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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublikacjaThe exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...
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High-Power Jamming Attack Mitigation Techniques in Spectrally-Spatially Flexible Optical Networks
PublikacjaThis work presents efficient connection provisioning techniques mitigating high-power jamming attacks in spectrally-spatially flexible optical networks (SS-FONs) utilizing multicore fibers. High-power jamming attacks are modeled based on their impact on the lightpaths’ quality of transmission (QoT) through inter-core crosstalk. Based on a desired threshold on a lightpath’s QoT, the modulation format used, the length of the path,...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal 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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New Alternative Passive Networks to Improve the Range Output Voltage Regulation of the PWM Inverters
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Highlights from RNDM 2018 – 10th Anniversary Workshop on Resilient Networks Design and Modeling
PublikacjaArtykuł prezentujący relację z workshopu RNDM 2018
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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A Reputation Scheme to Discourage Selfish QoS Manipulation in Two-Hop Wireless Relay Networks
PublikacjaIn wireless networks, stations can improve their received quality of service (QoS) by handling packets of source flows with higher priority. Additionally, in cooperative relay networks, the relays can handle transit flows with lower priority. We use game theory to model a two-hop relay network where each of the two involved stations can commit such selfish QoS manipulation. We design and evaluate a reputation-based incentive scheme...
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Inter-governmental Collaborative Networks for Digital Government Innovation Transfer -Structure, Membership, Operation
PublikacjaDigital government refers to the transformation of government organizations and their relationships with citizens, business and each other through digital technology. It entails digital innovation in processes, services, organizations, policies, etc. which are increasingly developed and tested in one country and transferred, after adaptation, to other countries. The process of innovation transfer and the underlying information...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Using LSTM networks to predict engine condition on large scale data processing framework
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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublikacjaIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Development of cooperation in localized cooperation networks: A comparative study of cluster organizations and technology parks
PublikacjaThe main aim of the paper is to analyze the level of development of cooperative relationships in localized cooperation networks – among enterprises associated in cluster organizations and park tenants. The author reports the findings from the quantitative study carried out in the selected cluster organizations and technology parks functioning in Poland. The basic method of data collection was a survey questionnaire. The research...
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublikacjaIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Performance Evaluation of GAM in Off-Body Path Loss Modelling for Body Area Networks
PublikacjaThis paper addresses the performance evaluation of an off-body path loss model, based on measurements at 2.45 GHz, which has been developed with the use of the Generalised Additive Model, allowing to model a non-linear dependence on different predictor variables. The model formulates path loss as a function of distance, antennas’ heights, antenna orientation angle and polarisation, results showing that performance is very sensitive...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublikacjaFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublikacjaThis work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry...
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Efficiency of service recovery in scale-free optical networks under multiple node failures
PublikacjaIn 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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Distributed protection against non-cooperative node behavior in multi-hop wireless networks
PublikacjaAn 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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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe 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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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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Numerical Analysis of Steady Gradually Varied Flow in Open Channel Networks with Hydraulic Structures
PublikacjaIn this paper, a method for numerical analysis of steady gradually varied fl ow in channel networks with hydraulic structures is considered. For this purpose, a boundary problem for the system of ordinary differential equations consisting of energy equation and mass conservation equations is formulated. The boundary problem is solved using fi nite difference technique which leads to the system of non-linear algebraic equations....
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Dempster-shafer theory-based trust and selfishness evaluation in mobile ad hoc networks
PublikacjaThe paper addresses the problem of selfishness detec-tion in mobile ad hoc networks. It describes an approach based on Dempster-Shafer theory of evidence. Special attention is paid to trust evaluation and using it as a metric for coping with (weighted) recommendations from third-party nodes. Efficiency and robustness of the pre-sented solution is discussed with an emphasis on resil-iency to false recommendations.
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublikacjaMost 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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Shifting from the EU’s production networks? Electronics industry exports of Central and Eastern Europe
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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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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublikacjaIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublikacjaCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Capacity efficient shared protection and fast restoration scheme in self-configured optical networks
PublikacjaW artykule zaproponowano nową koncepcję optymalizacji rozdziału zasobów dla przeżywalnych sieci rozległych, która gwarantuje szybkie odtwarzanie usług po wystąpieniu awarii. Wykazano, iż proponowany algorytm, wykorzystujący ideę wierzchołkowego kolorowania grafów, nie powoduje wydłużania ścieżek zabezpieczających - zjawiska charakterystycznego dla powszechnie stosowanych algorytmów optymalizacji. Udowodniono, iż powyższa cecha...
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Primary role identification in e-mail networks using pattern subgraphs and sequence diagrams
PublikacjaSocial networks often forms very complex structures that additionally change over time. Description of actors' roles in such structures requires to take into account this dynamics reflecting behavioral characteristics of the actors. A role can be defined as a sequence of different types of activities. Various types of activities are modeled by pattern subgraphs, whereas sequences of these activities are modeled by sequence diagrams....
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis 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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On reducing the value of aggregate restoration time when assuring survivability in scale-free networks.
PublikacjaReferat 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
PublikacjaPrzedyskutowano 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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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublikacjaArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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KONFIGURACJA SIECI LAN TYPU SOHO DO PRACY W INTERNECIE IPv6
PublikacjaArtykuł przedstawia podstawowe problemy występujące przy migracji środowisk małych sieci do obsługi protokołu IPv6. Wraz z problemami przedstawione zostały propozycje metodologii przeprowadzenia migracji i narzędzia wspomagające ten proces. Przedstawiono system wspierający administratorów w migracji zarządzanych przez nich sieci do obsługi protokołu IPv6. Celem pracy jest analiza problemów procesów migracji IPv4 do IPv6 oraz wskazanie...
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Networkig activities of general judiciary - from theory to practice
PublikacjaOver the last three decades, networks - as a field of research - have acquired a significant place among management sciences. Unfortunately, in the judiciary they have become a subject of more careful analyses only recently, which resulted in a large discrepancy of knowledge - both in theory and in its practical adaptation for the needs of the courts. In order to fill this cognitive gap, an attempt was made to identify levels of...
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Security Evaluation of IT Systems Underlying Critical Networked Infrastructures
PublikacjaCritical infrastructures have become highly dependent on information and communication technology (ICT). The drawback of this situation is that the consequences of disturbances of the underlying ICT networks may be serious as cascading effects can occur. This raises a high demand for security assurance, with a high importance assigned to security evaluations. In this paper we present an experiment-centric approach for the characterisation...
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On the Importance of Resilience Engineering for Networked Systems in a Changing World
PublikacjaResilience is featured increasingly often in the media, usually applied to society when faced, for example, with disasters such as flooding and the enormous challenges that the Covid-19 pandemic posed. There are now many resilience-related discussion groups worldwide, and some standards initiatives devoted in particular to city resilience. However, there is relatively little explicit interest in resilience engineering for communication...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublikacjaThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublikacjaIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...