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Voltage and Current Unbalance Reduction in Power Networks with Distributed Generation and Electric Vehicles
PublikacjaThe current development of prosumer microsources and the expected spread of electric vehicles may cause the appearance of significant current and voltage unbalance in low-voltage (LV) networks. This unbalance, which is an unfavorable phenomenon, may occur when using single-phase photovoltaic (PV) microsources and single-phase home chargers for electric vehicles. This paper presents a proposal for the symmetrization of the LV network...
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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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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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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublikacjaCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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A bound on the number of middle-stage crossbars in f-cast rearrangeable Clos networks
PublikacjaIn 2006 Chen and Hwang gave a necessary and sufficient condition under which a three-stage Clos network is rearrangeable for broadcast connections. Assuming that only crossbars of the first stage have no fan-out property, we give similar conditions for f-cast Clos networks, where f is an arbitrary but fixed invariant of the network. Such assumptions are valid for some practical switching systems, e.g. high-speed crossconnects....
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Spatio-temporal filtering for determination of common mode error in regional GNSS networks
PublikacjaThe spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually...
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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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A survey of strategies for communication networks to protect against large-scale natural disasters
PublikacjaRecent natural disasters have revealed that emergency networks presently cannot disseminate the necessary disaster information, making it difficult to deploy and coordinate relief operations. These disasters have reinforced the knowledge that telecommunication networks constitute a critical infrastructure of our society, and the urgency in establishing protection mechanisms against disaster-based disruptions. Hence, it is important...
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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Methods and means of processing discrete information in networks with a high level of noise
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks
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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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General construction of noiseless networks detecting entanglement with the help of linear maps
PublikacjaW pracy zaprezentowano ogólny schemat konstrukcji bezszumowych sieci pozwalających wykrywać splątanie przy pomocy odwzorowań liniowych. Pokazano jak zastosować metodę do detekcji splątania nieznanego stanu bez jego wcześniejszej rekonstrukcji. W szczególności pokazano, że zawsze istnieje bezszumowa sieć pozwalająca wykrywać splątanie przy użyciu dodatnich, ale nie kompletnie dodatnich odwzorowań. Zaprezentowano także uogólnienie...
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Automatic singing voice recognition employing neural networks and rough sets
PublikacjaCelem prac opisanych w referacie jest automatyczne rozpoznawanie głosów śpiewaczych. Do tego celu utworzona została baza nagrań próbek śpiewu profesjonalnego i amatorskiego. Próbki poddane zostały parametryzacji parametrami zaproponowanymi przez autorów ściśle do tego celu. Sposób wyznaczenia parametrów i ich interpretacja fizyczna przedstawione są w referacie. Parametry wprowadzane są do systemów decyzyjnych, klasyfikatorów opartych...
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublikacjaW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublikacjaNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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Topology improvements in scale-free networks when assuring security and survivability
PublikacjaW artykule zaproponowano heurystyczny algorytm iteracyjny (NEA) kontrolowanego rozrostu sieci, zmniejszający stopień jej bezskalowości. Pokazano, że odpowiednia kontrola rozrostu sieci, prowadzi do uzyskania sieci o topologii zbliżonej do regularnej, a więc w duzym stopniu odpornej na celowe działania niszczące - ataki. Właściwości algorytmu zostały przebadane przy pomocy dedykowanego symulatora dla reprezentatywnej próby inicjalnych...
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Estimation of musical sound separation algorithm effectiveness employing neural networks.
PublikacjaŚlepa separacja dźwięków sygnałów muzycznych zawartych w zmiksowanym materiale jest trudnym zadaniem. Jest to spowodowane tym, że dźwięki znajdujące się w relacjach harmonicznych mogą zawierać kolidujące składowe sinusoidalne (składowe harmoniczne). Ewaluacja wyników separacji jest również problematyczna, gdyż analiza błędu energetycznego często nie odzwierciedla subiektywnej jakości odseparowanych sygnałów. W tej publikacji zostały...
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Self-healing ATM networks based on preplanned restoration of virtual paths
PublikacjaW pracy omówiono klasyfikację metod odtwarzania usług w samonaprawialnych sieciach ATM opartych na ścieżkach wirtualnych i o topologii kratkowej. Przedstawiono model z zaplanowanymi z góry ścieżkami zabezpieczającymi i wyniki badań przykładowej sieci w Polsce.
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublikacjaNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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System Loss Model for Body-to-Body Networks in Indoor and Outdoor Environments
PublikacjaA system loss model for body-to-body networks in indoor and outdoor environments is proposed in this paper, based on measurements taken at 2.45 GHz. The influence of the type of environment, antenna visibility and user mobility on model parameters has been investigated. A significant impact of mutual antennas’ placement and their visibility is shown. The proposed model fits well to empirical data, with the average root mean square...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublikacjaThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Study of data scheduling methods in the WiMAX Mobile metropolitan area networks
PublikacjaThe paper discusses basic assumptions of the WiMAX Mobile system. It also presents and analyses the results of simulation tests run for selected data scheduling methods and subcarrier allocation. Based on the test results, the authors have prepared a comparative analysis of two popular data scheduling methods, i.e. WRR and PF, and their own method CDFQ which uses information about the current channel situation for the queuing processes...
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Cluster-dependent rotation-based feature selection for the RBF networks initialization
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3rd International Workshop on Reliable Networks Design and Modeling (RNDM 2011)
Publikacjaartykuł sprawozdawczy z konferencji
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Enhancing Performance of Switched Parasitic Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). The limitations of the existing design approach are illustrated, as well as perspectives and challenges of the proposed solution in relation to the localization in...
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Fourth International Workshop on Reliable Networks Design and Modeling (RNDM 2012)
Publikacjaartykuł sprawozdawczy z konferencji
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Performance analysis of mobility protocols and handover algorithms for IP-based networks
PublikacjaA rapid growth of IP-based networks and services has created the vast collection of resources and functionality available to users by means of a universal method of access - an IP protocol. At the same time, advances in design of mobile electronic devices have allowed them to reach utility level comparable to stationary, desktop computers, while still retaining their mobility advantage. Following this trend multiple extensions...
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublikacjaBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
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Automated Diagnostics of Current Pick-Up Disturbances in Electric Traction Networks
PublikacjaThe present work defines the basic causes of bow disturbances of current pick-up, sets a task of establishing a system of automated control of bow disturbances at feeder zones of electric traction networks, proposes structural variants of the technical system implementation, describes the algorithm of detection of bow disturbances of current pick-up.
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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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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublikacjaIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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An Off-Body Channel Model for Body Area Networks in Indoor Environments
PublikacjaThis paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two...
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THE USE OF GNSS GEODETIC NETWORKS ON THE APPROACH TO THE PORTS � GULF OF GDANSK STUDY
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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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Influence of User Mobility and Antenna Placement on System Loss in B2B Networks
PublikacjaIn this paper, the influence of user mobility and on-body antenna placement on system loss in body-to-body communications in indoor and outdoor environments and different mobility scenarios is studied, based on system loss measurements at 2.45 GHz. The novelty of this work lies on the proposal of a classification model to characterise the effect of user mobility and path visibility on system loss, allowing to identify the best...
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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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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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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublikacjaIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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Diffusion equations with spatially dependent coefficients and fractal Cauer-type networks
PublikacjaIn this article, we formulate and solve the representation problem for diffusion equations: giving a discretization of the Laplace transform of a diffusion equation under a space discretization over a space scale determined by an increment h > 0, can we construct a continuous in h family of Cauer ladder networks whose constitutive equations match for all h > 0 the discretization. It is proved that for a finite differences discretization...
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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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Methods for physical impairment constrained routing with selected protection in all-optical networks
PublikacjaIn this paper, we investigate the problem of survivable all-optical routing in WDM networks with physical impairments. One of the recent key issues in survivable optical network design refers to maximization of the ratio of routeable demands while keeping the overall network cost low. In WDM networks, this goal can be achieved by routing as many demands in all-optical way as possible. Based on the latest technical trends driven...