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Behaviour of asphalt concrete in cyclic and static compression creep test with and without lateral confinement
PublikacjaArtykuł przedstawia wpływ metodyki badań na określanie parametrów betonu asfaltowego. Wykazano, że badania pełzania bez skrępowania bocznego w większym stopniu uwypuklają wpływ asfaltu na parametry badanego betonu asfaltowego natomiast w badaniach ze skrępowaniem bocznym, zarówno rola asfaltu jak i szkieletu mineralnego jest uwzględniana przy ocenie parametrów betonu asfaltowego. Ponadto wykazano, że lepszymi miarami do oceny betonu...
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Działania firm w organizacji EURO 2012 w rejonie Gdańska a środowisko naturalne
PublikacjaW pracy przedstawiono analizę wpływu działalności przedsiębiorców w przygotowaniach do turnieju finałowego mistrzostw Europy w roku 2012 w Gdańsku. Omówiono aktualny stan gospodarki wodno-ściekowej oraz gospodarki odpadami w rejonie Trójmiasta i stwierdzono brak zagrożeń dla środowiska naturalnego związanych z działalnością firm przed i w trakcie Euro 2012. Przedstawiono również zagadnienia związane z klimatem Gdańska i określono...
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Initial value problems for neutral fractional differential equations involving a Riemann-Liouville derivative
PublikacjaBadano równania neutralne typu ułamkowego z odchylonym argumentem. Podano warunki dostateczne na istnienie jednego rozwiązania.
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Multilevel inverter neutral-point voltage sensor diagnostic based on the Extended Kalman Filter
PublikacjaA new algorithm for neutral point voltage imbalance estimation in DC link of the three-level (3L) neutral point clamped (NPC) voltage source inverter (VSI) is proposed. Application of the proposed algorithm does not require any additional sensors. The unbalanced voltage calculation is based on the information derived from the inverter output measured currents and from the knowledge of the load model parameters. In order to estimate...
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Synthesis, structure and magnetic properties of neutral Ni(II) tri-tert-butoxysilanethiolate cluster
PublikacjaNowy klaster niklu(II) [Ni6(μ-O)6{SSi(tBuO)3}6(H2O)6(NH3)4] został otrzymany w reakcji NiCl2·6H2O z tri-tert-butoksysilanotiolu i amoniakiem w roztworze wodnym. Pomiary właściwości magnetycznych badanego związku pokazują obecność silnych antyferromagnetycznych oddziaływań pomiędzy centrami metalicznymi.
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Cyclic analysis of thermal impedance of a passive layer of aluminium in a neutral borate buffer solution
PublikacjaW pracy przedstawiono wyniki badań warstwy pasywnej tworzącej się na stopie 1050 A w warunkach zmieniającej się temperatury. Zmiany realizowano w sposób cykliczny zwiększając a następnie zmniejszając temperaturę. W czasie zmian temperatury prowadzono badania metodę dynamicznej elektrochemicznej spektroskopii impedancyjnej. Stwierdzono największe zmiany parametrów elektrycznego schematu zastępczego w czasie pierwszego cyklu zmian....
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Study of free convective boundary layer of isothermal lateral surface of axisymmetrical horizontal body
PublikacjaPrzedstawiono rozwiązanie równań Naviera-Stokesa i Fouriera-Kirchhoffa we współrzędnych tau i sigma. Pierwsza jest styczną a druga normalną do konwekcyjnych linii prądu, wzdłuż jakich porusza się ogrzany od powierzchni płyn. Wynik w postaci równania na grubość warstwy przyściennej zweryfikowano dla granicznych przypadków ciała obrotowego o poziomej osi symetrii (stożka poziomego i kołowej pionowej płyty).
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Spatial expansion of the symmetrical objects point clouds to the lateral surface of the cylinder – Mathematical model
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Musical instrument sound separation methods supported by artificial nueural network decision system
PublikacjaRozprawa doktorska (27 czerwica 2006).Celem prowadzonych prac badawczych było opracowanie algorytmów separacji dźwięków instrumentów muzycznych. Dodatkowo dobrano zestaw parametrów tak aby możliwe było wytrenowanie sztucznej sieci neuronowej w celu automatycznego rozpoznawania odseparowanych sygnałów. Zaproponowano również aby algorytm decyzyjny odpowiedzialny za klasyfikacje dźwięków pełnił funkcję automatycznej metody oceny algorytmów...
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Indoor Air Quality and Thermal Comfort in Naturally Ventilated Low-Energy Residential Houses
PublikacjaRozdział omawia jakość powietrza i termiczny komfort w naturalnie wentylowanych energooszczędnych budynkach mieszkalnych. Obliczenia wykonano metoda elementów skończonych dla wentylacji naturalnej. Uwzględniono 2 różne położenia wlotów powietrza oraz system grzewczy kaloryferowy i podłogowy. Wyniki MES porównano z doświadczeniami.
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Wybrane wiadomości z etnobotaniki i etnofarmacji. Karty z dziejów lecznictwa naturalnego [Selected issues from ethnobotany and ethno-pharmacy. Pages from the history of natural medicine]
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A multi-analytical approach to the characterization of natural organic dyestuffs and inorganic substrates present in the 19th-century artistic oil paints manufactured by a French art materials supplier Richard Aines
PublikacjaThis paper presents a comprehensive analysis of artistic paints produced in the 19th century by a French art materials supplier Richard Ain`es. Improved mild extraction with hydrofluoric acid enabled the observation of intact organic dyes. Reversed-phase liquid chromatography with diode-array and mass spectrometry detection was utilised for the identification of 35 dyes present in yellow and red paint samples, and in selected plant...
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Legislative and criminal law aspects of water protection and prevention of pharmaceuticals accumulation in nature
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Towards bees detection on images: study of different color models for neural networks
PublikacjaThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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In Search of Panacea—Review of Recent Studies Concerning Nature-Derived Anticancer Agents
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublikacjaSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublikacjaAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Application of spatial neural simulators of turbine blade rows to fluid flow diagnostics
PublikacjaThis chapter presents the results of neural modelling of fluid flow in steam turbine row. In modelling working conditions of the flow channel varied, thus the aim of the work was to reconstruct the reference state - distributions of velocity, pressure, and losses in flow channel - with high accuracy for fluid flow diagnostics.
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Accuracy Investigations of Turbine Blading Neural Models Applied to Thermal and Flow Diagnostics
PublikacjaPossibility of replacing computional fluid dynamics simulations by a neural model for fluid flow and thermal diagnostics of steam turbines is investigated. Results of calculations of velocity magnitude of steam for 3D model of the stator of steam turbine is presented.
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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublikacjaA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublikacjaA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublikacjaTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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EPILEPTIC BEHAVIOR WITH A DISTINGUISHED PREICTAL PERIOD IN A LARGE-SCALE NEURAL NETWORK MODEL
PublikacjaWe present a neural network model capable of reproducing focal epileptic behavior. An important property of our model is the distinguished preictal state. This novel feature may shed light on the pathologi-cal mechanisms of seizure generation and, in perspective, help develop new therapeutic strategies to manage refractory partial epilepsy.
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublikacjaIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublikacjaShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublikacjaThe slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublikacjaThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Can architecture be 11-dimensional? The nature of space in the architecture of the digital world era
PublikacjaThis research aims to explore the development of architectural theories about ‘architectural dimensions’ and look at architecture as a multidimensional space. It is important to understand that with today's development of virtual reality technology and through the combination of theories of physics and architecture, a new possibility of creating space has emerged. The arguments are made through inductive reasoning and grounded...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublikacjaThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublikacjaExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublikacjaNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublikacjaIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublikacjaIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
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Application of fuzzy neural network for supporting measurements and control in a wastewater treatment plant
PublikacjaOczyszczanie ścieków jest jednym z ważniejszych aspektów ochrony środowiska. Nowoczesne systemy kontroli w oczyszczalniach ścieków pozwalają na poprawę jakości procesu oczyszczania redukując jednocześnie koszty. Systemy kontroli i optymalizacji jakie odkilku lat opracowuje się dla oczyszczalni ścieków, bazują zazwyczaj na skomplikowanych modelach matematycznych. Kluczowym problemem w zastosowaniu tych systemów jest duża liczba...
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PTD4 Peptide Increases Neural Viability in an In Vitro Model of Acute Ischemic Stroke
PublikacjaIschemic stroke is a disturbance in cerebral blood flow caused by brain tissue ischemia and hypoxia. We optimized a multifactorial in vitro model of acute ischemic stroke using rat primary neural cultures. This model was exploited to investigate the pro-viable activity of cell-penetrating peptides: arginine-rich Tat(49–57)-NH2 (R49KKRRQRRR57-amide) and its less basic analogue, PTD4 (Y47ARAAARQARA57-amide). Our model included glucose...
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NF-κB deficit in spinal motoneurons in patients with sporadic amyotrophic lateral sclerosis – a pilot study
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