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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Packet routing and frame length optimization in wireless mesh networks with multicast communications
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Resilience through multicast – An optimization model for multi-hop wireless sensor networks
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WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks
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Priority-enabled optimization of resource utilization in fault-tolerant optical transport networks.
PublicationW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów przeżywalnych sieci rozległych, które uzależnia szybkość przywracania ciągłości połączenia od klasy usługi. Wykazano, iż proponowana metoda nie powoduje wydłużania ścieżek zabezpieczających (w przypadku usług w wymaganej wysokiej jakości obsługi) lub czyni to w sposób minimalny (dla pozostały usług). Ze względu na fakt, że zadanie znalezienia ścieżek aktywnych...
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An incentive-based forwarding protocol for mobile ad hoc networks with anonymous packets
PublicationPrzekazywanie pakietów w sieciach ad hoc z transmisją wieloetapową zależy od współpracy ruchomych terminali oraz stworzenia właściwego systemu motywacyjnego. Zaproponowany protokół wykorzystuje elementy podejścia systemu reputacyjnego dla stworzenia funkcji wypłaty w grze niekooperacyjnej, w której strategie dotyczą konfiguracji progu admisji pakietów źródłowych w stacjach. Dla symetrycznego modelu sieci pokazano, że istnieją punkty...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Integrated Control in High-Speed Networks Using Constrained Model Predictive Control
PublicationThis paper studies congestion control in high-speed communication networks using Model Predictive Control (MPC). Network traffic is assumed to consist of best-effort and priority traffic sources. An integrated controller consisting of two control parts is designed. The controller calculates the capacity for priority sources and the input rate of best-effort sources. MPC is desirable as it can take into account the constraints on...
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REAL-TIME VOICE QUALITY MONITORING TOOL FOR VOIP OVER IPV6 NETWORKS
PublicationThe primary aim of this paper is to present a new application which is at this moment the only open source real-time VoIP quality monitoring tool that supports IPv6 networks. The application can keep VoIP system administrators provided at any time with up-to-date voice quality information. Multiple quality scores that are automatically obtained throughout each call reflect influence of variable packet losses and delays on voice...
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Methods for physical impairment constrained routing with selected protection in all-optical networks
PublicationIn this paper, we investigate the problem of survivable all-optical routing in WDM networks with physical impairments. One of the recent key issues in survivable optical network design refers to maximization of the ratio of routeable demands while keeping the overall network cost low. In WDM networks, this goal can be achieved by routing as many demands in all-optical way as possible. Based on the latest technical trends driven...
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Assessing the time effectiveness of trust management in fully synchronised wireless sensor networks
PublicationThe paper presents the results of the time effectiveness assessment of the distributed WSN Cooperative Trust Management Method - WCT2M in a fully synchronized Wireless Sensor Network (WSN). First we introduce some basic types of synchronization patterns in WSN based on the idea of sleep scheduling. Then we explain how WCT2M works in the network applying the fully synchronized sleep scheduling pattern. Such networks were subjected...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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On the fast BSS transition algorithms in the IEEE 802.11r local area wireless networks
PublicationHandover performance is critical to support multimedia services that are becoming increasingly available over the wireless devices. The high transition delay can be unaccepted for such services or can be a source of disruption on the session. On the other side, IEEE 802.11 standard is being extended with new functionalities. Security and QoS features, included in recent IEEE 802.11-2007 standard, add management frames that are...
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Mobility Managment Scenarios for IPv6 Networks-Proxy Mobile IP-v6Implementation Issues
PublicationManagement of user at the network layer plays an important role in efficient network operation. In the paper, authors' implementation of one of network-based mobility management models, namely Proxy Mobile IPv6, is presented and tested in a number of networking topologies and communication scenarios. The proposed implementation covers PMPIv6 functionality with optional security extensions (use of Diameter protocol) and handover...
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Using trust management model for detection of faulty nodes in Wireless Sensor Networks
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A new role-switching mechanism optimizing the coexistence of bluetooth and wi-fi networks
PublicationPasmo ISM jest wykorzystywane przez sieci bezprzewodowe różnych technologii. Z tego powodu niezbędne jest opracowanie odpowiednich mechanizmów podnoszących efektywność pracy urządeń w środowisku współistniejących sieci. W artykule rozpatrywany jest problem wzajemnych interferencji pomiędzy nadajnikami IEEE 802.11b (Wi-Fi) oraz urządzeniami Bluetooth. Zaproponowano metodę optymalizacji określania topologii sieci BT, skutkującą...
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Intelligent acquisition of audio signals, employing neutral networks and rough set algorithms
PublicationAlgorytmy oparte na sztucznych sieciach neuronowych i metodzie zbiorówprzybliżonych zostały zastosowane do lokalizacji sygnałów fonicznych obar-czonych pasożytniczym szumem i rewerberacjami. Informacja o kierunku napły-wania dźwięku była uzyskiwana na wyjściach tych algorytmów na podstawie re-prezentacji parametrycznej. Przedstawiono wyniki eksperymentalne i przepro-wadzono ich dyskusję.
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublicationSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Voltage and Current Unbalance Reduction in Power Networks with Distributed Generation and Electric Vehicles
PublicationThe current development of prosumer microsources and the expected spread of electric vehicles may cause the appearance of significant current and voltage unbalance in low-voltage (LV) networks. This unbalance, which is an unfavorable phenomenon, may occur when using single-phase photovoltaic (PV) microsources and single-phase home chargers for electric vehicles. This paper presents a proposal for the symmetrization of the LV network...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublicationNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Fast Fading Characterization for Body Area Networks in Circular Metallic Indoor Environments
PublicationWith the increasing development of 5G and Body Area Network based systems being implemented in unusual environments, propagation inside metallic structures is a key aspect to characterize propagation effects inside ships and other similar environments, mostly composed of metallic walls. In this paper, indoor propagation inside circular metallic structures is addressed and fast fading statistical distributions parameters are obtained...
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublicationForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublicationCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublicationA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
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Service-based Resilience via Shared Protection in Mission-critical Embedded Networks
PublicationMission-critical networks, which for example can be found in autonomous cars and avionics, are complex systems with a multitude of interconnected embedded nodes and various service demands. Their resilience against failures and attacks is a crucial property and has to be already considered in their design phase. In this paper, we introduce a novel approach for optimal joint service allocation and routing, leveraging virtualized...
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A Wideband Channel Model for Body Area Networks in Circular Metallic Indoor Environments
PublicationIn this paper, the wideband characterization of the propagation channel in circular metallic indoor environments is addressed, regarding Body Area Networks and 5G small cells, an analytical model for the dependence of the mean delay and the average delay spread on the circle radius, the working frequency and the distance between the transmitter and the receiver being proposed. The derivation of the model is initially done analytically,...
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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublicationThe slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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ON DYNAMICS OF ELASTIC NETWORKS WITH RIGID JUNCTIONS WITHIN NONLINEAR MICRO-POLAR ELASTICITY
PublicationWithin the nonlinear micropolar elasticity we discuss effective dynamic (kinetic) properties of elastic networks with rigid joints. The model of a hyperelastic micropolar continuum is based on two constitutive relations, i.e., static and kinetic ones. They introduce a strain energy density and a kinetic energy density, respectively. Here we consider a three-dimensional elastic network made of three families of elastic fibers connected...
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The Analysis of Cross-Polarisation Discrimination for Body Area Networks in Cylindrical Metallic Environment
PublicationThe analysis of cross-polarisation discrimination for Body Area Networks in an untypical environment of cylindrical metallic room has been performed in the paper. This analysis was done based on the measurements carried out for dynamic narrowband off-body channels operating at the frequency of 2.45 GHz. The results have shown that there is a strong dependence of the depolarisation effect on the existence of direct component in...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Router Selfishness in Community Wireless Mesh Networks: Cross-Layer Benefits and Harms
PublicationWęzły sieci mesh nie są poddane administracyjnej kontroli, zarazem nie odczuwają ograniczeń energetycznych. Są przez to skłonne do zachowań egoistycznych w warstwach 2 i 3 OSI, w szczególności w odniesieniu do protokołów MAC i routingowych. W pracy przebadano symulacyjnie wybrane aspekty środowiska mesh uzasadniające podjęcie ataków egoistycznych i zidentyfikowano trzy: gęstość rozmieszczenia i położenie routerów oraz warstwa OSI...
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
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Towards the boundary between easy and hard control problems in multicast Clos networks
PublicationIn this article we study 3-stage Clos networks with multicast calls in general and 2-cast calls, in particular. We investigate various sizes of input and output switches and discuss some routing problems involved in blocking states. To express our results in a formal way we introduce a model of hypergraph edge-coloring. A new class of bipartite hypergraphs corresponding to Clos networks is studied. We identify some polynomially...
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Selfish Attacks in Two-Hop IEEE 802.11 Relay Networks: Impact and Countermeasures
PublicationIn IEEE 802.11 networks, selfish stations can pursue a better quality of service through selfish MAC-layer attacks. Such attacks are easy to perform, secure routing protocols do not prevent them, and their detection may be complex. Two-hop relay topologies allow a new angle of attack: a selfish relay can tamper with either source traffic, transit traffic, or both. We consider the applicability of selfish attacks and their variants...
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An Empirical System Loss Model for Body Area Networks in a Passenger Ferry Environment
PublicationThis paper presents a general empirical system loss model for estimating propagation loss in Body Area Networks in off-body communications at 2.45 GHz in a passenger ferry environment. The model is based on measurements, which were carried out in dynamic scenarios in the discotheque passenger ferry environment. The model consists of three components: mean system loss, attenuation resulting from the variable antenna position on...
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An Empirical System Loss Model for Body Area Networks in a Passenger Ferry Environment
PublicationThis paper presents a general empirical system loss model for estimating propagation loss in Body Area Networks in off-body communications at 2.45 GHz in a passenger ferry environment. The model is based on measurements, which were carried out in dynamic scenarios in the discotheque passenger ferry environment. The model consists of three components: mean system loss, attenuation resulting from the variable antenna position on...
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Improving voltage levels in low-voltage networks with distributed generation – case study
PublicationThe use of distributed generation in low-voltage networks may cause the voltage variation in them, within the wide range. In unfavourable circumstances, the voltage may reach unacceptable values. The paper presents the effect of distributed generation on voltage levels in a selected low-voltage rural distribution network in Poland. An analysis of possible methods for improving voltage levels in this network is conducted. The most...
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory
PublicationMemory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Comparison of Impedance-Source Networks for Two and Multilevel Buck–Boost Inverter Applications
Publicationmpedance-source networks are an increasingly popular solution in power converter applications, especially in single-stage buck-boost power conversion to avoid additional front-end dc-dc power converters. In the survey papers published, no analytical comparisons of different topologies have been described, which makes it difficult to choose the best option. Thus, the aim of this paper is to present a comprehensive analytical comparison...
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A survey of strategies for communication networks to protect against large-scale natural disasters
PublicationRecent natural disasters have revealed that emergency networks presently cannot disseminate the necessary disaster information, making it difficult to deploy and coordinate relief operations. These disasters have reinforced the knowledge that telecommunication networks constitute a critical infrastructure of our society, and the urgency in establishing protection mechanisms against disaster-based disruptions. Hence, it is important...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublicationTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...