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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublikacjaIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Comparative study of neural networks used in modeling and control of dynamic systems
PublikacjaIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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ReFlexeNN - the Wearable EMG Interface with Neural Network Based Gesture Classification
PublikacjaThe electromyographic activity of muscles was measured using a wireless biofeedback device. The aim of the study was to examine the possibility of creating an automatic muscle tension classifier. Several measurement series were conducted and the participant performed simple physical exercises - forcing the muscle to increase its activity accordingly to the selected scale. A small wireless device was attached to the electrodes placed...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublikacjaThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublikacjaGlobal 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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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublikacjaAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial 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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Applying artificial neural networks for modelling ship speed and fuel consumption
PublikacjaThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublikacjaLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublikacjaPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublikacjaPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublikacjaHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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Accidental wow evaluation based on sinusoidal modeling and neural nets prediction
PublikacjaReferat przedstawia opis algorytmu do określenia charakterystyki zniekształcenia kołysania dźwięku. Prezentowane podejście wykorzystuje sinusoidalną analizę dźwięku bazującą zarówno na amplitudowym jak i fazowym widmie sygnału fonicznego. Trajektorie poszczególnych składowych tonalnych, obrazujące zniekształcenie kołysania, określane są na podstawie analizy ich chwilowych amplitud, częstotliwości i faz. Dodatkowo referat przedstawia...
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Comparison of the Toxicity of Pristine Graphene and Graphene Oxide, Using Four Biological Models
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Simplifying biochemical tumorous bone remodeling models through variable order derivatives
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What Can Be Observed Locally? Round based models for quantum distributed computing
PublikacjaW pracy rozważono zagadnienie lokalności w kontekście informacji kwantowej w obliczeniach rozproszonych. Rozważono dwa kwantowe rozszerzenia modelu LOCAL Liniala, otrzymane poprzez: (1) inicjalizację systemu w kwantowym stanie splątanym, (2) zastosowanie kwantowych kanałów komunikacyjnych. Dla obydwu typów rozszerzeń zaproponowano przykłady problemów, których złożoność rundowa ulega redukcji w porównaniu do oryginalnego modelu...
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Application of the simplified models to inverse flood routing in upper Narew river(Poland)
PublikacjaW pracy przedstawiono rozwiązanie zagadnienia odwrotnej transformacji przepływów z zastosowaniem uproszczonych modeli. Zastosowano model fali kinematycznej oraz równanie retencji. W pierwszym przypadku równanie całkowano w kierunku malejącego czasu zaś w drugim w kierunku przeciwnym do przepływu. Wykazano, że obydwa podejścia są równoważne. Modele zastosowano dla górnego odcinka Narwi.
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Comparison of numerical models of impact force for simulation of earthquake-induced structural pounding
PublikacjaW artykule przedstawiono porównanie trzech modeli numerycznych służących do symulacji siły zderzenia w czasie kontaktu pomiędzy konstrukcjami budowlanymi podczas trzęsień ziemi. Efektywność każdego z modeli zbadano porównując wyniki analiz numerycznych z wynikami badań eksperymentalnych. Wyniki pracy pokazują, iż nieliniowy model lepkosprężysty najdokładniej symuluje przebieg czasowy siły zderzenia w czasie kontaktu.
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Proteins Structure Models in the Evaluation of Novel Variant (C.472_477del) in the MOCS2 Gene
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Estimation of the excitation variances of speech and noise AR-models for enhanced speech coding
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Investigating Human Visual Behavior by Hidden Markov Models in the Design of Marketing Information
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A single and triple-objective mathematical programming models for assignment of services in a healthcare institution
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Cadmium tri-tert-butoxysilanethiolates. Structural and spectroscopic models of metal sites in proteins.
PublikacjaW publikacji opisano syntezy i struktury dla dwóch heteroleptycznych kompleksów kadmu z rdzeniem CdS2NO2 i CdS2N2. Bis(tri-tert-butoksysilanotiolato)(1-metyloimidazol)kadmu(II) oraz bis(tri-tert-butoksysilanotiolato)bis(1-metyloimidazol)kadmu(II) współistnieją w roztworze chloroformu przy różnych stężeniach Bis(tri-tert-butoksysilanotiolanu) kadmu(II) i 1 metyloimidazolu. Rotzwór ten został scharakteryzowany za pomocą analizy spektralnej...
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The operational method of filling information gaps in satellite imagery using numerical models
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Assessment of the effect of vegetation on the transition of the flood wave using hydraulic 2D models
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Risk factors assessment and risk prediction models in lung cancer screening candidates
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Application of Spatial Models in Making Location Decisions of Wind Power Plant in Poland
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublikacjaThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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“Silver Economy” Models in the European Union in the Comparative Approach: An Attempt to Introduce Discussion
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Early stage of critical clusters growth in phenomenological and Molecular Dynamic simulation models
PublikacjaW artykule opisano wzrost klastrów krytycznych w ramach klasycznego podejścia fenomenologicznego oraz dynamiczno-molekularnego (MD). Została wyprowadzona nowa formuła opisujaca liczbę klastrów krytycznych. Sformułowano równania opisujace wczesne etapy wzrostu kropli o rozmiarach krytycznych. Opisano wyniki symulacji dynamiczno-molekularnych powstawania klastrów w jednorodnej parze przesyconej oraz podano czasowe zmiany rozkładu...
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Early stage of critical clusters growth in phenomenological and Molecular Dynamic simulation models.
PublikacjaOpisano proces kondensacji pary wodnej w ujĘciu fenomenologicznymi dynamiczno-molekularnym. Wczesne fazy wzrostu klastra opisano w ramach klasycznej teorii Hertza-Knudsena. Obszernie przedstawiono wyniki symulacji dynamiczno-molekularnych zjawiska kondensacji pary wodnej z jednorodnej fazy gazowej (przebieg powstawania małych klastrów H2O i szybkość wzrostu klastrów ponadkrytycznych).
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Implementation of didactic simulation models in Open Source and SCORM compliant LMS systems.
PublikacjaModele symulacyjne są cenną pomocą w procesie dydaktycznym. Ich zastosowanie w systemach komputerowego wspomagania nauczania znacząco podnosi ich efektywność oraz pozwala na przeprowadzanie wirtualnych ćwiczeń laboratoryjnych (na przykład podczas nauczania na odległość). Niestety stosowane obecnie systemy LMS (Lerning Management System) nie są zadowalająco przystosowane do obsługi symulacyjnej zawartości dydaktycznej. W artykule...
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Real and virtual enviromnents in environmental engineering: approaches, models, technologies, and critical issues.
PublikacjaW pracy scharakteryzowano zagadnienia związane z projektowaniem systemów uwzględniającym ochronę środowiska.
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Optimal input design using sensitivity criterion for parametric identification of pharmacokinetic models
PublikacjaPrzedstawiono identyfikację parametryczną kompartmentowych modeli SISO zmiennych stanu systemów farmakokinetycznych. Struktura modelu formułowana jest na podstawie wiedzy a priori. Początkowe estymaty parametrów obliczane są w oparciu o pomiary zgromadzone w eksperymencie intuicyjnym. Na ich podstawie projektowane jest pobudzenie optymalne, które zapewnia najlepszą dokładność estymat parametrów. Przedstawiono optymalizację czułościową...
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Structural properties of water: Comparison of the SPC, SPCE, TIP4P and TIP5P models of water
PublikacjaDla czterech najpopularniejszych modeli wody obliczono wartości entropii absolutnej ciekłej wody w temperaturze 298 K, średnią liczbę wiązań wodorowych tworzonych przez cząsteczkę wody, średni czas życia wiązania wodorowego, średni czas życia cząsteczki wody w stanie związanym (gdy tworzy ona co najmniej jedno wiązanie wodorowe) oraz średnią energię wiązania wodorowego. Otrzymane rezultaty porównano z eksperymentem. Uzyskane wyniki...
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Numerical Simulations of Seepage in Dikes Using unsaturated and Two-Phase Flow Models
PublikacjaModeling of water flow in variably saturated porous media, including flood dikes, is often based on the Richards equation, which neglects the flow of pore air, assuming that it remains at constant atmospheric pressure. However, there is also evidence that the air flow can be important, especially when the connectivity between the pore air and atmospheric air is lost. In such cases a full two-phase air-water flow model should be...
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Environmentally Oriented Models and Methods for the Evaluation of Drug x Drug Interaction Effects
PublikacjaThis detailed review compares known and widely used methods for drug interaction estimation, some of which now have historical significance. Pharmaceutical application has been noted as far back as several thousand years ago. Relatively late in the 20th century, however, researchers became aware that their fate and metabolism, which still remain a great challenge for environmental analysts and risk assessors. For the patient’s...
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Empirical verification in industrial conditions of fracture mechanics models of cutting power prediction
PublikacjaA comparison of experimental results obtained in the industrial conditions at a sawmill located in the Baltic Natural Forest Region (PL) and theoretical cutting power consumption forecasted with the models which include work of separation (fracture toughness) in addition to plasticity and friction has been described. In computations of cutting power consumption during rip sawing of Scots pine wood (Pinus sylvestris L.) values of...
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A concept of application of the technical state change models of devices inship operation process
PublikacjaPrzedstawiono warunki zastosowania modeli zmian stanu technicznego urządzeń siłowni okrętowej w trakcie eksploatacji statku, koncepcję prognozowania zasobu godzin pracy urządzeń w zmiennych warunkach pływania oraz planowania obsług profilaktycznych.
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Testing interaction models by using x-ray absorption spectroscopy: solid Pb
PublikacjaPraca prezentuje zastosowanie metody EXAFS jako narzędzia do testowania potencjałów oddziaływań międzyatomowych używanych w symulacjach dynamiczno-molekularnych na przykładzie czystego ołowiu w fazie stałej (od temperatury pokojowej do temperatury topnienia). Testowaniu poddano następujące potencjały: dwuciałowy empiryczny potencjał Dzugutova, Larssona i Ebbsjo (DLE), potencjał ciasnego wiązania (TB) i potencjał w modelu osadzonego...
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Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples
PublikacjaHere, identification of processes and systems in the sense of the least sum of absolute values is taken into consideration. The respective absolute value estimators are recognised as exceptionally insensitive to large measurement faults or other defects in the processed data, whereas the classical least squares procedure appears to be completely impractical for processing the data contaminated with such parasitic distortions. Since...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...