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International Conference on Artificial Neural Networks
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Conference on Innovation in Clouds, Internet and Networks
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IEEE Conference on Local Computer Networks
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The International Conference on Future Networks and Communications
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International Conference on COMmunication Systems & NETworkS
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International Symposium on Networks, Computers and Communications
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International Conference on Security of Information and Networks
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Workshop on Cryptography for Ad hoc Networks
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European Conference on Universal Multiservice Networks
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Conference on Software in Telecommunications and Computer Networks
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International Science Conference on Computer Networks
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IEEE Dynamic Spectrum Access Networks
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Marek Blok dr hab. inż.
OsobyMarek Blok w 1994 roku ukończył studia na kierunku Telekomunikacja wydziału Elektroniki Politechniki Gdańskiej i uzyskał tytuł mgra inżyniera. Doktorat w zakresie telekomunikacji uzyskał w 2003 roku na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej. W 2017 roku uzyskał stopień naukowy dra habilitowanego w dyscyplinie telekomunikacja. Jego zainteresowania badawcze ukierunkowane są na telekomunikacyjne...
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Krzysztof Nyka dr hab. inż.
OsobyKrzysztof Nyka, absolwent Wydziału Elektroniki Telekomunikacji i Informatyki Politechniki Gdańskiej (WETI PG), gdzie uzyskał tytuł magistra inżyniera (1986, telekomunikacja) stopień doktora nauk technicznych (2002, elektronika) i doktora habilitowanego (2020 automatyka, elektronika i elektrotechnika). Obecnie jest zatrudniony na stanowisku profesora uczelni w Katedrze Inżynierii Mikrofalowej i Antenowej WETI PG. Zainteresowania...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Overview of cooperative communication methods
PublikacjaThe paper presents issues related to the cooperative communication in wireless networks. Cooperative com-munication involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. It is also possible to use several different data transmission standards. The paper presents the methods used to implement cooperative communication. The types of cooperative...
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Logical Interface for Soft Handover – an effective scheme of handovers in Proxy Mobile IPv6
PublikacjaMultimedia services are currently commonly available on mobile devices. Due to networks' convergence and migration to all-IP networks, mobility management at network layer is required. Moreover, nowadays it is popular to equip mobile devices with more than one wireless interface. Thus, soft handovers can be implemented, which means that an existing connection is removed after a new one is established. Usage of the Logical Interfaces...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial 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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International Symposium on Algorithms and Experiments for Wireless Networks
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International Conference on Ambient Systems, Networks and Technologies
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International Conference on Computer Communication and Networks [IC3N]
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Workshop on Approximation and Randomization Algorithms in Communication Networks
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IEEE International Joint Conference on Neural Networks
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International Symposium on the Mathematical Theory of Networks and Systems
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Conference on Artificial Neural Networks and Expert systems
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International Symposium on Parallel Architectures, Algorithms and Networks
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International Conference on Embedded Wireless Systems and Networks
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International Conference on Broadband Communications, Networks and Systems
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International Conference on Security and Privacy for Communication Networks
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International Conference on Wireless Networks and Mobile Communications
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International Conference on Engineering Applications of Neural Networks
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International Conference on AD-HOC Networks and Wireless
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Testbeds and Research Infrastructures for the Development of Networks and Communities
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The Optical Transport Network Control Based on SDN Architecture
PublikacjaThe aim of this publication is to present research results on the usability of the Software-Defined Networking concept to control transport networks. For this purpose, an easy-to-use connection scheduler was developed capable of controlling connections in optical transport networks. The authors would like to present this solution and details of constructed SDN architecture implemented for modern optical transport solutions based...
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Taxonomy of Schemes for Resilient Routing
PublikacjaThis chapter provides a taxonomy of schemes for resilient routing followed by a discussion of their application to contemporary architectures of communication networks. In particular, a general classification of schemes for resilient routing is first presented followed by a description of the reference schemes for IP networks. The chapter in its later part focuses on the representative techniques of resilient routing for a multi-domain...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin 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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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin 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...
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Path Loss Modelling for Location Service Applications
PublikacjaThe aim of this paper is the path loss modeling for the radiolocation services in radiocommunication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the mobile station (MS) and the base station (BS) is outlined. This...
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New type T-Source inverter
PublikacjaThis paper presents different topologies of voltage inverters with alternative input LC networks. The basic topology is known in the literature as a Z-source inverter (ZSI). Alternative passive networks were named by the authors as T-sources. T-source inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage of the T-source inverter (TSI) is its use of a common voltage...
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Evolutionary Algorithms in MPLS network designing
PublikacjaMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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Aleksandra Parteka dr hab. inż.
OsobyAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Radio Link Measurement Methodology for Location Service Applications
PublikacjaThe aim of this paper is the methodology of measurements executed in a radio link for the realization of radiolocation services in radiocommunication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the universal mobile telecommunications system (UMTS) are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation...
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Pathological brain network activity: memory impairment in epilepsy
PublikacjaOur thinking, memory and cognition in general, relies upon precisely timed interactions among neurons forming brain networks that support cognitive processes. The surgical evaluation of drug-resistant epilepsy using intracranial electrodes provides a unique opportunity to record directly from human brain and to investigate the coordinated activity of cognitive networks. In this issue of Neurology®, Kleen and colleagues1 implicate...
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Surface EMG-based signal acquisition for decoding hand movements
Dane BadawczeBiosignal processing plays a crucial role in modern hand prosthetics. The challenge is to restore functionality of a lost limb based on the signals acquired from the surface of the stump. The number of sensors (emg channels) used for signal acquisition influence the quality of a prosthetic hand. Modern algorithms (including neural networks) can significantly...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Utilization of a Non-Linear Error Function in a Positioning Algorithm for Distance Measurement Systems Designed for Indoor Environments
PublikacjaA new positioning algorithm for distance measurement systems is outlined herein. This algorithm utilizes a non-linear error function which allows us to improve the positioning accuracy in highly difficult indoor environments. The non-linear error function also allows us to adjust the performance of the algorithm to the particular environmental conditions. The well-known positioning algorithms have limitations, mentioned by their...
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Application possibilities of LBN for civil engineering issues
PublikacjaBayesian Networks (BN) are efficient to represent knowledge and for the reasoning in uncertainty. However the classic BN requires manual definition of the network structure by an expert, who also defines the values entered into the conditional probability tables. In practice, it can be time-consuming, hence the article proposes the use of Learning Bayesian Networks (LBN). The aim of the study is not only to present LBN, which can...
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublikacjaThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Multipath routing for quality of service differentiation and network capacity optimization in broadband low-earth orbit systems
PublikacjaThis paper shows the importance of employing multiple different paths for routing in Inter-Satellite Link (ISL) networks in broadband Low-Earth Orbit (LEO) satellite systems. A theoretical analysis is presented and a routing concept is proposed to demonstrate three facts that make multipath routing especially important in broadband LEO networks: (1) differences in the propagation delays have a much greater impact on end-to-end...