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Wyniki wyszukiwania dla: POWER NETWORKS
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A novel genetic approach to provide differentiated levels of service resilience in IP-MPLS/WDM networks
PublikacjaThis paper introduces a novel class-based method of survivable routing for connection-oriented IP-MPLS/WDM networks, called MLS-GEN-H. The algorithm is designed to provide differentiated levels of service survivability in order to respond to varying requirements of end-users. It divides the complex problem of survivable routing in IP-MPLS/WDM networks into two subproblems, one for each network layer, which enables finding the...
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Long-distance quantum communication over noisy networks without long-time quantum memory
PublikacjaThe problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008)] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
PublikacjaMolecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus,the inter- and...
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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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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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Optimum Choice of Randomly Oriented Carbon Nanotube Networks for UV-Assisted Gas Sensing Applications
PublikacjaWe investigated the noise and photoresponse characteristics of various optical transparencies of nanotube networks to identify an optimal randomly oriented network of carbon nanotube (CNT)-based devices for UV-assisted gas sensing applications. Our investigation reveals that all of the studied devices demonstrate negative photoconductivity upon exposure to UV light. Our studies confirm the effect of UV irradiation on the electrical...
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Application of Bayesian Networks in risk diagnostics arising from the degree of urban regeneration area degradation
PublikacjaUrban regeneration as a complex project, generates many extremely specific threats affecting the increase of investment risk. Its unique nature causes that probability parameter, normally applied in the process of risk quantification, is extremely difficult to estimate. Due to lack of historical data urban regeneration related activities are therefore associated with uncertainty. According to the authors, a useful tool for resolving...
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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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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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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublikacjaThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublikacjaA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublikacjaSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Vision-based parking lot occupancy evaluation system using 2D separable discrete wavelet transform
PublikacjaA simple system for rough estimation of the occupancy of an ad-hoc organized parking lot is presented. A reasonably simple microprocessor hardware with a low resolution monochrome video camera observing the parking lot from the location high above the parking surface is capable of running the proposed 2-D separable discrete wavelet transform (DWT)-based algorithm, reporting the percentage of the observed parking area occupied by...
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Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System
PublikacjaBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...
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Disciplines and measures of information resilience
PublikacjaCommunication 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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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Selfishness Detection in Mobile Ad Hoc Networks: How Dissemination of Indirect Information Turns into Strategic Issue
PublikacjaDla środowiska sieci mobilnej ad hoc przedyskutowano wymienność pomiędzy wydatkiem energetycznym węzła egoistycznego a obniżaniem jego metryki reputacyjnej. Badania symulacyjne wskazują, że atakom polegającym na selektywnym usuwaniu pakietów można przeciwdziałać poprzez datacentryczny system reputacyjny bazujący na potwierdzeniach końcowych, który nakazuje jednakowo uaktualniać metryki reputacyjne dla wszystkich węzłów na źle zachowującej...
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Social networks as a context for small business? A new look at an enterprise in the context of a smallness and newness liability syndrome
PublikacjaIn this paper we aim to propose and outline key ingredients to a small enterprise success, emerging from the social capital of small business owner-managers and their business networks. We employ resource based view of an organization as well as an embeddedness perspective along with new approach transaction costs to outline the pillars of an advantage of a small business entity. The analysis of survey data leads us to conclusion,...
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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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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Fast service restoration under shared protection at lightpath level in survivable WDM mesh grooming networks
PublikacjaW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów w przeżywalnych sieciach optycznych z agregacją strumieni ruchu. Zaproponowana metoda bazuje na wierzchołkowym kolorowaniu grafu konfliktów. Jest pierwszym podejściem, dedykowanym sieciom optycznym z agregację strumieni ruchu z pełną zdolnością do konwersji długości fal, która nie powoduje wydłużenia ściezek zabezpieczjących, a więc zapewnia szybkie odtwarzanie...
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Probability estimation of the city’s energy efficiency improvement as a result of using the phase change materials in heating networks
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
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Fabrication of toughened plastic using styrene butadiene rubber-poly (methyl methacrylate) interpenetrating polymer networks
PublikacjaA standard set of interpenetrating polymeric networks (IPNs) has been contrived using an elastomerstyrene butadiene rubber and a thermoplastic poly (methyl methacrylate) through sequential polymerization protocol. This low-cost material can be hopefully engaged as a toughened plastic with cocontinuous morphology. Different morphological protocols including Raman imaging are effectively utilized to envisage the effect of blend ratio...
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublikacjaFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Risk Modelling with Bayesian Networks - Case Study: Construction of Tunnel under the Dead Vistula River in Gdansk
PublikacjaThe process of decision-making in public procurement of construction projects during the preparation and implementation phases ought to be supported by risk identification, assessment, and management. In risk assessment one has to take into account factors that lead to risk events (background info), as well as the information about the risk symptoms (monitoring info). Typically once the risks have been assessed a decision-maker...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferry Environment
PublikacjaIn the article an off-body narrowband and ultra-wide band channel model for Body Area Networks in a ferry environment is described. A mobile, heterogeneous measurement stand, that consists of three types of devices: miniaturized mobile nodes, stationary reference nodes and a data acquisition server was developed. A detailed analysis of both radio channels parameters in untypical indoor environment was carried out. An analysis of...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment
PublikacjaIn the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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KRYTERIA STOSOWANE W WIELOKRYTERIALNYM PLANOWANIU ROZWOJU SYSTEMU ELEKTROENERGETYCZNEGO
PublikacjaProblematyka planowania rozwoju systemów elektroenergetycznych jest zagadnieniem często podejmowanym w badaniach optymalizacyjnych ze względu na wagę i zasięg problemu. Rozwój techniki komputerowej pozwolił na połączenie tematyki optymalizacji struktury wytwarzania i planowania sieci elektroenergetycznej, co jest zagadnieniem wielowątkowym oraz wielowymiarowym. W prezentowanym artykule przedstawiono kryteria stosowane w analizach...
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Resource constrained neural network training
PublikacjaModern 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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Workshop on Power Aware Computing and Systems
Konferencje -
Formal Power Series and Algebraic Combinatorics
Konferencje -
Marek Wójcikowski dr hab. inż.
OsobyMarek Wójcikowski ukończył w 1993 r. Wydział Elektroniki Politechniki Gdańskiej, specjalność układy elektroniczne. W 2002 r. uzyskał stopień doktora w dziedzinie elektroniki, a w 2016 r. uzyskał stopień doktora habilitowanego na Wydziale Elektroniki Telekomunikacji i Informatyki Politechniki Gdańskiej. Od początku kariery jest związany z Politechniką Gdańską: najpierw jako asystent (lata 1994–2002), a następnie jako adiunkt (od...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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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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Service time distribution influence on end-to-end call setup delay calculation in networks with Session Initiation Protocol
PublikacjaThe most important GoS parameter for networks with SIP protocol is end-to-end call setup delay. So far there were no coherent models allowing calculation of these parameters for networks with SIP protocol. Few models were developed but they are insufficient. In the paper we propose model which allows end-to-end call setup delay calculation for networks with SIP protocol. The model is using chain of M/G/1/K models and is applicable...