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Robust estimation of deformation from observation differences for free control networks
PublicationDeformation measurements have a repeatable nature. This means that deformation measurements are performed often with the same equipment, methods, geometric conditions and in a similar environment in epochs 1 and 2 (e.g., a fully automated, continuous control measurements). It is, therefore, reasonable to assume that the results of deformation measurements can be distorted by both random errors and by some non-random errors, which...
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Reliable routing and resource allocation scheme for hybrid RF/FSO networks
PublicationSignificant success of wireless networks in the last decade has changed the paradigms of communication networks design. In particular, the growing interest in wireless mesh networks (WMNs) is observed. WMNs offer an attractive alternative to conventional cable infrastructures, especially in urban areas, where the cost of new installations is almost prohibitive. Unfortunately, the performance of WMNs is often limited by the cluttered...
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Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks
PublicationThe aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe 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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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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3rd International Workshop on Reliable Networks Design and Modeling (RNDM 2011)
Publicationartykuł sprawozdawczy z konferencji
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Enhancing Performance of Switched Parasitic Antenna for Localization in Wireless Sensor Networks
PublicationThis 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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General construction of noiseless networks detecting entanglement with the help of linear maps
PublicationW 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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Evaluation of IEEE 802.21 Handover between IEEE 802.11 and UMTS Networks
PublicationThe paper presents IEEE 802.21 - the ongoing standard for network handovers - illustrating its functional features, and considering and simulating a set of scenarios of mobile stations moving between IEEE 802.11 and UMTS networks. In order to evaluate the performance of IEEE 802.21 hanover packet loses and switching delays caused by hanover procedures are investigated. The authors discuss example results of simulation experiments...
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Automatic singing voice recognition employing neural networks and rough sets
PublicationCelem 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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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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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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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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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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Simulation model for evaluation of QoS routing algorithm in large packet networks
PublicationThe variety of traffic transferred via current telecommunication networks includes also voice, which should meet quality requirements. One of mechanisms, which can support QoS in current packet networks, is routing. There exist many routing proposals which should introduce the QoS into the network but practically they don't. Following paper presents the realization of simulation model for evaluation of a new routing algorithm DUMBRA...
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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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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A hybrid-mesh solution for coverage issues in WiMAX metropolitan area networks.
PublicationThe new WiMAX technology offers several advantages over the currently available (GSM or UMTS-based) solutions. It is a cost effective, evolving, and robust technology providing quality of service guarantees, high reliability, wide coverage and non-line-of-sight (NLOS) transmission capabilities. All these features make it particularly suitable for densely populated urban environments. In this paper we discuss the design and implementation...
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Adaptive prediction of stock exchange indices by state space wavelet networks
PublicationThe paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session...
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The reliability of any-hop star networks with respect to failures of communication nodes.
PublicationThis paper investigated the reliability of any-hop star networks. The any-hop star topology is used in centralized computer networks. We will assume that the all nodes fail independently, links are failure-free. Following measures of network reliability are assumed: the expected number of nodes, which can communicate with the central node; the expected number of node pairs, which are connected by a path through the central node;...
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Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture
PublicationDynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...
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Comparative study of neural networks used in modeling and control of dynamic systems
PublicationIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe 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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An Off-Body Channel Model for Body Area Networks in Indoor Environments
PublicationThis 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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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Local variance factors in deformation analysis of non-homogenous monitoring networks
PublicationThis paper proposes a modification of the classical deformation analysis algorithm for non-homogeneous (e.g. linear-angular) monitoring networks. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal monitoring network. The obtained results confirm the usefulness of the proposed solution.
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublicationBearing 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
PublicationThe 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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Study of data scheduling methods in the WiMAX Mobile metropolitan area networks
PublicationThe 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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Fourth International Workshop on Reliable Networks Design and Modeling (RNDM 2012)
Publicationartykuł sprawozdawczy z konferencji
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublicationIn 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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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Cost-Efficient Optical Fronthaul Architectures for 5G and Future 6G Networks
PublicationFifth-generation and Beyond (5GB) wireless networks have introduced new centralized architectures such as cloud radio access network (CRAN), which necessitate extremely high-capacity low latency Fronthaul (FH). CRAN has many advantageous features in terms of cost reduction, performance enhancement, ease of deployment, and centralization of network management. Nevertheless, designing and deploying a cost-efficient FH is still a...
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Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks
PublicationThe rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs....
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System Loss Model for Body-to-Body Networks in Indoor and Outdoor Environments
PublicationA 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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Diffusion equations with spatially dependent coefficients and fractal Cauer-type networks
PublicationIn 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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THE USE OF GNSS GEODETIC NETWORKS ON THE APPROACH TO THE PORTS � GULF OF GDANSK STUDY
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Technology brands in the digitally-based and network economy. Setting the background
PublicationThis chapter defines and draws a general picture on Digital Technologies and Technology Brands’ meaning in the current economy. It contextualises the role and channels of digital technology’s impact on their shaping technology brands in network economy. It briefly explains why digital, innovative technologies constitute a perfect background and environment for technology brands of global scope. It discusses the place of technology...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Application of the Polish Active Geodetic Network for railway track determination
PublicationJednym z głównych problemów wyznaczania przebiegu trasy kolejowej jest konieczność realizacji pomiarów geodezyjnych w lokalnym układzie współrzędnych, który znacząco wpływa na dokładność wyznaczeń pozycji w przypadku pomiarów realizowanych na długich (kilku dziesięcio kilometrowych) odcinkach trasy. Z tego względu pomiary realizuje się sekcyjnie, co skutkuje istotnymi z punktu widzenia dokładności dodatkowymi błędami. W roku 2004...
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EFFICIENCY OF HEALTHCARE SYSTEMS IN EUROPEAN COUNTRIES - THE DEA NETWORK APPROACH
PublicationHealthcare systems in Europe are constantly undergoing reforms which adapt them to social, economic and political requirements. The aim of this article is to examine the efficiency of healthcare systems in 30 European countries in 2014. The Network Data Envelopment Analysis (NDEA) model was used. The efficiency of the countries’ overall health systems and their two main components were examined: the public health system and the...
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Full Network Coverage Monitoring Solutions – The netBaltic System Case
PublicationThis paper defines the problem of monitoring a specific network, and more precisely – part of reporting process, which is responsible for the transport of data collected from network devices to station managers. The environment requires additional assumptions, as a specific network related to the netBaltic Project is to be monitored. Two new monitoring methods (EHBMPvU and EHBMPvF) are proposed, which priority is full network coverage....
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...