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Search results for: computer networks
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Józef Woźniak prof. dr hab. inż.
PeopleProfessor Józef Woźniak received his M.Sc., Ph.D. and D.Sc. degrees in electronics and telecommunications from the Faculty of Electronics, Gdańsk University of Technology (GUT), Poland, in 1971, 1976 and 1991, respectively. In January 2002 he became a full professor. In 1993 he was elected Associate Dean of the Faculty of Electronics and in 1994 he was he was appointed a Professor at GUT. Simultaneously, from October 1994 till...
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Modelling the malware propagation in mobile computer devices
PublicationNowadays malware is a major threat to the security of cyber activities. The rapid develop- ment of the Internet and the progressive implementation of the Internet of Things (IoT) increase the security needs of networks. This research presents a theoretical model of malware propagation for mobile computer devices. It is based on the susceptible-exposed- infected-recovered-susceptible (SEIRS) epidemic model. The scheme is based on...
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Distributed protection against non-cooperative node behavior in multi-hop wireless networks
PublicationAn important security problem in today's distributed data networks is the prevention of non-cooperative behavior i.e., attacks consisting in the modification of standard node operation to gain unfair advantage over other system nodes. Such a behavior is currently feasible in many types of computer networks whose communication protocols are designed to maximize the network performance assuming full node cooperation. Moreover, it...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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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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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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Clothes Detection and Classification Using Convolutional Neural Networks
PublicationIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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The reliability of any-hop star networks with respect to failures of communication nodes.
PublicationThis paper investigated the reliability of any-hop star networks. The any-hop star topology is used in centralized computer networks. We will assume that the all nodes fail independently, links are failure-free. Following measures of network reliability are assumed: the expected number of nodes, which can communicate with the central node; the expected number of node pairs, which are connected by a path through the central node;...
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A repeated game formulation of network embedded coding for multicast resilience in extreme conditions
PublicationComputer networks and data sharing applications are vital for our current society and fundamental for any available ICT solution, so that networking is considered as one of the key critical infrastructures and its correct behavior should be always enforced, even in case of disasters or severe execution conditions. Resilience is a strongly demanding nonfunctional requirement for current computer networks, and one of the key factors...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Deep Learning Basics 2023/24
e-Learning CoursesA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Piotr Szczuko dr hab. inż.
PeoplePiotr Szczuko received his M.Sc. degree in 2002. His thesis was dedicated to examination of correlation phenomena between perception of sound and vision for surround sound and digital image. He finished Ph.D. studies in 2007 and one year later completed a dissertation "Application of Fuzzy Rules in Computer Character Animation" that received award of Prime Minister of Poland. His interests include: processing of audio and video, computer...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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A review on computer‐aided chemogenomics and drug repositioning for rational COVID ‐19 drug discovery
PublicationApplication of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment―either experimentally or computationally―to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Paweł Czarnul dr hab. inż.
PeoplePaweł Czarnul obtained a D.Sc. degree in computer science in 2015, a Ph.D. in computer science granted by a council at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology in 2003. His research interests include:parallel and distributed processing including clusters, accelerators, coprocessors; distributed information systems; architectures of distributed systems; programming mobile devices....
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More Just Measure of Fairness for Sharing Network Resources
PublicationA more just measure of resource distribution in computer networks is proposed. Classic functions evaluate fairness only “on average”. The proposed new fairness score function ensures that no node is left without resources while on average everything looks good. It is compared with well-known and widely adopted function proposed by Jain, Chiu and Hawe and another one recently proposed fairness function by Chen and Zhang. The function...
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Radio Simulcasting at a Glance: a New Look at Broadcasting and Streaming Services
PublicationRadio is by far one of the most popular and accessible medium. With its availability it attracts listeners all around the world. There are numerous ways of delivering content to consumers. The present situation is characterized by the convergence of acoustics, computer science and telecommunications. This paper reviews the current status of radio broadcasting and streaming services. It describes a subjective study concerning different...
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Minimising the Churn Out of the Service by Using a Fairness Mechanism
PublicationThe paper proposes an algorithm of bandwidth distribution, ensuring fairness to end-users in computer networks. The proposed algorithm divides users into satisfied and unsatisfied users. It provides fairness in terms of quality of experience (QoE) for satisfied users and quality of service (QoS) for unsatisfied users. In this paper, we present detailed comparisons relevant to service providers to show the advantages of the proposed...