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- Publikacje 1523 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: COGNITIVE RADIO NETWORKS
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn 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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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-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...
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Bartosz Czaplewski dr inż.
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Modulo N Backoff Scheme for effective QoS differentiation and increased bandwidth utilization in IEEE 802.11 networks
PublikacjaThe paper presents a new "modulo N" channel access scheme for wireless Local Area Networks (WLANs). The novel solution derives from the Distributed Coordination Function (DCF) of the IEEE 802.11 standard, further elaborated as Enhanced Distribution Channel Access (EDCA) by the 802.11e draft specification. The main innovation concerns improvement of the binary exponential backoff scheme used for collision avoidance in 802.11 networks....
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Assessing the time effectiveness of trust management in fully synchronised wireless sensor networks
PublikacjaThe 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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ON DYNAMICS OF ELASTIC NETWORKS WITH RIGID JUNCTIONS WITHIN NONLINEAR MICRO-POLAR ELASTICITY
PublikacjaWithin 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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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn 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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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublikacjaThis 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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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Mobility Managment Scenarios for IPv6 Networks-Proxy Mobile IP-v6Implementation Issues
PublikacjaManagement 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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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublikacjaThe 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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JOURNAL OF HIGH SPEED NETWORKS
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International Journal of Sensor Networks
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Journal of Computer Networks and Communications
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International Journal of Neural Networks
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International Journal of Security and Networks
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IEEE TRANSACTIONS ON NEURAL NETWORKS
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Sustainable Energy Grids & Networks
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ACM Transactions on Sensor Networks
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Journal of Communications and Information Networks
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International Journal of Intelligent Networks
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Online Social Networks and Media
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Maciej Sac dr inż.
OsobyMaciej Sac ukończył studia na Politechnice Gdańskiej w 2009 roku uzyskując tytuł zawodowy magistra inżyniera telekomunikacji. W roku 2022 uzyskał stopień naukowy doktora inżyniera w dziedzinie informatyka techniczna i telekomunikacja. Jego zainteresowania badawcze związane są z sieciami IP QoS, VoIP, IMS/NGN, SDN, a także usługami multimedialnymi i inżynierią ruchu telekomunikacyjnego. Obecnie jest zatrudniony na stanowisku adiunkta...
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Rearrangeable clos networks C(n,r_1,n^2-1,n,r_2) with certain restrictions for connections
PublikacjaW pracy została zaproponowana nowa metoda sprawdzania przestrajalności pól Closa dla połączeń jeden do wiele. W rozważaniach zakładamy grupowanie połączeń.In the article we will propose new method of checking rearrangeability of multicast Clos networks. In the literature there is no precise method for checking rearrangeability. We focused on three-stage Clos networks without any constraints about fan-out capability. We show the...
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REAL-TIME VOICE QUALITY MONITORING TOOL FOR VOIP OVER IPV6 NETWORKS
PublikacjaThe 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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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublikacjaThe 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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Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations
PublikacjaThe technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate...
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Primary role identification in e-mail networks using pattern subgraphs and sequence diagrams
PublikacjaSocial 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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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe 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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A hybrid-mesh solution for coverage issues in WiMAX metropolitan area networks.
PublikacjaThe new WiMAX technology offers several advantages over the currently available (GSM or UMTS-based) solutions. It is a cost effective, evolving, and robust technology providing quality of service guarantees, high reliability, wide coverage and non-line-of-sight (NLOS) transmission capabilities. All these features make it particularly suitable for densely populated urban environments. In this paper we discuss the design and implementation...
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Mitigating Traffic Remapping Attacks in Autonomous Multi-hop Wireless Networks
PublikacjaMultihop 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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Computer Networks
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe 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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Numerical Analysis of Steady Gradually Varied Flow in Open Channel Networks with Hydraulic Structures
PublikacjaIn 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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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublikacjaA 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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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward 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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Voltage and Current Unbalance Reduction in Power Networks with Distributed Generation and Electric Vehicles
PublikacjaThe 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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An Empirical System Loss Model for Body Area Networks in a Passenger Ferry Environment
PublikacjaThis 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
PublikacjaThis 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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Effects of traumatic life events, cognitive biases and variation in dopaminergic genes on psychosis proneness
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Blood pressure and low-density lipoprotein-cholesterol lowering for prevention of strokes and cognitive decline
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Compensatory functional reorganization may precede hypertension-related brain damage and cognitive decline
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Cognitive Abilities of Alzheimers Disease Transgenic Mice are Modulated by Social Context and Circadian Rhythm
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Radar time budget optimization subject to angle accuracy constraint via cognitive approach
PublikacjaThe problem of minimizing dwell time in multifunction phased array radar is considered. Target of interest is assumed to fluctuate according to a generalization of Swerling family and the parameters of fluctuation model are assumed to be known. The a'priori position of the target is uncertain. Optimization, whose variables include pulse count and array transmit beampattern, is carried out subject to achieving a desired accuracy...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting 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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Nodal cooperation equilibrium analysis in multi-hop wireless ad hoc networks with a reputation system
PublikacjaMotivated by the concerns of cooperation security, this work examines selected principles of state-of-the-art reputation systems for multi-hop ad hoc networks and their impact upon optimal strategies for rational nodes. An analytic framework is proposed and used for identification of effective cooperation-enforcement schemes. It is pointed out that optimum rather than high reputation can be expected to be sought by rational nodes.
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An Off-Body Channel Model for Body Area Networks in Indoor Environments
PublikacjaThis paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublikacjaPredicting 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...