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Search results for: CARRIER%20NETWORKS
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Influence of User Mobility and Antenna Placement on System Loss in B2B Networks
PublicationIn this paper, the influence of user mobility and on-body antenna placement on system loss in body-to-body communications in indoor and outdoor environments and different mobility scenarios is studied, based on system loss measurements at 2.45 GHz. The novelty of this work lies on the proposal of a classification model to characterise the effect of user mobility and path visibility on system loss, allowing to identify the best...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Cost-Efficient Optical Fronthaul Architectures for 5G and Future 6G Networks
PublicationFifth-generation and Beyond (5GB) wireless networks have introduced new centralized architectures such as cloud radio access network (CRAN), which necessitate extremely high-capacity low latency Fronthaul (FH). CRAN has many advantageous features in terms of cost reduction, performance enhancement, ease of deployment, and centralization of network management. Nevertheless, designing and deploying a cost-efficient FH is still a...
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Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks
PublicationThe rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs....
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System Loss Model for Body-to-Body Networks in Indoor and Outdoor Environments
PublicationA system loss model for body-to-body networks in indoor and outdoor environments is proposed in this paper, based on measurements taken at 2.45 GHz. The influence of the type of environment, antenna visibility and user mobility on model parameters has been investigated. A significant impact of mutual antennas’ placement and their visibility is shown. The proposed model fits well to empirical data, with the average root mean square...
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Diffusion equations with spatially dependent coefficients and fractal Cauer-type networks
PublicationIn this article, we formulate and solve the representation problem for diffusion equations: giving a discretization of the Laplace transform of a diffusion equation under a space discretization over a space scale determined by an increment h > 0, can we construct a continuous in h family of Cauer ladder networks whose constitutive equations match for all h > 0 the discretization. It is proved that for a finite differences discretization...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Routing Method for Interplanetary Satellite Communication in IoT Networks Based on IPv6
PublicationThe matter of interplanetary network (IPN) connection is a complex and sophisticated topic. Space missions are aimed inter alia at studying the outer planets of our solar system. Data transmission itself, as well as receiving data from satellites located on the borders of the solar system, was only possible thanks to the use of powerful deep space network (DSN) receivers, located in various places on the surface of the Earth. In...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublicationIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Local variance factors in deformation analysis of non-homogenous monitoring networks
PublicationThis paper proposes a modification of the classical deformation analysis algorithm for non-homogeneous (e.g. linear-angular) monitoring networks. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal monitoring network. The obtained results confirm the usefulness of the proposed solution.
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Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks
PublicationThe aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublicationIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting 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...
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Mitigating Traffic Remapping Attacks in Autonomous Multi-hop Wireless Networks
PublicationMultihop 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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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting 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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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Theoretical modelling of efficient fire safety water networks by certified domination
PublicationThis paper explores a new way of designing water supply networks for fire safety using ideas from graph theory, focusing on a method called certified domination. Ensuring a good water supply is crucial for fire safety in communities, this study looks at the rules and problems in Poland for how much water is needed to fight fires in different areas and how this can be achieved at a lowest possible cost. We present a way to plan...
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Self-healing ATM networks based on preplanned restoration of virtual paths
PublicationW pracy omówiono klasyfikację metod odtwarzania usług w samonaprawialnych sieciach ATM opartych na ścieżkach wirtualnych i o topologii kratkowej. Przedstawiono model z zaplanowanymi z góry ścieżkami zabezpieczającymi i wyniki badań przykładowej sieci w Polsce.
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublicationNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublicationW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublicationNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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Topology improvements in scale-free networks when assuring security and survivability
PublicationW artykule zaproponowano heurystyczny algorytm iteracyjny (NEA) kontrolowanego rozrostu sieci, zmniejszający stopień jej bezskalowości. Pokazano, że odpowiednia kontrola rozrostu sieci, prowadzi do uzyskania sieci o topologii zbliżonej do regularnej, a więc w duzym stopniu odpornej na celowe działania niszczące - ataki. Właściwości algorytmu zostały przebadane przy pomocy dedykowanego symulatora dla reprezentatywnej próby inicjalnych...
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Estimation of musical sound separation algorithm effectiveness employing neural networks.
PublicationŚlepa separacja dźwięków sygnałów muzycznych zawartych w zmiksowanym materiale jest trudnym zadaniem. Jest to spowodowane tym, że dźwięki znajdujące się w relacjach harmonicznych mogą zawierać kolidujące składowe sinusoidalne (składowe harmoniczne). Ewaluacja wyników separacji jest również problematyczna, gdyż analiza błędu energetycznego często nie odzwierciedla subiektywnej jakości odseparowanych sygnałów. W tej publikacji zostały...
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THE USE OF GNSS GEODETIC NETWORKS ON THE APPROACH TO THE PORTS � GULF OF GDANSK STUDY
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Jacek Rak dr hab. inż.
PeopleJacek Rak uzyskał stopień doktora habilitowanego nauk technicznych w dyscyplinie telekomunikacji (specjalność: teleinformatyka) w 2016 r., a stopień doktora nauk technicznych w dyscyplinie informatyka w 2009 r. Obecnie jest pracownikiem naukowo-dydaktycznym Katedry Teleinformatyki Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej. Jego działalność naukowa koncentruje się w obszarze doboru tras, projektowania...
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High prevalence of carriers of variant c.1528G>C of HADHA gene causing long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) in the population of adult Kashubians from North Poland
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The voltage on bus bars of the main switchboard of the car carrier electrical power system at sea trials during a sea voyage
Open Research DataThe dataset is part of the research results on the quality of supply voltage on bus bars of the main switchboard of the ship's electrical power system in different states of ship exploitation. The attached dataset contains the measurement results conducted onboard the car carrier at sea trials. The data were recorded during a sea voyage, under normal...
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Reinforced aluminium reference measurement R63 – earlier tests
Open Research DataPreliminary testing of aluminium alloys against 100Cr6 steel ball. Preparation to tests on wear of Al6061 alloy in ball on disk experiment. Research on the reinforcing effect of aluminium alloy injection reinforcement with TiN and WC powders in laser remelted surface layer.
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Reinforced aluminium reference measurement Result1 – earlier tests
Open Research DataPreliminary testing of aluminium alloys against 100Cr6 steel ball. Preparation to tests on wear of Al6061 alloy in ball on disk experiment. Research on the reinforcing effect of aluminium alloy injection reinforcement with TiN and WC powders in laser remelted surface layer.
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Turre cum capellis suis – identification of an earlier phase of the Holy Cross church at Tar – Stancija Blek (Tar-Vabriga – Torre-Abrega, Istria)
PublicationThe paper reports the results of the first campaign of excavations at the Church of the Holy Cross near Stancija Blek (Tar-Vabriga – Torre-Abrega municipality, Istria), which is close to the multiphase settlement of Old Tar. A trial trench behind the rear wall of the church and along its southern perimetral wall revealed an earlier building and one grave. Though the uncovered remains are scanty, several distinct architectural...
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The Kinetics of FMS-Related Tyrosine Kinase 3 Ligand (Flt-3L) during Chemoradiotherapy Suggests a Potential Gain from the Earlier Initiation of Immunotherapy
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Cassier E.Filozofia form symbolicznych. Część pierwsza: Język. Przekład, wstęp i opracowanie Przemysław Parszutowicz, Kęty : Wydawnictwo Marek Derewiecki, 2018
PublicationNeokantysta Cassirer podejmuje wyjściową kantowską intuicję, rozszerza ją jednak także poza przyrodoznawstwo, na cały obszar „rozumienia świata”. […] Sztuka, język, religia i nauka to wymiary ludzkiej aktywności sensotwórczej, które manifestują się jako obszary kultury, każdorazowo różniące się w swej funkcji i ekspresji. Wspólne im jest to, że nie odwzorowują po prostu tego, co dane, lecz że raczej to, co dane, najpierw wytwarzają....
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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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The Lack of Association between <b><i>FCN2</i></b> Gene Promoter Region Polymorphisms and Dental Caries in Polish Children
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Mobility Managment Scenarios for IPv6 Networks-Proxy Mobile IP-v6Implementation Issues
PublicationManagement 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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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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Towards the boundary between easy and hard control problems in multicast Clos networks
PublicationIn this article we study 3-stage Clos networks with multicast calls in general and 2-cast calls, in particular. We investigate various sizes of input and output switches and discuss some routing problems involved in blocking states. To express our results in a formal way we introduce a model of hypergraph edge-coloring. A new class of bipartite hypergraphs corresponding to Clos networks is studied. We identify some polynomially...
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A bound on the number of middle-stage crossbars in f-cast rearrangeable Clos networks
PublicationIn 2006 Chen and Hwang gave a necessary and sufficient condition under which a three-stage Clos network is rearrangeable for broadcast connections. Assuming that only crossbars of the first stage have no fan-out property, we give similar conditions for f-cast Clos networks, where f is an arbitrary but fixed invariant of the network. Such assumptions are valid for some practical switching systems, e.g. high-speed crossconnects....
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...