony search in preprocessing of data series before data mining. Moreover,...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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A comparative study of English viseme recognition methods and algorithm
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...
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Multibeam data processing for 3D object shape reconstruction
PublicationThe technology of hydroacoustic scanning offers an efficient and widely-used source of geospatial information regarding underwater environments, providing measurement data which usually have the structure of irregular groups of points known as point clouds. Since this data model has known disadvantages, a different form of representation based on representing surfaces with simple geometric structures, such as edges and facets,...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC
PublicationThis paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Redukcja czasu analizy MZP przez ograniczenie rozmiaru rozwiązania
PublicationAnaliza drzew niezdatności jest uznaną metodą analizy bezpieczeństwa systemów. Notacja ECSDM pozwala definiować zależności czasowe między zdarzeniami drzewa oraz przeanalizować je w celu określenia zależności pomiędzy zdarzeniami z Minimalnych Zbiorów Przyczyn (MZP). Dzięki wprowadzeniu klasyfikacji zdarzeń z MZP można wyodrębnić zależności czasowe istotne dla zapobiegania wywoływania hazardu przez konkretny MZP. Pozostałe zależności...
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Voice command recognition using hybrid genetic algorithm
PublicationAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Improving automatic surveillance by sound analysis
PublicationAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Video content analysis in the urban area telemonitoring system
PublicationThe task of constant monitoring of video streams from a large number of cameras and reviewing the recordings in order to find a specified event requires a considerable amount of time and effort from the system operators and it is prone to errors. A solution to this problem is an automatic system for constant analysis of camera images being able to raise an alarm if a predefined event is detected. The chapter presents various aspects...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn 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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Acoustic Processor of the Mine Countermeasure Sonar
PublicationThis paper presents the concept of an acoustic processor of the mine countermeasure sonar. Developed at the Department of Marine Electronics Systems, Gdansk University of Technology, the acoustic processor is an element of the MG-89, an underwater acoustic station. The focus of the article is on the modules of the processor. They are responsible for sampling analogue signals and implementing the algorithms controlling the measurement...
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AUTOMATYCZNA KLASYFIKACJA MOWY PATOLOGICZNEJ
PublicationAplikacja przedstawiona w niniejszym rozdziale służy do automatycznego wykrywania mowy patologicznej na podstawie bazy nagrań. W pierwszej kolejności przedstawiono założenia leżące u podstaw przeprowadzonych badan wraz z wyborem bazy mowy patologicznej. Zaprezentowano również zastosowane algorytmy oraz cechy sygnału mowy, które pozwalają odróżnić mowę niezaburzoną od mowy patologicznej. Wytrenowane sieci neuronowe zostały następnie...
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Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublicationAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
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Economical methods for measuring road surface roughness
PublicationTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Acoustic Processor of the MCM Sonar
PublicationThis paper presents the concept of an acoustic processor of the mine countermeasure sonar. Developed at the Department of Marine Electronics Systems, Gdansk University of Technology, the acoustic processor is an element of the MG-89, a modernised underwater acoustic station. The focus of the article is on the modules of the processor. They are responsible for sampling analogue signals and implementing the algorithms controlling...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning
PublicationThe technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation,...
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Algorytmy przetwarzania widm Ramana w procesie detekcji substancji chemicznych
PublicationRozprawa przedstawia szczegółowo algorytmy, jakie są stosowane podczas przetwarzania widm Ramana, rejestrowanych przenośnym spektrometrem o skończonej rozdzielczości. Pracę podzielono na osiem rozdziałów. W pierwszym określono cel i tezy pracy. Rozdział drugi opisuje podstawowe pojęcia dotyczące zjawiska Ramana oraz zasady budowy urządzeń do pomiarów widm Ramana. W rozdziale trzecim scharakteryzowano błędy występujące podczas pomiarów...
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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The computational complexity of the backbone coloring problem for planar graphs with connected backbones
PublicationIn the paper we study the computational complexity of the backbone coloring problem for planar graphs with connected backbones. For every possible value of integer parameters λ≥2 and k≥1 we show that the following problem: Instance: A simple planar graph GG, its connected spanning subgraph (backbone) HH. Question: Is there a λ-backbone coloring c of G with backbone H such that maxc(V(G))≤k? is either NP-complete or polynomially...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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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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Feasibility Study for Food Intake Tasks Recognition Based on Smart Glasses
PublicationIn this exploratory study 13 adult test subjects have performed different food intake tasks while wearing a three axis accelerometer mounted at a temple of glasses. Two different algorithms for task recognition have been applied and compared. The retrospective data processing leads to better task recognition results when the frequency range of 50 Hz to 100 Hz is analysed within accelerometer signal recordings. A straightforward...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) strategy applied to portable computers. The developed algorithms involve intelligent, rule-based settings of bass synthesis parameters with regard to music genre of an audio excerpt and the type of a portable device in use. The Smart VBS algorithm performs the synthesis based on a nonlinear device (NLD) with artificial controlling synthesis...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublicationPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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IEEE Information Theory Workshop on Detection, Estimation, Classification and Imaging
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Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego
PublicationW artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.
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A ship domain-based model of collision risk for near-miss detection and Collision Alert Systems
PublicationThe paper presents a new model of ship collision risk, which utilises a ship domain concept and the related domain-based collision risk parameters. An encounter is here described by five variables representing: degree of domain violation (DDV), relative speed of the two vessels, combination of the vessels’ courses, arena violations and encounter complexity. As for the first three variables, their values can be directly computed...
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Usage of parametric echosounder with emphasis on buried object searching.
PublicationThe purpose of this article is to present the results of investigation to search for buried objects. The paper will contain echograms and other means of visualization from buried pipe placed between area of W?adys?awowo and gas platform and interesting in terms of the number of small and medium-sized unidentified objects found in the muddy bottom at different depths localized in the Gulf of Puck - results will be presented also...
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The shallow sea experiment with usage of linear hydrophone array
PublicationPurpose of this article is to present designed and made linear hydrophone array and the results obtained during in situ trails on Gulf of Gdańsk. The measuring system allowed to localize hydrophones in the selected points and perform measurements in both the horizontal antenna positioning and vertical. Made in this way recordings allow creating accurate 3D imaging of sound intensity/propagation. During research three floating objects...
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Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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A system for Direction-Of-Arrival estimation in ISM 2.4 GHz frequency band based on ESPAR antenna and SDR technology
PublicationDetermination of the direction of the signal arrival (DOA) finds many applications in various areas of science and industry. Knowledge of DOA is used, among others to determine the position of a satellite with a low Earth orbit (LEO), localization of people and things as well as in research of wireless communication systems, for instance the determination of the number of...