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Search results for: dh network
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Relay-aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT utilizing ESPAR Antennas
PublicationIndustrial Internet of Things (IIoT) applicationsrequire reliable and efficient wireless communication. Assumingdense Wireless Sensor Networks (WSNs) operating in a harshenvironment, a concept of a Time Division Multiple Access(TDMA) based WSN enriched with Electronically SteerableParasitic Array Radiator (ESPAR) antennas is proposed andexamined in this work. The utilized...
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublicationWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Wideband High Efficiency Slot Array Antenna Based on Gap Waveguide Single-Layer Feeding Network
PublicationA single-layer, full metal, wideband and high efficiency slot array antenna operating in V-band (50-75 GHz) is proposed using single corporate-feeding network based on gap waveguide (GW) technology. Compared with conventional multi layered slot array antenna, the proposed antenna utilizes only one waveguide feeding layer excites the radiation slots, therefore the assembly complexity of multi-layer waveguide and manufacturing cost...
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The pollutant transport equation for a steady, gradually varied flow in an open channel network: a solution of high accuracy
PublicationW pracy przedstawiono metodę rozwiązania jednowymiarowego równania adwekcji-dyfuzji opisującego transport zanieczyszczeń w warunkach przepływu ustalonego wolnozmiennego w sieci kanałów otwartych. Zastosowano technikę dekompozycji. Zlineoryzowane równanie adwekcji-dyfuzji rozwiązano stosując całkę Duhamela, zaś równanie zacierające człon źródłowy-metodą różnic skończonych. Metoda zapewnia bardzo dużą dokładność rozwiązania nawet...
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Method to solve the non-linear systems of equations for steady gradually varied flow in open channel network.
PublicationW artykule omówiono rozwiązanie systemu równań nieliniowych opisujacych przepływ ustalony wolnozmienny w sieci kanałów otwartych. Niewiadomymi są glębokości w poszczególnych przekrojach oraz natężenia przepływów w poszczególnych gałęziach systemu. Układ musi być rozwiązywany iteracyjnie. Klasyczne metody Picarda i Newtona mogą okazać się nieskuteczne ze względu na oscylacje rozwiązania w kolejnych iteracjach i związany z tym brak...
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Safety assessment of ships in critical conditions using a knowledge-based system for design and neural network system
PublicationW pracy opisano wybrane elementy metody oceny bezpieczeństwa statków w stanie uszkodzonym, ukierunkowanej na ocenę osiągów statku i ocenę ryzyka. Metoda analizy osiągów i zachowania się statku w stanie uszkodzonym została wykorzystana do oceny charakterystyk hydromechanicznych statku uszkodzonego. Do oceny ryzyka wykorzystano elementy metodyki Formalnej Oceny Bezpieczeństwa. System ekspertowy został wykorzystany do analziy podziału...
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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublicationW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Mateusz Weiland Network Solutions
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Nexus Network Journal
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Sylwester Kaczmarek dr hab. inż.
PeopleSylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublicationThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublicationIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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Modeling of TEC Variations Based on Signals from Near Zenith GNSS Satellite Observed by Dense Regional Network
PublicationCurrently the substantial successes in high-resolution ionospheric mapping is declared in many publications. Nevertheless, up to now there are no examples of dynamic visualization of TEC disturbances on regional scale with as high resolution as tropospheric models. Over the years, ionosphere has been modeling basing on the simple assumption, that it is a thin layer, which surrounds the Earth at some arbitrary height. However, the...
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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublicationThe new adaptive method for data streams allocation in heterogeneous Wireless Body Area Networks and meas-urement equipment is presented. The results obtained using the developed method compared with the selected algorithms likely to be used in those networks. The pro-posed adaptive data streams allocation method based on radio channel parameters makes it even twice as efficient to use in terms of resources usage in a WBAN heterogeneous...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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<title>Selection of GRNN network parameters for the needs of state vector estimation of maneuvering target in ARPA devices</title>
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Radioimmunotherapy Confers Long-Term Survival to Lymphoma Patients with Acceptable Toxicity: Registry Analysis by the International Radioimmunotherapy Network
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The possibility of estimating the height of the ionospheric inhomogeneities based on TEC variations maps obtained from dense GPS network
PublicationA state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow...
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Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse
Publicationhe development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm....
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublicationThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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QUASI-DISTRIBUTED NETWORK OF LOW-COHERENCE FIBER-OPTIC FABRY-PÉROT SENSORS WITH CAVITY LENGTH-BASED ADDRESSING
PublicationDistributed measurement often relies on sensor networks. In this paper, we present the construction of low coherent fiber-optic Fabry-Pérot sensors connected into a quasi-distributed network. We discuss the mechanism of spectrum modulation in this type of sensor and the constraints of assembly of such sensors in the network. Particular attention was paid to separate the signals from individual sensors, which can be achieved by...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublicationAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Contact force network evolution in active earth pressure state of granular materials: photo‑elastic tests and DEM
PublicationArtykuł omawia ewolucję sieci sił kontaktowych w materiałach granulowanych podczas quasi-statycznego stanu aktywnego. Doświadczenia foto sprężyste zostały wykonane dla kulek szklanych. Doświadczenia zostały symulowane stosując metodę elementów dyskretnych (DEM). Model DEM prawidłowo przewidział strukturę sił kontaktowych i ich wielkość, lokalizację odkształceń oraz obszary zmian fazowych.
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Detection of roles of actors in social networks using the properties of actors' neighborhood structure.
PublicationArtykuł opisuje metodę identyfikacji ról aktorów sieci społecznej. Metoda ta może być szczególnie przydatna w sieciach społecznych, o których posiadamy ograniczoną wiedzę, głównie zawężoną do lokalnych powiązań pomiędzy aktorami. Przedstawiona w artykule metoda korzysta z grafu relacji społecznych, algorytmu identyfikacji ról oraz zbioru grafów wzorców relacji. Rozwiązanie zostało przetestowane w społeczności użytkowników serwisu...
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Simultaneous Optimization of Unicast and Anycast Flows and Replica Location in Survivable Optical Networks
PublicationDotychczasowe prace z zakresu ochrony sieci przed awariami dotyczyły przypadku transmisji unicast. W niniejszym artykule rozważamy problem ochrony transmisji anycast (jeden-do-jednego-z-wielu). Jako wariant ochrony stosujemy podejście pojedynczej ścieżki zabezpieczającej (ang. path protection), chroniącej przed awarią pojedynczego węzła.Wprowadzono nowe modele programowania całkowitoliczbowego optymalnego znajdowania tras oraz...
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Using trust management model for detection of faulty nodes in Wireless Sensor Networks
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A new role-switching mechanism optimizing the coexistence of bluetooth and wi-fi networks
PublicationPasmo ISM jest wykorzystywane przez sieci bezprzewodowe różnych technologii. Z tego powodu niezbędne jest opracowanie odpowiednich mechanizmów podnoszących efektywność pracy urządeń w środowisku współistniejących sieci. W artykule rozpatrywany jest problem wzajemnych interferencji pomiędzy nadajnikami IEEE 802.11b (Wi-Fi) oraz urządzeniami Bluetooth. Zaproponowano metodę optymalizacji określania topologii sieci BT, skutkującą...
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Router Selfishness in Community Wireless Mesh Networks: Cross-Layer Benefits and Harms
PublicationWęzły sieci mesh nie są poddane administracyjnej kontroli, zarazem nie odczuwają ograniczeń energetycznych. Są przez to skłonne do zachowań egoistycznych w warstwach 2 i 3 OSI, w szczególności w odniesieniu do protokołów MAC i routingowych. W pracy przebadano symulacyjnie wybrane aspekty środowiska mesh uzasadniające podjęcie ataków egoistycznych i zidentyfikowano trzy: gęstość rozmieszczenia i położenie routerów oraz warstwa OSI...
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Packet routing and frame length optimization in wireless mesh networks with multicast communications
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Resilience through multicast – An optimization model for multi-hop wireless sensor networks
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Distinguishable topology of the task-evoked functional genome networks in HIV-1 reservoirs
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Automated speech-based screening of depression using deep convolutional neural networks
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Application ofMsplitestimation to determine control points displacements in networks with unstable reference system
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An incentive-based forwarding protocol for mobile ad hoc networks with anonymous packets
PublicationPrzekazywanie pakietów w sieciach ad hoc z transmisją wieloetapową zależy od współpracy ruchomych terminali oraz stworzenia właściwego systemu motywacyjnego. Zaproponowany protokół wykorzystuje elementy podejścia systemu reputacyjnego dla stworzenia funkcji wypłaty w grze niekooperacyjnej, w której strategie dotyczą konfiguracji progu admisji pakietów źródłowych w stacjach. Dla symetrycznego modelu sieci pokazano, że istnieją punkty...
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An optimization approach to coexistence of Bluetooth and Wi-Fi networks operating in ISM environment
PublicationW artykule rozważono problem wzajemnych interferencji pomiedzy urządzeniami standardów IEEE 802.11b oraz Bluetooth (BT). Zaproponowano model optymalizacyjny bazujący na podejściu programowania liniowego. Uzyskano znaczącą porawę wykorzystania pasma ISM w przypadku koegzystencji sieci rozważanych standardów.
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Fast method for IEEE 802.16-2004 standard-based networks coverage measuring
PublicationThis paper presents the time and cost efficient method for measuring effective coverage of IEEE 802.16-2004 standard-based networks. This is done by performing a series of continuous measurements on the grid basis. Due to this kind of signal quality surveying, estimationof the probable coverage area can be made. It is significant that themethod is fast and is uses a standard customer equipment which makes it more accessible for...
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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublicationA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
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Assessing the time effectiveness of trust management in fully synchronised wireless sensor networks
PublicationThe paper presents the results of the time effectiveness assessment of the distributed WSN Cooperative Trust Management Method - WCT2M in a fully synchronized Wireless Sensor Network (WSN). First we introduce some basic types of synchronization patterns in WSN based on the idea of sleep scheduling. Then we explain how WCT2M works in the network applying the fully synchronized sleep scheduling pattern. Such networks were subjected...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...