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Search results for: EMAIL NETWORKS
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A framework for detection of selfishness in multihop mobile ad hoc networks
PublicationThe paper discusses the need for a fully-distributed selfishness detection mechanism dedicated for multihop wireless ad hoc networks which nodes may exhibit selfish forwarding behaviour. The main contribution of this paper is an introduction to a novel approach for detecting and coping with the selfish nodes. Paper describes a new framework based on Dempster-Shafer Theory called Dempster-Shafer Theory-based Selfishness Detection...
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Routing decisions independent of queuing delays in broadband leo networks
PublicationThis paper presents an analysis of queuing and propagation delays of Inter-Satellite Links (ISLs) in broadband Low-Earth Orbit (LEO) satellite networks. It is shown that queuing delays are negligible in all reasonable working conditions of the broadband ISL network. This fact makes it possible to simplify the routing protocols in such networks and permits using already known multi-commodity flow solutions for routing. The performance...
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Localization in wireless sensor networks using switched parasitic antennas
PublicationA switched parasitic monopole antenna for 2.4 GHz ISM applications is design and investigated in this paper. One of the most promising applications for such switched-beam antennas is localization in wireless sensor networks (WSN). It is demonstrated that the use of this antenna improves accuracy of localization algorithms and allows for reduction of the number of reference nodes in localization system.
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Joint optimization of anycast and unicast flows in survivable optical networks
PublicationZnane z literatury dotychczasowe prace związane z ochroną ruchu przed awarią elementów sieci dotyczą transmisji typu unicast (jeden-do-jednego). Niniejszy artykuł jest pierwszym prezentującym rozwiązanie jednoczesnej ochrony transmisji anycast (jeden-do-jednego-z-wielu) oraz transmisji unicast. Proponowane podejście wykorzystuje model ochrony ścieżki (ang. path protection). Zagadnienie zostało sformułowane w postaci odpowiedniego...
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A practical approach to restoration in survivable IP/WDM mesh networks
PublicationW pracy omówiono warstwową architekturę: IP na optycznej sieci transportowej (OTN). Węzły mają zintegrowaną funkcjonalność: rulerów IP i przełącznic optycznych (OXC). Dopuszcza się możliwość konwersji długości fal na ścieżkach optycznych. Autor rozważa zagadnienie znalezienia ścieżek optycznych o możliwie najniższym koszcie przy spełnieniu ograniczeń przepustowości, wymaganych strumieni zapotrzebowań i zabezpieczonych z góry na...
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Water hammer analysis in pipe networks by the method of characteristics (MOC).
PublicationZastosowano w pracy metodę charakterystyk do analizy zjawiska uderzenia hydraulicznego w sieci wodociągowej pierścieniowej.
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System Loss Model for Body Area Networks in Room Scenarios
PublicationThis paper presents an analysis of system loss in Body Area Networks for room scenarios, based on a wideband measurement campaign at 5.8 GHz. The measurements were performed with a fixed antenna transmitting vertically and horizontally polarised signals, while the user wears dualpolarised antennas. The average system losses in co- and crosspolarised channels are 41.4 and 42.6 dB for vertically polarised transmitted signals and...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Proposal of improvement to fairness mechanism of Resilient Packet Ring networks
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Application of neural networks for description of pressure distribution in slide bearing.
PublicationBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublicationWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Interdependence between Power Grids and Communication Networks: A Resilience Perspective
PublicationPower network resilience is increasingly dependent on communication networks. Besides traditional generation, power networks need to accommodate increasingly high penetration levels of dispersed micro generation, mostly based on renewable sources, and increasing and challenging demand, such as electric vehicles. At the same time the deployment of enabling technologies throughout the power grid makes available new demand resources...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublicationThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Measurement of Coherence Bandwidth in UHF Radio Channels for Narrowband Networks
PublicationThis paper presents results of investigation on the coherence bandwidth of narrowband radio channels in 430MHz band. The coherence bandwidth values were estimated froma power delay profile obtained by recording CDMA2000 forward channel signals during real-fieldmeasurements in various environments:mediumcity, flat terrain, and hilly terrain in northern Poland.The results of measurements are compared with characteristic parameters...
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The Analysis and Solutions to the Problems of IPv6 Configuration Migration of Small Networks
PublicationThe paper analyzes the problems of IPv4 to IPv6 migration processes and indicates the areas in which migration can be done without expensive replacement of hardware, software and organizational changes. This paper presents the migration tools developed for the SOHO network administrators. The tools provide theoretical knowledge and practical advices on migrating to IPv6 and enable automation of the migration process. The article...
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Exploring the role of social networks among entrepreneurial Polish immigrants
PublicationThe paper reports on the explanatory case study among seven Polish enterprising migrants from Aberdeen Scotland. The aim of the paper is to examine role of social support structure and social networks for enterprising Poles. It also attempts to extend of Waldinger et al (2000) ethnic business development model in the context of entrepreneurial strategies taken from by immigrants from their country of origin, claiming that transition...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Trade-offs in multiparty Bell-inequality violations in qubit networks
PublicationTwo overlapping bipartite binary input Bell inequalities cannot be simultaneously violated as this would contradict the usual no-signalling principle. This property is known as monogamy of Bell inequality violations and generally Bell monogamy relations refer to trade-offs between simultaneous violations of multiple inequalities. It turns out that multipartite Bell inequalities admit weaker forms of monogamies that allow for violations...
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On the Disaster Resiliency within the Context of 5G Networks : The RECODIS Experience
PublicationNetwork communications and the Internet pervade our daily activities so deeply that we strongly depend on the availability and quality of the services they provide. For this reason, natural and technological disasters, by affecting network and service availability, have a potentially huge impact on our daily lives. Ensuring adequate levels of resiliency is hence a key issue that future network paradigms, such as 5G, need to address. This...
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Estimation the rhythmic salience of sound with association rules and neural networks
PublicationW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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Józef Woźniak prof. dr hab. inż.
PeopleProfessor Józef Woźniak received his M.Sc., Ph.D. and D.Sc. degrees in electronics and telecommunications from the Faculty of Electronics, Gdańsk University of Technology (GUT), Poland, in 1971, 1976 and 1991, respectively. In January 2002 he became a full professor. In 1993 he was elected Associate Dean of the Faculty of Electronics and in 1994 he was he was appointed a Professor at GUT. Simultaneously, from October 1994 till...
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Organization of BBMRI.pl: The Polish Biobanking Network
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Network analyses with the use of spatial databases
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Software Agents for Computer Network Security
PublicationThe chapter presents applications of multi-agent technology for design and implementation of agent-based systems intended to cooperatively solve several critical tasks in the area of computer network security. These systems are Agent-based Generator of Computer Attacks (AGCA), Multi-agent Intrusion Detection and Protection System (MIDPS), Agent-based Environment for Simulation of DDoS Attacks and Defense (AESAD) and Mobile Agent...
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Berkeley Open Infrastructure for Network Computing
PublicationZaprezentowano system BOINC (ang. Berkeley Open Infrastructure for Network Computing) jako interesujące rozwiązanie integrujące rozproszone moce obliczeniowe osobistych komputerów typu PC w Internecie. Przedstawiono zasadę działania opisywanej platformy. W dalszej części zaprezentowano kilka wybranych projektów naukowych wykorzystujących BOINC, które są reprezentatywne w zakresie zastosowania systemu w ujęciu założonego paradygmatu...
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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Universal Augmentation Schemes for Network Navigability
PublicationRozważano problem uzupełniania grafu (reprezentującego np. sieci społeczne) poprzez dodanie w każdym węźle jednego dodatkowego skierowanego połączenia (długodystansowego). Dokładniej, dla każdego węzła definiuje się listę prawdopodobieństw istnienia połączenia wychodzącego z danego węzła do wszystkich pozostałych węzłów; wartości tych prawdopodobieństw muszą sumować się do jedności. Routing zachłanny w takiej sieci polega na przekazywaniu...
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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IEEE Transactions on Neural Networks and Learning Systems
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International Journal of Communication Networks and Distributed Systems
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International Journal of Communication Networks and Information Security
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Optical Memory and Neural Networks (Information Optics)
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International Conference on Embedded Wireless Systems and Networks
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A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing
Open Research DataNetworks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...
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Mitigating Traffic Remapping Attacks in Autonomous Multi-hop Wireless Networks
PublicationMultihop wireless networks with autonomous nodes are susceptible to selfish traffic remapping attacks (TRAs). Nodes launching TRAs leverage the underlying channel access function to receive an unduly high Quality of Service (QoS) for packet flows traversing source-to-destination routes. TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of honest nodes. Recognizing the need for providing...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Influence of User Mobility and Antenna Placement on System Loss in B2B Networks
PublicationIn this paper, the influence of user mobility and on-body antenna placement on system loss in body-to-body communications in indoor and outdoor environments and different mobility scenarios is studied, based on system loss measurements at 2.45 GHz. The novelty of this work lies on the proposal of a classification model to characterise the effect of user mobility and path visibility on system loss, allowing to identify the best...
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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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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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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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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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Routing Method for Interplanetary Satellite Communication in IoT Networks Based on IPv6
PublicationThe matter of interplanetary network (IPN) connection is a complex and sophisticated topic. Space missions are aimed inter alia at studying the outer planets of our solar system. Data transmission itself, as well as receiving data from satellites located on the borders of the solar system, was only possible thanks to the use of powerful deep space network (DSN) receivers, located in various places on the surface of the Earth. In...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...