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Tytuł:
Simulation of reconfiguration problems in sensor networks using OMNeT++ software
Autorzy:
Dymora, P.
Mazurek, M.
Płonka, P.
Powiązania:
https://bibliotekanauki.pl/articles/106238.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
sensor networks
reallocation algorithm
failure of network node
network-layer protocol
routing protocol
OMNeT++
Opis:
The paper presents a comparative analysis of reallocation algorithms in a structure of wireless sensor network in the event of a failure of network nodes. The article contains detailed research results of wireless sensor networks technology, with particular emphasis on thte network-layer protocols - routing protocols. In the research the simulation environment OMNeT++ was used to study the properties of reconfiguration and reallocation problems in the wireless sensor networks.
Źródło:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2013, 13, 1; 49-67
1732-1360
2083-3628
Pojawia się w:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wybrane metody diagnozowania nieprawidłowości działania sieci teleinformatycznych
Selected methods of diagnosing of telecommunication networks malfunctioning
Autorzy:
Chaładyniak, D.
Grzybowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/91391.pdf
Data publikacji:
2012
Wydawca:
Warszawska Wyższa Szkoła Informatyki
Tematy:
model ISO/OSI
sieci teleinformatyczne
warstwa fizyczna
warstwa łącza danych
warstwa sieciowa
analizator sieci
ISO/OSI model
telecommunication networks
physical layer
data link layer
network layer
network analyzer
Opis:
Sieci teleinformatyczne są efektywne, jeżeli działają prawidłowo, tzn. w pełni realizują swoje funkcje we wszystkich warstwach logicznego modelu ISO/OSI. W realnym świecie jednak z różnych przyczyn występują awarie, które powodują różnego rodzaju problemy z poprawnym działaniem sieci. Opierając się na warstwowym modelu ISO/OSI można sklasyfikować problemy występujące w sieciach teleinformatycznych w odniesieniu do poszczególnych warstw modelu. Większość problemów związanych z niedziałaniem sieci teleinformatycznych przypisane jest do niższych warstw modelu ISO/OSI. Są to warstwy związane z fizycznymi nośnikami danych sieciowych, urządzeniami sieciowymi oraz podstawowymi mechanizmami sterującymi przepływem danych w sieciach teleinformatycznych. Powyższym zagadnieniom poświęcony jest ten artykuł.
Telecommunication networks are efficient when they operate correctly, i.e. they fully carry out their functions in all layers of the logical ISO/OSI model. In the real world for various reasons, there are failures that cause problems and improper operation of networks. Based on the layered ISO/OSI model, we can develop a classification of the problems encountered in data communication networks for the individual layers of the model. Most of the problems related with networks malfunctioning are attributed to lower layers of the ISO/ OSI model. These are related to the network data storage medium, network devices and the basic mechanisms of data flow control in data communication networks. The article presents these issues.
Źródło:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2012, 6, 8; 61-76
1896-396X
2082-8349
Pojawia się w:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy method and neural network model parallel implementation of multi-layer neural network based on cloud computing for real time data transmission in large offshore platform
Autorzy:
Zhang, H..
Qin, W.
Powiązania:
https://bibliotekanauki.pl/articles/259083.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
parallel implementation
multi-layer neural network
cloud computing
Opis:
With the rapid development of electronic technology, network technology and cloud computing technology, the current data is increasing in the way of mass, has entered the era of big data. Based on cloud computing clusters, this paper proposes a novel method of parallel implementation of multilayered neural networks based on Map-Reduce. Namely in order to meet the requirements of big data processing, this paper presents an efficient mapping scheme for a fully connected multi-layered neural network, which is trained by using error back propagation (BP) algorithm based on Map-Reduce on cloud computing clusters (MRBP). The batch-training (or epoch-training) regimes are used by effective segmentation of samples on the clusters, and are adopted in the separated training method, weight summary to achieve convergence by iterating. For a parallel BP algorithm on the clusters and a serial BP algorithm on uniprocessor, the required time for implementing the algorithms is derived. The performance parameters, such as speed-up, optimal number and minimum of data nodes are evaluated for the parallel BP algorithm on the clusters. Experiment results demonstrate that the proposed parallel BP algorithm in this paper has better speed-up, faster convergence rate, less iterations than that of the existed algorithms.
Źródło:
Polish Maritime Research; 2017, S 2; 39-44
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Path Diversity Protection in Two-Layer Networks
Autorzy:
Dzida, M.
Śliwiński, T.
Zagożdżon, M.
Ogryczak, W.
Pióro, M.
Powiązania:
https://bibliotekanauki.pl/articles/308914.pdf
Data publikacji:
2009
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
link dimensioning
path diversity
resilient routing
two-layer network optimization
Opis:
The paper addresses an optimization problem related to dimensioning links in a resilient two-layer network. A particular version of the problem which assumes that links of the upper layer are supported by unique paths in the lower layer is considered. Two mixed-integer programming formulations of this problem are presented and discussed. Direct resolving of these formulations requirespre-selection of "good" candidate paths in the upper layer of the network. Thus, the paper presents an alternative approach which is based on decomposing the resolution process into two phases, resolved iteratively. The first phase subproblem is related to designing lower layer path flows that provide the capacities for the logical links of the upper layer. The second phase is related to designing the flow patterns in the upper layer with protection assured through diversity of paths. In this phase we take into account the failures of the logical links that result from the failures of the lower layer links (so called shared risk link groups).
Źródło:
Journal of Telecommunications and Information Technology; 2009, 3; 14-19
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Experimental and numerical investigation of the deep drawing process for an automobile panel and prediction of appropriate amount of parameters by multi-layer neural network
Autorzy:
Najafabadi, S. S.
Anaraki, A. T.
Moradi, M.
Powiązania:
https://bibliotekanauki.pl/articles/281868.pdf
Data publikacji:
2017
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
deep drawing
finite element analysis (FEA)
multi-layer artificial neural network (ANN)
Taguchi design
Opis:
In this paper, the deep drawing process of an automobile panel in order to select the appropriate amount of parameters has been investigated. The parameters include friction between the blank and die, blank width and length, blank thickness and gap between the blank and blank-holder. A multi-layer artificial neural network (ANN) trained by finite element analyses (FEA) is applied in order to improve forming parameters and achieve a better quality. As the FEA results are used to train the ANN, the FEA results have been verified by three experiments. Finally, an appropriate amount of each parameter is predicted by the trained ANN and a FEA has been done based on the ANN prediction to evaluate the accuracy of the trained ANN. Moreover, it is shown that the ANN could predict results within a 10 percent error. In addition, the proposed method for prediction of the appropriate parameters (ANN) is confirmed by comparing with the Taguchi design of experiment prediction. It is also shown that the model obtained by the former method has lower errors than the latter one. In this study, the Taguchi model is used to evaluate the effect of parameters on tearing and wrinkling. Based on the Taguchi design of experiment, while the blank length is the most effective parameter on tearing, the maximum height of wrinkles on flanged parts mainly depends on the blank thickness.
Źródło:
Journal of Theoretical and Applied Mechanics; 2017, 55, 2; 707-718
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset
Autorzy:
Mosavi, Mohammad Reza
Khishe, Mohammad
Naseri, Mohammad Jafar
Parvizi, Gholam Reza
Ayat, Mehdi
Powiązania:
https://bibliotekanauki.pl/articles/176971.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
MLP NN
Multi-Layer Perceptron Neural Network
ABGSA
Adaptive Best Mass Gravitational Search Algorithm
sonar
classification
Opis:
In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.
Źródło:
Archives of Acoustics; 2019, 44, 1; 137-151
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Statement Networks to Condition Monitoring of the Sealless Pump
Autorzy:
Rzydzik, S.
Amarowicz, M.
Psiuk, K.
Rogala, T.
Powiązania:
https://bibliotekanauki.pl/articles/226493.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
diagnostic model
statement network
multi-layer
expert system
Opis:
This paper shows an application of multi-layer statement networks to condition monitoring of the sealless magnetic drive pump. In this case, statement networks are computed based on the use of Bayesian probabilities. Moreover, the tool called REx which allows implementing such networks is described. An example of created four-layer network as well as final results of the performed tests shows also.
Źródło:
International Journal of Electronics and Telecommunications; 2014, 60, 3; 265-269
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Survey on WSN and MCN Convergence Networks
Autorzy:
Swain, Anita
Ray, Arun Kumar
Powiązania:
https://bibliotekanauki.pl/articles/308703.pdf
Data publikacji:
2020
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
IPv4
MAC layer
machine-to-machine network
QoS
Opis:
In this paper, we present a survey concerned with research focusing on the convergence of wireless sensor networks (WSN) and mobile cellular networks (MCN). The convergence of WSNs and MCNs may be a trigger stimulating new research dealing with such issues as architecture, protocols and air interfaces. The highlights and constraints of the phenomenon are discussed in this paper as well. The survey deals with convergence networks and with their smarty city applications. A few open research issues are also brought to the attention of researchers specializing in this field.
Źródło:
Journal of Telecommunications and Information Technology; 2020, 1; 39-49
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparing Gausian and exact models of malicious interference in VLC systems
Autorzy:
Blinowski, Grzegorz
Mościcki, Adam
Powiązania:
https://bibliotekanauki.pl/articles/225996.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
visible light communication networks
network security
physical layer security
transmission jamming
Opis:
Visible Light Communication (VLC) is a technique for high-speed, low-cost wireless data transmission based on LED luminaries. Wireless LAN environments are a major application of VLC. In these environments, VLC is used in place of traditional systems such as Wi-Fi. Because of the physical characteristics of visible light, VLC is considered to be superior to traditional radio-based communication in terms of security. However, as in all wireless systems, the security of VLC with respect to eavesdropping, signal jamming and modification must be analyzed. This paper focuses on the aspect of jamming in VLC networks. In environments where multiple VLC transmitters are used, there is the possibility that one or more transmitters will be hostile (or "rogue"). This leads to communication disruption, and in some cases, the hijacking of the legitimate data stream. In this paper we present the theoretical system model that is used in simulations to evaluate various rogue transmission scenarios in a typical indoor enviro.The typical approach used so far in jamming analysis assumes that all disruptive transmissions may be modeled as Gaussian noise, but this assumption may be too simplistic. We analyze and compare two models of VLC jamming: the simplified Gaussian and the exact model, where the full characteristics of the interfering signal are taken into account. Our aim is to determine which methodology is adequate for studying signal jamming in VLC systems.
Źródło:
International Journal of Electronics and Telecommunications; 2019, 65, 2; 277-286
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Timing measurement and simulation of the activation process in gigabit passive optical networks
Autorzy:
Horvath, T.
Munster, P.
Jurcik, M
Koci, L
Filka, M.
Powiązania:
https://bibliotekanauki.pl/articles/173869.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
gigabit passive optical network (GPON)
GPON transmission convergence (TC) layer measurement
transmission convergence (TC) layer simulation
MATLAB
GPON timing
Opis:
The passive optical networks are widely used nowadays. Service providers have many customers in their distribution networks. The most important thing for communication between the end unit and the control unit is an establishment contact. Design and measurement of the activation process between optical network unit and optical line termination is presented. In general, the service providers have a big split ratio (up to 1:128) due to the connection eminent value of the customers per optical line termination port in chassis. We present the simulation of the connection process for 16, 32, 64, and 128 optical network units and the measurement for single optical network unit (the GPON Xpert is able to read a single connection process). We compare our results in simulation discussion.
Źródło:
Optica Applicata; 2015, 45, 4; 459-471
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting economic and financial indicators by supply of deep and recovery neural networks
Autorzy:
Boyko, N.
Ivanets, A.
Bosik, M.
Powiązania:
https://bibliotekanauki.pl/articles/411261.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Oddział w Lublinie PAN
Tematy:
neural network
deep
recurrent
activation function
feedforward
neuron
hidden layer
stock price prediction
Opis:
This paper studies the potential of the application of the Recurrent Neural Networks, as well as the Deep Neural Networks in the field of the finances and trading. In particular, their use in the stock price predicting software. The concepts of the RNNs and DNNs are provided and explained thoroughly. Both techniques RNNs and DNNs are utilized in the implementation of the stock price predicting software. Two separate versions of the software are created in order to demonstrate the main differences between the algorithms, as well as to determine the best of the two. Each version is thoroughly examined. The comparison of each of the algorithms is performed and highlighted. Examples of the implementations of the software, utilizing each of the algorithms on big volumes of stock data, for stock price prediction are provided. The article summarizes the concept of stock price prediction backed by the popular machine learning algorithms and its application in the nowadays world.
Źródło:
ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2018, 7, 2; 3-8
2084-5715
Pojawia się w:
ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Burst communication – a solution for the underwater information management
Autorzy:
Nissen, I.
Powiązania:
https://bibliotekanauki.pl/articles/332097.pdf
Data publikacji:
2015
Wydawca:
Polskie Towarzystwo Akustyczne
Tematy:
underwater navigation
underwater communication
acoustical communication
burst communication
underwater network
physical layer
filtered multitone
Opis:
The performance of collaborating information systems in the hydrosphere is based on the robustness and tolerance of the wireless communication task. It is strongly intertwined with the cooperation and coordination reliability under water for sharing resources and common purposes. Key technology and bottleneck is the physical layer communication in the underwater ''chameleon'' acoustic channel environment and the challenges of non trivial channel effects like the multipath propagation - which is rapidly varying over time and space. In this contribution we introduce the burst communication as one possible solution. These transmissions are supposed to be of a very short duration. The purpose is to occupy the acoustical channel in the underwater column only for a short time window, like in impulse and click communication (similar to the use by marine mammal, Khoisan and wugbe languages), e.g. to reduce the probability of transmission collisions and allows an efficient EMission CONtrol (EMCON).
Źródło:
Hydroacoustics; 2015, 18; 113-126
1642-1817
Pojawia się w:
Hydroacoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Employing wireless networks in enhancing occupational safety at the developing seaport – two proposals
Autorzy:
Bauk, S.
Schmeink, A.
Colomer, J.
Powiązania:
https://bibliotekanauki.pl/articles/259992.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
occupational safety
developing seaport
Wireless Body Area Network Sensors (WBANSs)
channel simulations
physical layer
Opis:
The paper proposes two Wireless Body Area Network Sensors (WBANSs) scenarios at the logical and simulation levels for improving occupational safety and health conditions at the developing seaport environment. The Port of Bar (Montenegro) is taken as an exemplar. The logical model is based on the actual position of the Port of Bar at the seaport market, its needs and capacities for the information systems innovation through technology transfer and diffusion. The simulation model analyses the channel between the body central unit (BCU) of the worker’s on port wireless body sub-network and the port access point. The quality of the signal transmission at the physical layer has been tested through a source code generated in the Matlab. The code includes the BCU composite signal modulation, transmission, and demodulation, along with a noise and fading effects analysis. The results of the simulation experiments for the different transmission frequencies and distances between transmitter (worker’s BCU) and receiver (port’s access point) by using binary phase-shift keying (BPSK) and quadratic phase-shift keying (QPSK) modulation schemes are presented. Some directions for further investigations in this field are given, as well.
Źródło:
Polish Maritime Research; 2017, 1; 115-124
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of a neural statistical model for the prediction of relative humidity levels in the region of Rabat-Kenitra, North West Morocco
Autorzy:
El Azhari, Kaoutar
Abdallaoui, Badreddine
Dehbi, Ali
Abdalloui, Abdelaziz
Zineddine, Hamid
Powiązania:
https://bibliotekanauki.pl/articles/2174362.pdf
Data publikacji:
2022
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
artificial neural network
ANN
learning algorithm
multi-layer perceptron
MLP
modelling
Rabat-Kenitra
relative humidity
Opis:
This article accounts for the development of a powerful artificial neural network (ANN) model, designed for the prediction of relative humidity levels, using other meteorological parameters such as the maximum temperature, minimum temperature, precipitation, wind speed, and intensity of solar radiation in the Rabat-Kenitra region (a coastal area where relative humidity is a real concern). The model was applied to a database containing a daily history of five meteorological parameters collected by nine stations covering this region from 1979 to mid-2014. It has been demonstrated that the best performing three-layer (input, hidden, and output) ANN mathematical model for the prediction of relative humidity in this region is the multi-layer perceptron (MLP) model. This neural model using the Levenberg-Marquard algorithm, with an architecture of [5-11-1] and the transfer functions Tansig in the hidden layer and Purelin in the output layer, was able to estimate relative humidity values that were very close to those observed. This was affirmed by a low mean squared error (MSE) and a high correlation coefficient (R), compared to the statistical indicators relating to the other models developed as part of this study.
Źródło:
Journal of Water and Land Development; 2022, 54; 13--20
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinearity Correction in Dynamic Measuring Devices Using Neural Network Models
Korekcja nieliniowości za pomocą modeli sieci neuronowych w zastosowaniu do dynamicznych urządzeń pomiarowych
Autorzy:
Al Rawashdeh, Laith Ahmed Mustafa
Zakharov, Igor Petrovitch
Zaporozhets, Oleg Vasyliovych
Powiązania:
https://bibliotekanauki.pl/articles/2068664.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
artificial neural network
three-layer perceptron
training
inverse model
neural network compensator
sztuczna sieć neuronowa
trójwarstwowy perceptron
uczenie
model odwrotny
kompensator sieci neuronowej
Opis:
A neural network compensator for the nonlinearity of a dynamic measuring instrument is proposed, which allows restoring the value of the measured input signal. The inverse model of a nonlinear dynamic measuring device is implemented based on a three-layer perceptron supplemented by delay lines of input signals. The properties of the proposed neural network compensator are studied through simulation computer modelling using various types of calibration input signals for the training of an artificial neural network.
Zaproponowano kompensator sieci neuronowej dla nieliniowości dynamicznego przyrządu pomiarowego, który umożliwia odtworzenie wartości mierzonego sygnału wejściowego. Odwrotny model nieliniowego dynamicznego urządzenia pomiarowego realizowany jest w oparciu o trójwarstwowy perceptron uzupełniony o linie opóźniające sygnałów wejściowych. Właściwości proponowanego kompensatora sieci neuronowej są badane poprzez symulacyjne modelowanie komputerowe z wykorzystaniem różnego rodzaju sygnałów wejściowych kalibracji do uczenia sztucznej sieci neuronowej.
Źródło:
Pomiary Automatyka Robotyka; 2020, 24, 4; 57--60
1427-9126
Pojawia się w:
Pomiary Automatyka Robotyka
Dostawca treści:
Biblioteka Nauki
Artykuł
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