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Search results for: communiation networks
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Using LSTM networks to predict engine condition on large scale data processing framework
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Capacity efficient shared protection and fast restoration scheme in self-configured optical networks
PublicationW artykule zaproponowano nową koncepcję optymalizacji rozdziału zasobów dla przeżywalnych sieci rozległych, która gwarantuje szybkie odtwarzanie usług po wystąpieniu awarii. Wykazano, iż proponowany algorytm, wykorzystujący ideę wierzchołkowego kolorowania grafów, nie powoduje wydłużania ścieżek zabezpieczających - zjawiska charakterystycznego dla powszechnie stosowanych algorytmów optymalizacji. Udowodniono, iż powyższa cecha...
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Efficiency of service recovery in scale-free optical networks under multiple node failures
PublicationIn this paper we examine the properties of scale-free networks in case of simultaneous failures of two networknodes. Survivability assumptions are as follows: end-to-end path protection with two node-disjoint backup pathsfor each working path. We investigate three models of scale-free networks generation: IG, PFP and BA.Simulations were to measure the lengths of active and backup paths and the values of service recovery time.We...
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Primary role identification in e-mail networks using pattern subgraphs and sequence diagrams
PublicationSocial networks often forms very complex structures that additionally change over time. Description of actors' roles in such structures requires to take into account this dynamics reflecting behavioral characteristics of the actors. A role can be defined as a sequence of different types of activities. Various types of activities are modeled by pattern subgraphs, whereas sequences of these activities are modeled by sequence diagrams....
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INFLUENCE OF A VERTEX REMOVING ON THE CONNECTED DOMINATION NUMBER – APPLICATION TO AD-HOC WIRELESS NETWORKS
PublicationA minimum connected dominating set (MCDS) can be used as virtual backbone in ad-hoc wireless networks for efficient routing and broadcasting tasks. To find the MCDS is an NP- complete problem even in unit disk graphs. Many suboptimal algorithms are reported in the literature to find the MCDS using local information instead to use global network knowledge, achieving an important reduction in complexity. Since a wireless network...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Performance Evaluation of GAM in Off-Body Path Loss Modelling for Body Area Networks
PublicationThis paper addresses the performance evaluation of an off-body path loss model, based on measurements at 2.45 GHz, which has been developed with the use of the Generalised Additive Model, allowing to model a non-linear dependence on different predictor variables. The model formulates path loss as a function of distance, antennas’ heights, antenna orientation angle and polarisation, results showing that performance is very sensitive...
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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublicationThe exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublicationThis work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry...
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New Alternative Passive Networks to Improve the Range Output Voltage Regulation of the PWM Inverters
PublicationThis paper presents different topologies of buck-boost converters with passive input networks that have alternative topologies; this is known in the literature as a Z-source inverter. Alternative passive networks were named by the authors as T-inverters; these improve output voltage regulation of the PWM inverters. T-inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage...
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The influence of azide and imidazole on the properties of Mn- and Cd-based networks: conductivity and nonlinear phenomena
PublicationWe report a study on a family of four new Mn- and Cd-azide-imidazolate-based compounds with various crystal architectures. Notably, three of these compounds display noncentrosymmetric crystal arrangements at room temperature, a rare phenomenon in hybrid organic–inorganic materials. Both nonlinear optical (NLO) and electrical phenomena in these compounds are observed. The NLO processes include second and third harmonic generation,...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublicationHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Dempster-shafer theory-based trust and selfishness evaluation in mobile ad hoc networks
PublicationThe paper addresses the problem of selfishness detec-tion in mobile ad hoc networks. It describes an approach based on Dempster-Shafer theory of evidence. Special attention is paid to trust evaluation and using it as a metric for coping with (weighted) recommendations from third-party nodes. Efficiency and robustness of the pre-sented solution is discussed with an emphasis on resil-iency to false recommendations.
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Numerical Analysis of Steady Gradually Varied Flow in Open Channel Networks with Hydraulic Structures
PublicationIn this paper, a method for numerical analysis of steady gradually varied fl ow in channel networks with hydraulic structures is considered. For this purpose, a boundary problem for the system of ordinary differential equations consisting of energy equation and mass conservation equations is formulated. The boundary problem is solved using fi nite difference technique which leads to the system of non-linear algebraic equations....
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Inter-governmental Collaborative Networks for Digital Government Innovation Transfer -Structure, Membership, Operation
PublicationDigital government refers to the transformation of government organizations and their relationships with citizens, business and each other through digital technology. It entails digital innovation in processes, services, organizations, policies, etc. which are increasingly developed and tested in one country and transferred, after adaptation, to other countries. The process of innovation transfer and the underlying information...
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublicationThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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A Reputation Scheme to Discourage Selfish QoS Manipulation in Two-Hop Wireless Relay Networks
PublicationIn wireless networks, stations can improve their received quality of service (QoS) by handling packets of source flows with higher priority. Additionally, in cooperative relay networks, the relays can handle transit flows with lower priority. We use game theory to model a two-hop relay network where each of the two involved stations can commit such selfish QoS manipulation. We design and evaluate a reputation-based incentive scheme...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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High-Power Jamming Attack Mitigation Techniques in Spectrally-Spatially Flexible Optical Networks
PublicationThis work presents efficient connection provisioning techniques mitigating high-power jamming attacks in spectrally-spatially flexible optical networks (SS-FONs) utilizing multicore fibers. High-power jamming attacks are modeled based on their impact on the lightpaths’ quality of transmission (QoT) through inter-core crosstalk. Based on a desired threshold on a lightpath’s QoT, the modulation format used, the length of the path,...
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublicationThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublicationCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublicationIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublicationIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Development of cooperation in localized cooperation networks: A comparative study of cluster organizations and technology parks
PublicationThe main aim of the paper is to analyze the level of development of cooperative relationships in localized cooperation networks – among enterprises associated in cluster organizations and park tenants. The author reports the findings from the quantitative study carried out in the selected cluster organizations and technology parks functioning in Poland. The basic method of data collection was a survey questionnaire. The research...
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Highlights from RNDM 2018 – 10th Anniversary Workshop on Resilient Networks Design and Modeling
PublicationArtykuł prezentujący relację z workshopu RNDM 2018
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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On reducing the value of aggregate restoration time when assuring survivability in scale-free networks.
PublicationReferat dotyczy zapewniania przeżywalności połączeń w rozległych sieciach bezskalowych. Zaproponowano metrykę pozwalającą omijać centra sieci, a tym samym zmniejszać ilość połączeń wymagających odtwarzania na skutek awarii węzła. Wyniki dla sieci bezskalowych porównywane są z wynikami dla sieci losowych. Uzyskane wyniki potwierdzają efektywność metryki w sieciach bezskalowych.
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublicationArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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Disciplines and measures of information resilience
PublicationCommunication networks have become a fundamental part of many critical infrastructures, playing an important role in information delivery in various failure scenarios triggered e.g., by forces of nature (including earthquakes, tornados, fires, etc.), technology-related disasters (for instance due to power blackout), or malicious human activities. A number of recovery schemes have been defined in the context of network resilience...
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A taxonomy of challenges to resilient message dissemination in VANETs
PublicationInter-vehicular communications is seen as a promising solution to a number of issues related with public road safety, road congestion management, and infotainment. However, Vehicular Ad-hoc NETworks (VANETs) characterized by high mobility of vehicles and facing a number of other issues related with high frequency wireless communications and network disconnections, encounter major challenges related with reliability of message delivery....
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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An Innovative Antenna Array with High Inter Element Isolation for Sub-6 GHz 5G MIMO Communication Systems
PublicationA novel technique is shown to improve the isolation between radiators in antenna arrays. The proposed technique suppresses the surface-wave propagation and reduces substrate loss thereby enhancing the overall performance of the array. This is achieved without affecting the antenna’s footprint. The proposed approach is demonstrated on a four-element array for 5G MIMO applications. Each radiating element in the array is constituted...
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Quality Evaluation of Speech Transmission via Two-way BPL-PLC Voice Communication System in an Underground Mine
PublicationIn order to design a stable and reliable voice communication system, it is essential to know how many resources are necessary for conveying quality content. These parameters may include objective quality of service (QoS) metrics, such as: available bandwidth, bit error rate (BER), delay, latency as well as subjective quality of experience (QoE) related to user expectations. QoE is expressed as clarity of speech and the ability...
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Measuring the effectiveness of digital communication - social media performance: an example of the role played by AI-assisted tools at a university
PublicationThe aim of the article is to show the role played by AI-powered tools in measuring the effectiveness of digital communication in social media using a university case study. Therefore, a research problem was formulated to identify the metrics (KPIs) used to measure the effectiveness – non-financial outcomes – of digital social media communication at the university using AI tools. The literature review on the role of AI in digital...
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Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set
PublicationThis paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time...
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What do hashtags afford in digital fashion communication? An exploratory study on Gucci-related hashtags on Twitter and Instagram.
PublicationBeing enmeshed in a digital environment, we daily produce internet-mediated texts – encompassing several different semiotic codes – accessible on a global scale. Posts on different networks usually contain hashtags, which can be understood as affordances or behavior opportunities. These affordances allow specific actions both from the part of the writer and the reader. They can also be “behavior triggers,” which invite certain...
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Characterization of Slow and Fast Fading in Off-Body Communication at 2.45 GHz with Space Diversity Scheme in an Indoor Environment
PublicationThe characterization of slow and fast fading in wireless body area networks with space diversity scheme has been presented. The analysis, based on the measurements at 2.45 GHz in an indoor environment, has shown that for all investigated configurations of receiving wearable antennas, the correlation coefficient values of the received signals’ parameters are below the assumed value of 0.5, being close to zero for the vast majority...