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Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING
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MOTIVATION AND EMOTION
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublicationSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
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Compulsive sexual behavior and dysregulation of emotion
PublicationIntroduction Dysregulation of emotion (DE) is commonly seen in individuals suffering from compulsive sexual behavior (CSB), as well as represents a crucial element of its common comorbidities like mood, anxiety, and substance use disorders. Aim To investigate the links between CSB and DE. Methods A review of pertinent literature on CSB and DE was performed using EBSCO, PubMed, and Google Scholar databases. Main Outcome Measure...
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Risks associated with the transportation of hazardous materials on public roads
PublicationA significant proportion of the transport of hazardous materials is carried out on public roads. Therefore, the safety of such transport is becoming increasingly important. Every catastrophe involving hazardous materials has a negative impact on direct road users and the surrounding environment, becauses its range is mostly not local. It follows that in the event of such catastrophe, its effects should be minimized. This is possible...
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Computational Intelligence - 2023
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Computational Intelligence 2022
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Grand Challenges on the Theory of Modeling and Simulation
PublicationModeling & Simulation (M&S) is used in many different fields and has made many significant contributions. As a field in its own right, there have been many advances in methodologies and technologies. In 2002 a workshop was held in Dagstuhl, Germany, to reflect on the grand challenges facing M&S. Ten years on, a series of M& S Grand Challenge activities are marking a decade of progress and are providing an opportunity to reflect...
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On Computing Curlicues Generated by Circle Homeomorphisms
PublicationThe dataset entitled Computing dynamical curlicues contains values of consecutive points on a curlicue generated, respectively, by rotation on the circle by different angles, the Arnold circle map (with various parameter values) and an exemplary sequence as well as corresponding diameters and Birkhoff averages of these curves. We additionally provide source codes of the Matlab programs which can be used to generate and plot the...
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Introductory modeling for decision-making using AMPL
e-Learning CoursesIntroductory modeling for decision-making using AMPL
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Modeling projects for decision-making using AMPL
e-Learning CoursesModeling projects for decision-making using AMPL
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Measures for Evaluation of Structure and Semantics of Ontologies
PublicationArtykuł przedstawia zagadnienie miar jakości ontologii ze szczególnym uwzględnieniem ich podziału na syntaktyczne (strukturalne) i semantyczne. Na tym tle przedstawione jest nowe podejście do pomiaru właściwości semantycznych ontologii bazujące na kartografii wiedzy.
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Piotr Paradowski dr
PeopleDr Piotr Paradowski's areas of expertise in quantitative social science methods include truncated and censored models, quantile regressions, survival analysis, panel data models, discrete regressions and qualitative choice models, instrumental variable estimation, and hierarchical modeling. He is also an expert in statistical matching and statistical methods to handle missing data. In addition, he conducts research on income and...
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Recognition and sensing of anions
PublicationMolecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...
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General Provisioning Strategy for Local Specialized Cloud Computing Environments
PublicationThe well-known management strategies in cloud computing based on SLA requirements are considered. A deterministic parallel provisioning algorithm has been prepared and used to show its behavior for three different requirements: load balancing, consolidation, and fault tolerance. The impact of these strategies on the total execution time of different sets of services is analyzed for randomly chosen sets of data. This makes it possible...
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Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
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Ahmer Bin Hafeez
PeopleI have experience in Microbiology & Computational Biology, particularly bioinformatics, homology modeling, phylogenetics, structural biology, and drug discovery. Currently, my interest lies in translatable omics studies and drug discovery against novel protein targets involved in cancer and infectious diseases and Host-Pathogen PPIs. My aim involves the use of computational methods for the identification of novel targets and to...
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Numerical Modeling of Hydrosystems 2024/2025
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Numerical Modeling of Hydrosystems 2024/2025
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Numerical Modeling of Hydrosystems 2023/2024
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Language Models in Speech Recognition
PublicationThis chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.
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Application of Web-GIS and Cloud Computing to Automatic Satellite Image Correction
PublicationRadiometric calibration of satellite imagery requires coupling of atmospheric and topographic parameters, which constitutes serious computational problems in particular in complex geographical terrain. Successful application of topographic normalization algorithms for calibration purposes requires integration of several types of high-resolution geographic datasets and their processing in a common context. This paper presents the...
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COMPUTATIONAL STATISTICS & DATA ANALYSIS
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JOURNAL OF COMPUTATIONAL ANALYSIS AND APPLICATIONS
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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
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A fast time-frequency multi-window analysis using a tuning directional kernel
PublicationIn this paper, a novel approach for time-frequency analysis and detection, based on the chirplet transform and dedicated to non-stationary as well as multi-component signals, is presented. Its main purpose is the estimation of spectral energy, instantaneous frequency (IF), spectral delay (SD), and chirp rate (CR) with a high time-frequency resolution (separation ability) achieved by adaptive fitting of the transform kernel. We...
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Berkeley Open Infrastructure for Network Computing
PublicationZaprezentowano system BOINC (ang. Berkeley Open Infrastructure for Network Computing) jako interesujące rozwiązanie integrujące rozproszone moce obliczeniowe osobistych komputerów typu PC w Internecie. Przedstawiono zasadę działania opisywanej platformy. W dalszej części zaprezentowano kilka wybranych projektów naukowych wykorzystujących BOINC, które są reprezentatywne w zakresie zastosowania systemu w ujęciu założonego paradygmatu...
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International Journal of Numerical Analysis and Modeling
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublicationIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Computational analysis of power-law fluids for convective heat transfer in permeable enclosures using Darcy effects
PublicationNatural convection is a complex environmental phenomenon that typically occurs in engineering settings in porous structures. Shear thinning or shear thickening fuids are characteristics of power-law fuids, which are non-Newtonian in nature and fnd wide-ranging uses in various industrial processes. Non-Newtonian fuid fow in porous media is a difcult problem with important consequences for energy systems and heat transfer. In this...
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Multimodal English corpus for automatic speech recognition
PublicationA multimodal corpus developed for research of speech recognition based on audio-visual data is presented. Besides usual video and sound excerpts, the prepared database contains also thermovision images and depth maps. All streams were recorded simultaneously, therefore the corpus enables to examine the importance of the information provided by different modalities. Based on the recordings, it is also possible to develop a speech...
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A space-efficient algorithm for computing the minimum cycle mean in a directed graph
PublicationAn algorithm is introduced for computing the minimum cycle mean in a strongly connected directed graph with n vertices and m arcs that requires O(n) working space. This is a considerable improvement for sparse graphs in comparison to the classical algorithms that require O(n^2) working space. The time complexity of the algorithm is still O(nm). An implementation in C++ is made publicly available at http://www.pawelpilarczyk.com/cymealg/.
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Edge-Computing based Secure E-learning Platforms
PublicationImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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Video Semantic Analysis Framework based on Run-time Production Rules - Towards Cognitive Vision
PublicationThis paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered in the pathway towards Cognitive Vision as a support for classical Computer Vision techniques that have been broadly used by the scientific community. In the article, we particularly focus in solving some of the reported scalability issues found in current...
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Computational aspects of greedy partitioning of graphs
PublicationIn this paper we consider a variant of graph partitioning consisting in partitioning the vertex set of a graph into the minimum number of sets such that each of them induces a graph in hereditary class of graphs P (the problem is also known as P-coloring). We focus on the computational complexity of several problems related to greedy partitioning. In particular, we show that given a graph G and an integer k deciding if the greedy...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Improved Efficacy Behavioral Modeling of Microwave Circuits through Dimensionality Reduction and Fast Global Sensitivity Analysis
PublicationBehavioral models have garnered significant interest in the realm of high-frequency electronics. Their primary function is to substitute costly computational tools, notably electromagnetic (EM) analysis, for repetitive evaluations of the structure under consideration. These evaluations are often necessary for tasks like parameter tuning, statistical analysis, or multi-criterial design. However, constructing reliable surrogate models...
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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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Testing heart rate asymmetry in long, nonstationary 24 hour RR-interval time series
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Dynamical description of quantum computing: generic nonlocality of quantumnoise
PublicationWe develop a dynamical non-Markovian description of quantum computing in the weak-coupling limit, in the lowest-order approximation. We show that the long-range memory of the quantum reservoir (such as the 1/t4 one exhibited by electromagnetic vacuum) produces a strong interrelation between the structure of noise and the quantum algorithm, implying nonlocal attacks of noise. This shows that the implicit assumption of quantum error...
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Complementary oriented allocation algorithm for cloud computing
PublicationNowadays cloud computing is one of the most popular processing models. More and more different kinds of workloads have been migrated to clouds. This trend obliges the community to design algorithms which could optimize the usage of cloud resources and be more effiient and effective. The paper proposes a new model of workload allocation which bases on the complementarity relation and analyzes it. An example of a case of use is shown...
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Roads unsafety - social costs
PublicationThe condition of road safety has a significant impact on the quality of citizens' life. Yearly, one in a hundred families in Poland suffers because of road accidents. It is affected by them not only in material terms but first and foremost in moral terms. Road accidents are one of the main causes of degradation in the quality of life. In Poland we hardly know anything about the fate of the road traffic victims, their life problems...
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Numerical Analysis of Flow in Building Arrangement: Computational Domain Discretization
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Analysis of muscles behaviour : The computational model of muscle. -Part I
PublicationW artykule zaproponowano model obliczeniowy mięśnia szkieletowego, który potraktowano jako strukturę o złożonych i zróżnicowanych właściwościach mechanicznych. Szczegółowo opisano metodę identyfikacji tych właściwości. Ponadto określono sposób przeprowadzenia weryfikacji ilościowej i jakościowej zaproponowanego modelu. Za pomocą takiego obliczeniowego modelu mięśnia można łatwo określać siły w mięśniach, które należą do zespołu...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
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Speed management on local government managed roads – research, recommendations and guidelines
PublicationCommissioned by the National Road Safety Council Secretariat, the project “Guidelines for speed management on local government managed roads” studied car driver be haviour when subjected to selected speed management measures such a local speed restrictions, surveillance, traffic calming and restricted speed areas. In addition, analyses were conducted on the impact of selected me asures...
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Acceleration of decision making in sound event recognition employing supercomputing cluster
PublicationParallel processing of audio data streams is introduced to shorten the decision making time in hazardous sound event recognition. A supercomputing cluster environment with a framework dedicated to processing multimedia data streams in real time is used. The sound event recognition algorithms employed are based on detecting foreground events, calculating their features in short time frames, and classifying the events with Support...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Parallel Programming for Modern High Performance Computing Systems
PublicationIn view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and...