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Search results for: neural embeddings
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ANN for human pose estimation in low resolution depth images
PublicationThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....
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Comparison of selected electroencephalographic signal classification methods
PublicationA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Environmemtal Degradation of Ramie Fibre Reinforced Biocomposites
PublicationThe estimation of environmental degradibility of different fibre reinforced biocomposites in Baltic sea and in compost with activated sludge under natural conditions is the subject of this paper. Two types of biocomposites, ramie fibre/ecoflex and ramie fibre/cellulose nanofibre reinforced corn starch resin, were studied.It was demonstrated that the biocomposites with natural fibre of ramie were degraded in compost faster than...
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An optimal form of the finite element mass matrix in the analysis of longitudinal vibrations of rods
PublicationIn this paper, an attempt is made to find the optimal form of the mass matrix of a rod finite element, which allows one to obtain the smallest errors in the longitudinal frequency determination of natural vibrations of any boundary conditions within the whole range of determined frequencies. It is assumed that the mass matrix can be treated as a linear combination of the consistent and diagonal matrices. Based on analytical considerations,...
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Improved-Efficacy EM-Driven Optimization of Antenna Structures Using Adaptive Design Specifications and Variable-Resolution Models
PublicationOptimization-driven parameter tuning is an essential step in the design of antenna systems. Although in many cases it is still conducted through parametric studies, rigorous numerical methods become a necessity if truly optimum designs are sought for, and the problem intricacies (number of variables, multiple goals, constraints) make the interactive approaches insufficient. The two practical considerations of electromagnetic (EM)-driven...
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Smart growth - is it a fairytale or the best initiative for polish cities and their functional regions?
PublicationThe paper presents smart growth perceived as natural step in sustainable development understanding.
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A spline-based FE approach to modelling of high frequency dynamics of 1-D structures
PublicationIn this paper a computational methodology leading to the development of a new class of FEs, based on the application of continuous and smooth approximation polynomials, being splines, has been presented. Application of the splines as appropriately defined piecewise elemental shape functions led the authors to the formulation of a new approach for FEM, named as spFEM, where contrary to the well-known NURBS approach, the boundaries...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublicationThe 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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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Application of ANN and PCA to two-phase flow evaluation using radioisotopes
PublicationIn the two-phase flow measurements a method involving the absorption of gamma radiation can be applied among others. Analysis of the signals from the scintillation probes can be used to determine the number of flow parameters and to recognize flow structure. Three types of flow regimes as plug, bubble, and transitional plug – bubble flows were considered in this work. The article shows how features of the signals in the time and...
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublicationThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment
PublicationIn this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....
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Music Mood Visualization Using Self-Organizing Maps
PublicationDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Biophilic Design: A Trend Watch
PublicationDuring the 20th century, many people migrated to cities for employment and economic opportunities, abandoning farming and natural landscapes so their direct connection to the countryside and nature was lost. This process continues to this day with unprecedented urban growth, in fact, it’s estimated 68% of the world population will live in urban areas by 2050. Due to the evolutionary disposition of humans, when people live in an...
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The organophosphorus sulfenyl bromides as versatile reagents for cysteine derivatives functionalization by unsymmetrical disulfide bond formation
PublicationWe have developed a convenient method for the synthesis of L-cysteine unsymmetrical disulfides under mild conditions with good to excellent yields. Described method is based on the straightforward preparation of the organophosphorus sulfenyl bromide readily available from bis-(5,5-dimethyl-2-thiono-1,3,2-dioxaphosphorinanyl) disulfide. The unsymmetrical disulfides can be obtained for L-cysteine derivatives and thiols bearing neutral...
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Proton affinities of simple organic compounds
PublicationThe Restricted Hatree-Fock method with 6-311G** split-valence molecular orbitals basis sets has been applied to geometrical optimizations and calculations of total electronic, zero point vibrational energies and proton affinities at 298 K for small neutral and protonated alkanes, alcohols, acetic acid, methyl and ethyl acetate, acetone, and acetaldehyde. Calculated values of proton affinities are compared with experimental data.
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On the deformation and frequency analyses of SARS-CoV-2 at nanoscale
PublicationThe SARS-CoV-2 virus, which has emerged as a Covid-19 pandemic, has had the most significant impact on people's health, economy, and lifestyle around the world today. In the present study, the SARS-CoV-2 virus is mechanically simulated to obtain its deformation and natural frequencies. The virus under analysis is modeled on a viscoelastic spherical structure. The theory of shell structures in mechanics is used to derive the governing...
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Rozdział 3.1.1. Przestrzenne formy ochrony przyrody. W: [Praca zbiorowa]Materiały do monografii przyrodniczej regionu gdańskiego. Gdańsk: Marpress **2002 s. 57-66, 4 tab. Tom 8 Diagnoza stanu i koncepcja ochrony środowiska przyrodniczo-kulturowe- go w województwie pomorskim. Diagnosis of natural-cultural environment´scondition and the idea of its protection in Pomeranian Voivodship. Red. A.Kostarczyk, M. Przewoźniak.
Publication...
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Wybrane zagadnienia przepływowe turbiny gazowej pracującej w tłoczni gazu ziemnego.
PublicationW niniejszym artykule przedstawiono cieplno-przepływowe obliczenia turbiny gazowej, stanowiącej napęd sprężarki w tłoczni gazu ziemnego. Wartości parametrów wejściowych niezbędnych do przeprowadzenia obliczeń przyjęto na podstawie danych technicznych tłoczni zasilających polski odcinek gazociągu tranzytowego Jamał-Europa, w których pracują turbiny gazowe SGT-600 firmy Siemens, o mocy 25,3 MW.
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EXPERIMENTAL STUDY OF A TEMPORARY STEEL GRANDSTAND UNDER CROWD LOAD
PublicationTemporary structures, such as grandstands, are commonly used during different types of mass events, especially sport and music concerts. In this paper, the results of the experimental study on temporary steel grandstand are presented. The aim of the investigation was to determine modal characteristics of such structures. Modes of free vibrations and corresponding natural frequencies have been obtained for empty and occupied grandstand....
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublicationThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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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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Laser-assisted approach for improved performance of Au-Ti based glucose sensing electrodes
PublicationThis paper focuses on the synthesis route and electrochemical properties of electrocatalytic material based on gold nanoparticles (NPs) embedded in a structured titanium template obtained via optimized anodization, chemical etching and laser processing. SEM inspection reveals the presence of Au NPs (60–90 nm in diameter) sited in the titanium foil cavities. Performed electrochemical measurements enable nomination of the set of working...
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Thermal buckling of functionally graded piezomagnetic micro- and nanobeams presenting the flexomagnetic effect
PublicationGalerkin weighted residual method (GWRM) is applied and implemented to address the axial stability and bifurcation point of a functionally graded piezomagnetic structure containing flexomagneticity in a thermal environment. The continuum specimen involves an exponential mass distributed in a heterogeneous media with a constant square cross section. The physical neutral plane is investigated to postulate functionally graded material...
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Sentiment Analysis of Facebook Posts:the Uber case
PublicationThis article analyses the sentiment of opinions, i. e. its classification as phrases with a neutral, positive and negative emotional tone. Data used as a basis for the analysis were opinions expressed by Facebook users about Uber and collected in the period between July 2016 and July 2017. The primary objective of the study was to obtain information about the perceptions of Uber over thirteen consecutive months. The study confirms...
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Dissecting gamma frequency activities during human memory processing
PublicationGamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not...
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End of the hydrocarbon fuels' age?
PublicationHydrocarbon is still one of the most important natural treasures which has an enormous range of implementations in different sectors of the industry.
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Metoda prognozowania mocy skrawania przy przecinaniu piłami polskiego drewna sosnowego z uwzględnieniem wiązkości materiału obrabianego
PublicationW pracy zostały przedstawione wartości właściwości materiałowych tj.: wiązkość R oraz naprężenia tnące w strefie skrawania τy, dla drewna sosnowego (Pinus sylvestris L.). Badane próbki drewna pochodziły z czterech Krain Przyrodniczo - Leśnych Polski: Bałtyckiej Krainy Przyrodniczo - Leśnej (kraina A), Karpackiej Krainy Przyrodniczo - Leśnej (kraina B), Małopolskiej Krainy Przyrodniczo - Leśnej (kraina C) oraz Wielkopolsko - Pomorskiej...
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Dynamika bezzałogowego aparatu latającego w układzie czterowirnikowego pionowzlotu
PublicationDziałanie maszyn, w tym również pojazdów latających, jest nieodłącznie związane z przekazywaniem oddziaływań siłowych: statycznych i dynamicznych. Dynamika jest działem mechaniki zajmującym się makroskopowym ruchem ciał przy uwzględnieniu przyczyn wywołujących ten ruch. Pierwszym etapem analizy dynamiki konstrukcji są zwykle obliczenia wartości i postaci drgań własnych modelu konstrukcji. Drgania własne zwykle ulegają szybkiemu...
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Cohousing: the place of community
PublicationThe crisis of social bonds, which affects living environment, has lead to the revival of traditional neighbourly relations. The idea of cohousing is included in this trend. Its inspiration may be found in the tradition of rural community, which used to adjust the system of rural settlements to the needs of community life.
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Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublicationFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...
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Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublicationThe article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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Text Categorization Improvement via User Interaction
PublicationIn this paper, we propose an approach to improvement of text categorization using interaction with the user. The quality of categorization has been defined in terms of a distribution of objects related to the classes and projected on the self-organizing maps. For the experiments, we use the articles and categories from the subset of Simple Wikipedia. We test three different approaches for text representation. As a baseline we use...
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Residual MobileNets
PublicationAs modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory
PublicationMemory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Rozdział 2.2.1. Strukturalizacja przyrodnicza obszaru województwa pomors-kiego. W: [Praca zbiorowa] Materiały do monografii przyrodniczej regionu gdańskiego. Gdańsk: Marpress**2002 s. 18-31, 1 rys. Tom 8 Diagnoza stanu i koncepcja ochrony środowiska przyrodniczo-kulturowe- go w województwie pomorskim. Diagnosis of natural-cultural environment´scondition and the idea of its protection in Pomeranian Voivodship. Red. A.Kostarczyk, M. Przewoźniak.
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Rozdział 2.1. Metoda zintegrowanej waloryzacji środowiska przyrodniczo-kul-turowego. W: [Praca zbiorowa] Materiały do monografii przyrodniczej regionu gdańskiego. Gdańsk: Marpress**2002 s. 16-18.Tom 8 Diagnoza stanu i koncepcja ochrony środowiska przyrodniczo-kulturowe- go w województwie pomorskim. Diagnosis of natural-cultural environment´scondition and the idea of its protection in Pomeranian Voivodship. Red. A.Kostarczyk, M. Przewoźniak.
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