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Search results for: RADIOCOMMUNICATION NETWORKS
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Guessing Intrinsic Forwarding Trustworthiness of Wireless Ad Hoc Network Nodes
PublicationA novel node misbehavior detection system called GIFTED is proposed for a multihop wireless ad hoc network (WAHN) whose nodes may selfishly refuse to forward transit packets. The system guesses the nodes’ intrinsic forwarding trustworthiness (IFT) by analyzing end-to-end path performance rather than utilizing unreliable and incentive incompatible low-layer mechanisms. It can work with occasional IFT jumps, directional antennae,...
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Artificial Neural Network-Based Sensorless Nonlinear Control Of Induction Motors
PublicationW niniejszym artykule przedstawiono strukturę sztucznej sieci neuronowej służącej do korygowania działania układu estymacji prędkości kątowej wirnika. Odtworzona prędkość kątowa wirnika zostały wykorzystane w bezczujnikowym układzie sterowania silnikiem indukcyjnym pracującym w zamkniętej pętli sprzężenia prędkościowego.Przedstawiono wyniki badań eksperymentalnych z silnikiem o mocy 1,1kW.
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Risk Modelling with Bayesian Networks - Case Study: Construction of Tunnel under the Dead Vistula River in Gdansk
PublicationThe process of decision-making in public procurement of construction projects during the preparation and implementation phases ought to be supported by risk identification, assessment, and management. In risk assessment one has to take into account factors that lead to risk events (background info), as well as the information about the risk symptoms (monitoring info). Typically once the risks have been assessed a decision-maker...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferry Environment
PublicationIn the article an off-body narrowband and ultra-wide band channel model for Body Area Networks in a ferry environment is described. A mobile, heterogeneous measurement stand, that consists of three types of devices: miniaturized mobile nodes, stationary reference nodes and a data acquisition server was developed. A detailed analysis of both radio channels parameters in untypical indoor environment was carried out. An analysis of...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment
PublicationIn the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublicationThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublicationFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Probability estimation of the city’s energy efficiency improvement as a result of using the phase change materials in heating networks
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Modulo N Backoff Scheme for effective QoS differentiation and increased bandwidth utilization in IEEE 802.11 networks
PublicationThe paper presents a new "modulo N" channel access scheme for wireless Local Area Networks (WLANs). The novel solution derives from the Distributed Coordination Function (DCF) of the IEEE 802.11 standard, further elaborated as Enhanced Distribution Channel Access (EDCA) by the 802.11e draft specification. The main innovation concerns improvement of the binary exponential backoff scheme used for collision avoidance in 802.11 networks....
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Fast service restoration under shared protection at lightpath level in survivable WDM mesh grooming networks
PublicationW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów w przeżywalnych sieciach optycznych z agregacją strumieni ruchu. Zaproponowana metoda bazuje na wierzchołkowym kolorowaniu grafu konfliktów. Jest pierwszym podejściem, dedykowanym sieciom optycznym z agregację strumieni ruchu z pełną zdolnością do konwersji długości fal, która nie powoduje wydłużenia ściezek zabezpieczjących, a więc zapewnia szybkie odtwarzanie...
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Social networks as a context for small business? A new look at an enterprise in the context of a smallness and newness liability syndrome
PublicationIn this paper we aim to propose and outline key ingredients to a small enterprise success, emerging from the social capital of small business owner-managers and their business networks. We employ resource based view of an organization as well as an embeddedness perspective along with new approach transaction costs to outline the pillars of an advantage of a small business entity. The analysis of survey data leads us to conclusion,...
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Selfishness Detection in Mobile Ad Hoc Networks: How Dissemination of Indirect Information Turns into Strategic Issue
PublicationDla środowiska sieci mobilnej ad hoc przedyskutowano wymienność pomiędzy wydatkiem energetycznym węzła egoistycznego a obniżaniem jego metryki reputacyjnej. Badania symulacyjne wskazują, że atakom polegającym na selektywnym usuwaniu pakietów można przeciwdziałać poprzez datacentryczny system reputacyjny bazujący na potwierdzeniach końcowych, który nakazuje jednakowo uaktualniać metryki reputacyjne dla wszystkich węzłów na źle zachowującej...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublicationThis paper presents the design, realization and measurements of 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). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Fabrication of toughened plastic using styrene butadiene rubber-poly (methyl methacrylate) interpenetrating polymer networks
PublicationA standard set of interpenetrating polymeric networks (IPNs) has been contrived using an elastomerstyrene butadiene rubber and a thermoplastic poly (methyl methacrylate) through sequential polymerization protocol. This low-cost material can be hopefully engaged as a toughened plastic with cocontinuous morphology. Different morphological protocols including Raman imaging are effectively utilized to envisage the effect of blend ratio...
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The European Training Network ETUDE (Encompassing Training in fUnctional Disorders across Europe): a new research and training program of the EURONET-SOMA network recruiting 15 early stage researchers
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International Journal of Networked and Distributed Computing
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Digital Communications and Networks
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublicationLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublicationTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublicationW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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A new approach to inter-layer sharing providing differentiated protection services in survivable IP-MPLS/WDM networks
PublicationArtykuł omawia zagadnienie ochrony transmisji o charakterze połączeniowym w sieciach wielowarstwowych IP-MPLS/WDM. W szczególności prezentuje nową metodę współdzielenia międzywarstwowego zasobów ścieżek zabezpieczających gwarantującą szybkie odtwarzanie uszkodzonych połączeń (nawet o 40% szybciej w porównaniu z powszechnie stosowaną metodą).
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Practical Trial for Low-Energy Effective Jamming on Private Networks With 5G-NR and NB-IoT Radio Interfaces
PublicationFourth-generation (4G) mobile networks are successively replaced by fifth-generation (5G) ones, based on the new releases of the 3rd Generation Partnership Project (3GPP) standard. 5G generation is dedicated to civilian users and the conducted analytical work shows that it has numerous technological gaps that prevent its direct implementation in military communications systems. However, the recent armed world conflicts showed that...
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Frequency-Variant Double-Zero Single-Pole Reactive Coupling Networks for Coupled-Resonator Microwave Bandpass Filters
PublicationIn this work, a family of frequency-variant reactive coupling (FVRC) networks is introduced and discussed as new building blocks for the synthesis of coupled-resonator bandpass filters with real or complex transmission zeros (TZs). The FVRC is a type of nonideal frequency-dependent inverter that has nonzero elements on the diagonal of the impedance matrix, along with a nonlinear frequency-variation profile of its transimpedance...
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Service time distribution influence on end-to-end call setup delay calculation in networks with Session Initiation Protocol
PublicationThe most important GoS parameter for networks with SIP protocol is end-to-end call setup delay. So far there were no coherent models allowing calculation of these parameters for networks with SIP protocol. Few models were developed but they are insufficient. In the paper we propose model which allows end-to-end call setup delay calculation for networks with SIP protocol. The model is using chain of M/G/1/K models and is applicable...
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Rearrangeable clos networks C(n,r_1,n^2-1,n,r_2) with certain restrictions for connections
PublicationW pracy została zaproponowana nowa metoda sprawdzania przestrajalności pól Closa dla połączeń jeden do wiele. W rozważaniach zakładamy grupowanie połączeń.In the article we will propose new method of checking rearrangeability of multicast Clos networks. In the literature there is no precise method for checking rearrangeability. We focused on three-stage Clos networks without any constraints about fan-out capability. We show the...
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INTER-LAYER SHARING OF BACKUP PATH CAPACITIES PROVIDING FAST SERVICE RECOVERY IN IP-MPLS/WDM NETWORKS
PublicationIn this paper, we investigate the issue of providing the transmission continuity in IP-MPLS/WDM networks in the presence of failures of nodes/links. Special focus is put on assuring fast restoration of flows affected after a failure in a scenario assuming sharing the backup path capacities in order to decrease the overall bandwidth consumption. In particular, we propose a new approach to inter-layer sharing of link capacity reserved...
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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublicationThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublicationObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Proposal of a System Loss Model for Body Area Network in Passenger Ferry Environment
PublicationIn the paper, proposal of an empirical off-body system loss model for Body Area Networks working in a passenger ferry environment at 2.45 GHz has been presented. The measurements were carried out for dynamic scenarios in the discotheque passenger ferry environment. The general model formula consists of three components: mean system loss, attenuation resulting from the variable antenna position on the human body, and attenuation...
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Transmission Losses Spatial Analysis of the Supply System of Electrified Urban Transport Network
PublicationThe paper presents mathematical model TOPSIS which was applied for MCDA benchmark of trolleybus supply system. Moreover, paper presents the novel method of transmission losses analysis in electrified urban transport system. Research work was based on measurements realized in Gdynia trolleybus network.
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Step-Up DC/DC Converters With Cascaded Quasi-Z-Source Network
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DAB+ Coverage Analysis: a New Look at Network Planning using GIS Tools
PublicationFor many years, the matter of designing a transmitter network, optimized for best signal coverage, has been a subject of intense research. In the last decade, numerous researchers and institutions used GIS and spatial analysis tools for network planning, especially transmitter location. Currently, many existing systems operate in a strictly two-dimensional manner, not taking into account the three-dimensional nature of the analyzed...
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Network oscillations modulate interictal epileptiform spike rate during human memory
PublicationEleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...