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Search results for: NETWORKED WORLD
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A new approach to provide the differentiated levels of network survivability under a double node failure
PublicationW artykule zaproponowano klasową metodę ochrony strumieni ruchu w sieciach WDM zapewniającą szybkie odtwarzanie połączeń w sytuacji jednoczesnej awarii jej dwóch elementów. Szczególny nacisk położono na zagadnienie zapewnienia zróżnicowanych poziomów przeżywalności w celu ich lepszego dopasowania do zróżnicowanych wymagań użytkowników. Pokazano, że w celu zapenienia ochrony przed awarią dwóch elementów, wymagania dotyczące przepustowości...
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Comparative Evaluation of Multicoil Inductive Power Transfer Approaches Based on Z-source Network
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Novel Inductive Power Transfer Approach Based on Z-Source Network with Compensation Circuit
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The Influence of the Soil Environment on the Corrosivity of Failure Infrastructure - Case Study of the Exemplary Water Network
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Fast synchronous distribution network of data streams for RPC Muon Trigger in CMS experiment
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<title>FPGA-based modular configurable controller with fast synchronous optical network</title>
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Transfer of charging information between exchanges of different network operators in multi-provider environment.
PublicationW pracy przedstawiono różne konfiguracje systemów taryfikacji i zaliczania w środowisku zdemonopolizowanym. Przeanalizowano różne opcje przepływu danych w takim środowisku i omówiono rozszerzenie sygnalizacji SS7, która jest opracowana przez ETSI i wykorzystywana dla aplikacji zaliczania.
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Neural network based control system architecture proposal for underwatership hull cleaning robot.
PublicationPrzedstawiono model matematyczny podwodnej głowicy roboczej, oraz określono metodę jej pozycjonowania i orientacji w lokalnym środowisku. Zaproponowano architekturę układu sterowania, opartego na bazie sieci neuronowych, za pomocą którego można sterować podwodnym robotem, przeznaczonym do czyszczenia burt statku.
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Analysis of energy recovery from surplus water pressure of municipal heat distribution network
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublicationThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Analytical Traffic Model for a Multidomain IMS/NGN Network Including Service and Transport Stratum
PublicationThis paper addresses the problem of modelling call processing performance (CPP) in a multidomain Next Generation Network (NGN) architecture including the elements of the IP Multimedia Subsystem (IMS) in service stratum and based on the Multiprotocol Label Switching (MPLS) technology in transport stratum. An analytical traffic model for such an architecture is proposed by integrating the formerly implemented submodels of service...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublicationCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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APPLICATION OF STATISTICAL FEATURES AND MULTILAYER NEURAL NETWORK TO AUTOMATIC DIAGNOSIS OF ARRHYTHMIA BY ECG SIGNALS
PublicationAbnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregu- larity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Musical instrument sound separation methods supported by artificial nueural network decision system
PublicationRozprawa doktorska (27 czerwica 2006).Celem prowadzonych prac badawczych było opracowanie algorytmów separacji dźwięków instrumentów muzycznych. Dodatkowo dobrano zestaw parametrów tak aby możliwe było wytrenowanie sztucznej sieci neuronowej w celu automatycznego rozpoznawania odseparowanych sygnałów. Zaproponowano również aby algorytm decyzyjny odpowiedzialny za klasyfikacje dźwięków pełnił funkcję automatycznej metody oceny algorytmów...
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An application of neural network for Structural Health Monitoring of an adaptive wing with an array of FBG sensors
PublicationW pracy przedstwiono możliwości zastoswania sieci czujników FBG i sztucznych sieci neuronowych do detekcji uszkodzeń w poszyciu adaptacyjnego skrzydła.
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Operation of trolleybus transport in Portugal. Revitalization of trolleybus network in Coimbra and development plans in Amadora
PublicationW artykule opisano sytuację komunikacji trolejbusowej w Portugalii.
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Linux scheduler improvement for time demanding network applications, running on Communication Platform Systems
PublicationCommunication Platform Systems as ex. ATCA standard blades located in standardized chassis provides high level communication services between system peripherals. Each ATCA blade brings dedicated functionality to the system but can as well exist as separated host responsible for servicing set of task. According to platform philosophy these parts of system can be quite independent against another solutions provided by competitors....
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Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network
PublicationWe analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative...
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Analysis of electromagnetic disturbances in DC network of grid connected building-integrated photovoltaic system
PublicationThis paper focuses on conducted electromagnetic interference (EMI) emissions and propagation in the DC network of grid connected building integrated photovoltaic (PV) system. The investigated PV system, consists of ten solar panels, cabling and the grid-connected one phase inverter. The EMI simulation model of the real PV system has been developed with the aid of impedance analyzer measurements of solar panels and the DC network...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Development of Intelligent Control for Annealing Unit to Ensure the Minimization of Retroactive Effects on the Supply Network
PublicationResearch conducted by our team focused on the development of a complete annealing unit, using modern technologies and components, such as a programmable logic controller, an industrial computer and microcontrollers, ensuring an intelligent way to control power semiconductor elements (SSR relays), with regard to minimizing retroactive effects on the supply network. This modern configuration offers a number of new possibilities of...
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Tacit Knowledge Sharing and Value Creation in the Network Economy: Socially Driven Evolution of Business
PublicationKey factors which affect competitive advantage in the network economy are innovation, relationships, cooperation, and knowledge. Sharing knowledge is not easy. Companies find it problematic. Presented studies show that the essence of the value creation today is not in sharing explicit but rather tacit knowledge, which is a source of creativity and innovation. Delivering value through knowledge does not only require efficient Transactive...
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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublicationThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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A strategy for GPS data processing in a precise local network during high solar activity
PublicationThis paper presents the analyses connected with reduction of errors from ionospheric refraction using GPS data from local satellite networks. This is particularly essential during rising solar activity. The Bernese GPS Software v. 4.2 was used, as an analytical tool. The test data included measurements from a geodynamic network SUDETES situated in the Sudety Mountains across the border between the Czech Republic and Poland. A local...
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublicationThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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Integration and Visualization of the Results of Hydrodynamic Models in the Maritime Network-Centric GIS of Gulf of Gdansk
PublicationEnsuring of security in the coastal area makes on a seaside countries research in the field of infrastructure spatial information of environmental data. The paper presents the results of work on the construction of this infrastructure by integrating electronic navigational chart with ortophotomaps of coastal areas as well as numerical data from weather and hydrodynamic models. Paper focuses on a problems associated with creating...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublicationAbstract—In the era of collecting large amounts of tissue materials, assisting the work of histopathologists with various electronic and information IT tools is an undeniable fact. The traditional interaction between a human pathologist and the glass slide is changing to interaction between an AI pathologist with a whole slide images. One of the important tasks is the segmentation of objects (e.g. cells) in such images. In this...
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Comparative Evaluation of Multicoil Inductive Power Transfer Approaches Based on Z-source Network
PublicationThis paper describes comparative evaluation between wireless power transfer topologies with utilization of Z-source network. Paper describes components calculation method. List of open-loop, close-loop simulations were conducted to compare both topologies. Spectrum of signals is also researched.
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Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
PublicationThis paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne 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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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublicationThe 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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Risk Modelling with Bayesian Networks - Case Study: Construction of Tunnel under the Dead Vistula River in Gdansk
PublicationThe 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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Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
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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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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Modulo N Backoff Scheme for effective QoS differentiation and increased bandwidth utilization in IEEE 802.11 networks
PublicationThe 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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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferry Environment
PublicationIn 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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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment
PublicationIn 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...