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Search results for: MULTIDOMAIN NETWORK
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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublicationThe 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 Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublicationCurrently, 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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Entangled rendezvous: a possible application of Bell non-locality for mobile agents on networks
PublicationRendezvous is an old problem of assuring that two or more parties, initially separated, not knowing the position of each other, and not allowed to communicate, are striving to meet without pre-agreement on the meeting point. This problem has been extensively studied in classical computer science and has vivid importance to modern and future applications. Quantum non-locality, like Bell inequality violation, has shown that in many...
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Service-based Resilience via Shared Protection in Mission-critical Embedded Networks
PublicationMission-critical networks, which for example can be found in autonomous cars and avionics, are complex systems with a multitude of interconnected embedded nodes and various service demands. Their resilience against failures and attacks is a crucial property and has to be already considered in their design phase. In this paper, we introduce a novel approach for optimal joint service allocation and routing, leveraging virtualized...
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A Wideband Channel Model for Body Area Networks in Circular Metallic Indoor Environments
PublicationIn this paper, the wideband characterization of the propagation channel in circular metallic indoor environments is addressed, regarding Body Area Networks and 5G small cells, an analytical model for the dependence of the mean delay and the average delay spread on the circle radius, the working frequency and the distance between the transmitter and the receiver being proposed. The derivation of the model is initially done analytically,...
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The Analysis of Cross-Polarisation Discrimination for Body Area Networks in Cylindrical Metallic Environment
PublicationThe analysis of cross-polarisation discrimination for Body Area Networks in an untypical environment of cylindrical metallic room has been performed in the paper. This analysis was done based on the measurements carried out for dynamic narrowband off-body channels operating at the frequency of 2.45 GHz. The results have shown that there is a strong dependence of the depolarisation effect on the existence of direct component in...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublicationNumerous 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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ON DYNAMICS OF ELASTIC NETWORKS WITH RIGID JUNCTIONS WITHIN NONLINEAR MICRO-POLAR ELASTICITY
PublicationWithin the nonlinear micropolar elasticity we discuss effective dynamic (kinetic) properties of elastic networks with rigid joints. The model of a hyperelastic micropolar continuum is based on two constitutive relations, i.e., static and kinetic ones. They introduce a strain energy density and a kinetic energy density, respectively. Here we consider a three-dimensional elastic network made of three families of elastic fibers connected...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe 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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Event driven MPC for networked control systems
PublicationBecause of variable delays and stochastic data packets loss networked control systems require suitable algorithms to ensure stability of the control system and guarantee desired control performance. This paper presents the idea of an event driven approach with MPC controller. In opposition to network compensation, where standard regulators are used, the presented solution integrates network with plant. A MPC based controller is...
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Journal of Networks
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IEEE Transactions on Signal and Information Processing over Networks
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EAI Endorsed Transactions on Industrial Networks and Intelligent Systems
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International Journal of Networked and Distributed Computing
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Stromal-Epithelial Cross-Talk in the Intestinal Stem Cell Niche is Mediated by a Regulatory Network that Involves TGF-Beta and CTGF
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A Simulation-Optimization Model for Automated Parcel Lockers Network Design in Urban Scenarios in Pamplona (Spain), Zakopane, and Krakow (Poland)
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Prenatal stress leads to changes in IGF-1 binding proteins network in the hippocampus and frontal cortex of adult male rat
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A diode rectifier with a Special Coupled Reactor and additional Active Power Filter in the Marine Local Power Network Supply Conditions
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Planowanie rozwoju sieci dystrybucji energii elektrycznej na obszarach miejskich = Planning of development of the urban electricity distribution network
PublicationReferat przedstawia opis rozwiązania problemu planowania rozwoju sieci dystrybucji energii elektrycznej na obszarach miejskich. Rozwiązanie uzyskuje się w drodze zaprogramowania rozwoju z wykorzystaniem algorytmu genetycznego. Uwzględniane są dane o zawodności istniejącej infrastruktury i jej ograniczenia przesyłowe. Podjęto również próbę odwzorowania możliwych do wyboru tras prowadzenia linii kablowych. Funkcja zdatności rozwiązania...
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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublicationW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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Update on the molecular pathogenesis and clinical treatment of Mantle Cell Lymphoma (MCL): minutes of the 9th European MCL Network conference
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Real-Time Basic Principles Nuclear Reactor Simulator Based on Client-Server Network Architecture with WebBrowser as User Interface
PublicationThe real-time simulator of nuclear reactor basic processes (neutron kinetics, heat generation and its exchange, poisoning and burn- ing up fuel) build in a network environment is presented in this paper. The client-server architecture was introduced, where the server is a pow- erful computing unit and the web browser application is a client for user interface purposes. The challenge was to develop an application running under the...
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Selecting wells for an optimal design of groundwater monitoring network based on monitoring priority map: A Kish Island case study
PublicationThis paper presents a novel approach, i.e. a combination of gamma test and monitoring priority map, for optimal design of groundwater monitoring network (GMN) by considering the cumulative effects of industries, human activities, and natural factors on the groundwater quality. The proposed method was successfully applied to design an optimal network for groundwater salinity monitoring on Kish Island, Persian Gulf. The priority...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublicationIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for detection of organic gases (ethanol, acetone)
Open Research DataCarbon nanotube networks of different optical transparencies were investigated via resistance and 1/f noise measurements for detection of ethanol and acetone. The sensor resistive and noise responses were collected for dark and UV-assisted conditions, revealing the improvement in sensor sensitivity and limit of detection after applying UV light (275...
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Shifting from the EU’s production networks? Electronics industry exports of Central and Eastern Europe
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Efficiency of service recovery in scale-free optical networks under multiple node failures
PublicationIn this paper we examine the properties of scale-free networks in case of simultaneous failures of two networknodes. Survivability assumptions are as follows: end-to-end path protection with two node-disjoint backup pathsfor each working path. We investigate three models of scale-free networks generation: IG, PFP and BA.Simulations were to measure the lengths of active and backup paths and the values of service recovery time.We...
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Large-scale multimedia content delivery over optical networks for interactive TV services
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Maximization of multicast periodic traffic throughput in multi-hop wireless networks with broadcast transmissions
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Throughput vs. Resilience in Multi-hop Wireless Sensor Networks with Periodic Packet Traffic
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Comparison of IP-based and explicit paths for one-to-one fast reroute in MPLS networks
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New Alternative Passive Networks to Improve the Range Output Voltage Regulation of the PWM Inverters
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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On reducing the value of aggregate restoration time when assuring survivability in scale-free networks.
PublicationReferat dotyczy zapewniania przeżywalności połączeń w rozległych sieciach bezskalowych. Zaproponowano metrykę pozwalającą omijać centra sieci, a tym samym zmniejszać ilość połączeń wymagających odtwarzania na skutek awarii węzła. Wyniki dla sieci bezskalowych porównywane są z wynikami dla sieci losowych. Uzyskane wyniki potwierdzają efektywność metryki w sieciach bezskalowych.
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Using LSTM networks to predict engine condition on large scale data processing framework
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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublicationHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Distributed protection against non-cooperative node behavior in multi-hop wireless networks
PublicationAn important security problem in today's distributed data networks is the prevention of non-cooperative behavior i.e., attacks consisting in the modification of standard node operation to gain unfair advantage over other system nodes. Such a behavior is currently feasible in many types of computer networks whose communication protocols are designed to maximize the network performance assuming full node cooperation. Moreover, it...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...