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Wyniki wyszukiwania dla: DEEP NEURAL NETWORKS
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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Charakterystyka wybranych tłuszczów użytych w gastronomii do głębokiego smażenia. Characteristics of selected fats used in catering industry for deep frying of food stuffs.
PublikacjaW wybranych losowo próbach tłuszczów smażalniczych z gastronomii oznaczono skład kwasów tłuszczowych, Liczbę Kwasową, Liczbę Anizydynową, Liczbę Nadtlenkową oraz zawartość i skład frakcji polarnej. Nie znaleziono korelacji pomiędzy stopniem nienasycenia badanych tłuszczów smażalniczych (LJ) i badanymi wyróżnikami jakości.
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Optymalizacja zasad koegzystencji sieci standardów Bluetooth i IEEE 802.11 = Optimization of Bluetooth and IEEE 802.11 networks co-existence
PublikacjaZ uwagi na rosnącą popularność standardów Bluetooth (BT) i IEEE 802.11b (Wi-Fi ) można się z nimi spotkać praktycznie wszędzie. Gwałtowny wzrost liczby urządzeń różnych technologii ma także swoje negatywne strony. Stosowanie coraz większej liczby urządzeń różnych systemów radiokomunikacyjnych powoduje wzrost poziomu zaburzeń elektromagnetycznych. W konsekwencji działanie różnych sieci bezprzewodowych pracujących w bliskim zasięgu...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublikacjaNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Computational intelligence methods in production management
PublikacjaThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublikacjaIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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Multicast Traffic Throughput Maximization through Joint Dynamic Modulation and Coding Schemes Assignment, and Transmission Power Control in Wireless Sensor Networks
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince 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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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublikacjaTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition
PublikacjaThe idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral...
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
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On a Method of Efficiency Increasing in Kaplan Turbine
PublikacjaThis paper presents a method of increasing efficiency in Kaplan-type turbine. The method is based on blade profile optimisation together with modelling the interaction between rotor and stator blades. Loss coefficient was chosen as the optimisation criterion, which is related directly to efficiency. Global optimum was found by means of Genetic Algorithms, and Artificial Neural Networks were utilised for approximations to reduce...
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublikacjaThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
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Document Agents with the Intelligent Negotiations Capability
PublikacjaThe paper focus is on augmenting proactive document-agents with built -in intelligence to enable them to recognize execution context provided by devices visited durning the business process, and to reach collaboration agreement despite of their conflicting requirements. We propose a solution based on neural networks to improve simple multi-issue negotiation between the document and the device, practically with no excessive cost...
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Neuronowa symulacja temperatury i ciśnienia pary w upuście parowego bloku energetycznego = Neural simulation of pressure and temperature fluctuations at steam extraction of power units with steam turbine
PublikacjaW artykule przedstawiono metodę symulacji neuronowej dla zastosowań w diagnostyce on-line bloków energetycznych. Model neuronowy opiera się na statycznych jednokierunkowych sieciach neuronowych (SSN) oraz na danych z parowego bloku energetycznego o mocy 200 MW. SSN obliczają wartości referencyjne parametrów cieplno-przepływowych dla aktualnego obciążenia obiektu. Określono wpływ architektury sieci i danych uczących na jakość symulacji...
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Zarządzanie (współzarządzanie) sieciowe i zarządzanie sieciami w wymiarze sprawiedliwości – wyzwania (15 stron) Governance network and networks governance in the justice system – challenges
PublikacjaCelem artykułu jest próba odpowiedzi na pytania czy w wymiarze sprawiedliwości jest miejsce i podstawa do wdrożenia zarządzania sieciowego (współzarządzania) oraz czy w działalności pomocniczej wymiaru sprawiedliwości istnieje potencjał do jego wdrożenia. W wymiarze sprawiedliwości istnieje duży potencjał do wykorzystania mechanizmów sieciowej współpracy. W ramach przestrzeni wymiaru sprawiedliwości współpraca międzyorganizacyjna...
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Control of the cultivation of cartilages for using in the biobearings.
PublikacjaBiotribologiczne charakterystyki biołożysk są zależne od procesu hodowli żywej tkanki chrząstki w bioreaktorze. Z kolei proces ten, jest wielowymiarowym procesem dynamicznym sterowanym za pomocą odpowiedniego układu automatycznej regulacji. Praca przedstawia prawo i algorytm sterowania takiego procesu. W tym celu zastosowano sztuczne sieci neuronowe (Artificial Neural Networks - ANN) i zaprezentowano wyniki obliczeń.
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Adaptive CAD-Model Construction Schemes
PublikacjaTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn 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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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublikacjaThe 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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Knowledge representation of motor activity of patients with Parkinson’s disease
PublikacjaAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublikacjaThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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AUTOMATED NEGOTIATIONS OVER COLLABORATION PROTOCOL AGREEMENTS
PublikacjaThe dissertation focuses on the augmentation of proactive document - agents with built-in intelligence to recognize execution context provided by devices visited during a business process, and to reach collaboration agreement despite conflicting requirements. The proposed solution, based on intelligent bargaining using neural networks to improve simple multi-issue negotiation between the document and thedevice, requires practically...
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Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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General concept of reduction process for big data obtained by interferometric methods
PublikacjaInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states
PublikacjaContemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...
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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data
PublikacjaThe Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...
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Collaborative Data Acquisition and Learning Support
PublikacjaWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublikacjaIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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Signal Processing in the Investigation of Two-phase Liquid-gas Flow by Gamma-ray Absorption
Publikacjan this paper, the use of the gamma-absorption method applied in the investigation of the two-phase liquid-gas flow in the pipeline is described. An example of its application to the air transported by water in a horizontal pipeline is evaluated. In the measurements, Am-241 radioactive sources and probes with Nal (Tl) scintillation crystals have been used. The signals from the radiometric set were used to determine the velocity...
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Assessment of Emotional Expressions after Full-Face Transplantation
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Supramolecular structures formed by 2-aminopyridine derivatives. Part I. Hydrogenbonding networks via N-H...N interactions and the conformational polymorphism of N,N´-bis(2-piridyl)aryldiamines
PublikacjaOtrzymano serię N,N´-bis(2-pirydylo)arylodiamin w postaci monokryształów. Zgodnie z oczekiwaniami, powstawały dwie odmiany polimorficzne. Forma EE z układem wiązań R22(8) figuruje jako jednowymiarowe taśmy. Stwierdzono, że ugrupowanie 2-aminopirydylowe stanowi synton supramolekularny za pomocą którego można projektować struktury w ciele stałym. Właściwości tego syntonu były badane z wykorzystaniem metod dyfrakcyjnych oraz spektroskopii...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublikacjaIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublikacjaIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Special techniques and future perspectives: Simultaneous macro- and micro-electrode recordings
PublikacjaThere are many approaches to studying the inner workings of the brain and its highly interconnected circuits. One can look at the global activity in different brain structures using non-invasive technologies like positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), which measure physiological changes, e.g. in the glucose uptake or blood flow. These can be very effectively used to localize active patches...
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SNDlib 1.0—Survivable Network Design Library
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On the complexity of distributed graph coloring with local minimality constraints
PublikacjaArtykuł traktuje o zachłannym kolorowaniu grafów w modelu rozproszonym. Omówiono algorytmy rozproszone, dające w wyniku pokolorowanie spełniające warunki dla pokolorowań sekwencyjnych typu S oraz Largest-First (LF). Udowodniono również, że każda rozproszona implementacja algorytmu S wymaga co najmniej Omega(log n / log log n) rund, a algorytmu LF co najmniej Omega (n^{1/2}) rund, gdzie n oznacza liczbę wierzchołków grafu.
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Optimal edge-coloring with edge rate constraints
PublikacjaWe consider the problem of covering the edges of a graph by a sequence of matchings subject to the constraint that each edge e appears in at least a given fraction r(e) of the matchings. Although it can be determined in polynomial time whether such a sequence of matchings exists or not [Grötschel et al., Combinatorica (1981), 169–197], we show that several questions about the length of the sequence are computationally intractable....
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Complexity of a classical flow restoration problem
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On the complexity of resilient network design
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Toward Fast Calculation of Communication Paths for Resilient Routing
PublikacjaUtilization of alternate communication paths is a common technique to provide protection of transmission against failures of network nodes/links. However, a noticeable delay is encountered when calculating the relevant sets of disjoint paths using the available algorithms (e.g., using Bhandari’s approach). This, in turn, may have a serious impact on the ability of a network to serve dynamic demands...
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Kontrola procesowa za pomocą technik czujnikowych nowych metod selektywnego oczyszczania biogazu ze związków uciążliwych zapachowo
PublikacjaW obecnym czasie dużą uwagę zwraca się na opracowanie efektywnej technologii oczyszczania biogazu do gazu wysokometanowego. Głównym celem rozprawy doktorskiej było opracowanie ekonomicznie opłacalnych absorbentów do efektywnego oczyszczania strumieni biogazu z substancji uciążliwych zapachowo. Procesy absorpcji fizycznej prowadzono z wykorzystaniem zaprojektowanych i otrzymanych dotąd jeszcze nie publikowanych sorbentów na bazie...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublikacjaThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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ANN for human pose estimation in low resolution depth images
PublikacjaThe 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
PublikacjaA 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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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Music Mood Visualization Using Self-Organizing Maps
PublikacjaDue 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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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Wpływ ukształtowania zbrojenia na zarysowanie i nośność żelbetowego węzła tarczowego ze wspornikiem
PublikacjaPraca ma charakter eksperymentalno-teoretyczny i dotyczy zagadnień związanych z żelbetowymi tarczami pracującymi w przestrzennym układzie konstrukcji budynków. Celem niniejszej dysertacji było określenie wpływu głównych parametrów jakimi są sposób ukształtowania zbrojenia i smukłość ścinania na zarysowanie i nośność żelbetowego przestrzennego węzła tarczowego ze wspornikiem. Na podstawie aktualnego stanu wiedzy, opracowano program...
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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublikacjaThe 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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Residual MobileNets
PublikacjaAs 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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Fault detection in measuring systems of power plants
PublikacjaThis paper describes possibility of forming diagnostic relations based on application of the artifical neural networks (ANNs), intended for the identifying of degradation of measuring instruments used in developed power systems. As an example a steam turbine high-power plant was used. And, simulative calculations were applied to forming diagnostic neural relations. Both degradation of the measuring instruments and simultaneously...
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Urban scene semantic segmentation using the U-Net model
PublikacjaVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Determination of the impact indicators of electromagnetic interferences on computer information systems
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Effects of chronic neuroleptic treatment on dopamine release: Insights from studies using 3-methoxytyramine
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Poor evidence for depolarization block but uncoupling of nigral from striatal dopamine metabolism after chronic haloperidol treatment in the rat
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Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublikacjaOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publikacjais evaluated on 9 patients, data analysis methods are described, and experiments of correlating Glasgow Coma Scale with extracted features describing subjects performance in therapeutic exercises exploiting EEG and eyetracker are presented. Performance metrics are proposed, and k-means clusters used to define concepts for mental states related to EEG and eyetracking activity. Finally, it is shown that the strongest correlations...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublikacjaTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublikacjaThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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Rotor Blade Geometry Optimisation in Kaplan Turbine
PublikacjaThe paper presents the description of method and results of rotor blade shape optimisation. The rotor blading constitutes a part ofturbine flow path. Optimisation consists in selection of the shape that minimises ratio of polytrophic loss. Shape of the blade isdefined by the mean camber line and thickness of the airfoil. Thickness is distributed around the camber line based on the ratio ofdistribution. Global optimisation was done...
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Creation of Hydrogen Bonded 1D Networks by Cocrystallization of N,N`-bis(2-pyridyl) aryldiamines with Dicarboxylic Acids.Tworzenie 1D sieci krystalicznych poprzez kokrystalizację N,N` -bis(2-piry- dylo) arylodiamin z kwasami dikarboksylowymi.
PublikacjaZsyntetyzowano szereg N,N`-bis(2-pirydylo) arylodiamin, a następnie otrzymano serię kompleksów w/w amin z kwasami dikarboksylowymi oraz kwasem kwadratowym w postaci monokryształów. Jednostki N,N`-bis(2-pirydylo) arylodiamin i kwasy dikarboksylowe oddziaływują ze sobą poprzez wiązania wodorowe tworząc ośmioczłonowy cykliczny układ. W kompleksach 1:1 cząsteczki układają się w jedno-wymiarową sieć krystaliczną tworzoną przy udziale...
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Embedded Representations of Wikipedia Categories
PublikacjaIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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Automatic Rhythm Retrieval from Musical Files
PublikacjaThis paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....
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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublikacjaThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?
PublikacjaDespite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected...
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MAC contention in a wireless LAN with noncooperative anonymous stations
PublikacjaRozpatruje się model sieci bezprzewodowej wykorzystywanej przez wzajemnie nieprzenikalne grupy stacji anonimowych. Przy ustalonej regule wyłaniania zwycięzcy rywalizacji o dostęp do medium, stacje posiadają swobodę wyboru strategii selekcji szczeliny rywalizacyjnej. Dla szerokiego zbioru możliwych strategii proponuje się metodologię ich oceny i testowania wydajności opartą na pojęciu zbliżonym do ewolucyjnej stabilności.
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Circularly Polarized Antenna Array design with the Potential of Gain-Size Trade-off and Omnidirectional Radiation for Millimeter-Wave Small Base Station Applications
PublikacjaThis paper presents the design and validation of a slot-patch-hybrid circularly polarized antenna array for 28 GHz millimeter (mm) wave (mm-wave) applications. The proposed design has a simple geometry that facilitates the fabrication process, which is otherwise a challenging task due to the sub-mm dimensions of the circuit in the mm-wave band. In the proposed structure, aperture-coupled series slot-fed array is utilized to excite...
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Design of a Coplanar Waveguide-Fed Wideband Compact-Size Circularly Polarized Antenna and polarization-sense alteration
PublikacjaThis paper presents the design and validation of a geometrically simple circularly polarized(CP) structure featuring flat gain in the sub-6 GHz 5th generation spectrum. The proposed structure is based on coplanar-waveguide-fed, modified wide slot etched in the ground plane. For generating CP waves, the coplanar ground planes are designed with slight asymmetry in both the horizontal and vertical directions. Furthermore, the ground...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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MobileNet family tailored for Raspberry Pi
PublikacjaWith the advances in systems-on-a-chip technologies, there is a growing demand to deploy intelligent vision systems on low-cost microcomputers. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity of contemporary convolutional neural networks (CNNs). The state-of-the-art lightweight CNN is MobileNetV3. However, it was designed to achieve a good trade-off between...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublikacjaThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...
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The Effect of Cryogenic Treatment on Microstructure and Mechanical Response of AISI D3 Tool Steel Punches
PublikacjaRecently, deep cryogenic treatment is performed to improve the mechanical responses (wear, hardness, fatigue, and thermal conductivity) of various steel components. Researchers have tried to evaluate the eco-friendly and nontoxic process to optimize the parameters. Cold-shearing punches used to manufacture various holes that undergo severe impact loading and wear in the metal forming process. This study concerns the effect of soaking...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Book Review
PublikacjaActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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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
PublikacjaPlain 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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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe 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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Experience-Oriented Intelligence for Internet of Things
PublikacjaThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublikacjaThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublikacjaThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublikacjaLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical 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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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublikacjaThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublikacjaW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Runge-Kutta bicharacteristic methods for first order partial functional di- fferential equations
PublikacjaW pracy prezentujemy nową klasę metod numerycznych dla równań różniczkowo-funkcyjnych. Są to metody bicharakterystyk Rungego-Kutty. Ponadto porównuje-my wprowadzone metody z metodami klasycznymi.
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublikacjaThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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Opracowanie technologii spawania naprawczego szyn poddźwigowych A120 oraz badania nieniszczące jakości szyn w DCT w Porcie Północnym
PublikacjaEkspertyza dotyczy realizacji zlecenia związanego z naprawą spoin szyn poddźwigowych na terenie terminalu kontenerowego - Deep Water Terminal (DCT) w Porcie Północnym w Gdańsku. W ramach opracowania: 1. Wykonano badania ultradźwiękowe (UT) i magnetyczno-proszkowe (MT) spoin czołowych szyn poddźwigowych typu A120, według schematu dostarczonego przez firmę SKANSKA S.A. 2. Wykonano analizę wyników badań...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublikacjaThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...