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Wyniki wyszukiwania dla: Bayesian%20Networks
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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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Paweł Czarnul dr hab. inż.
OsobyPaweł Czarnul uzyskał stopień doktora habilitowanego w dziedzinie nauk technicznych w dyscyplinie informatyka w roku 2015 zaś stopień doktora nauk technicznych w zakresie informatyki(z wyróżnieniem) nadany przez Radę Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej w roku 2003. Dziedziny jego zainteresowań obejmują: przetwarzanie równoległei rozproszone w tym programowanie równoległe na klastrach obliczeniowych,...
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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...
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President and Manager of the court versus networking in justice system - "Extending of Delimitation"
PublikacjaCurrent knowledge and empirical studies concering the networks collaboration in public sector, the role of decision-making centre in the building of network structure, strategy formulation and evaluation is fragmentary.
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International Conference on Emerging Ubiquitous Systems and Pervasive Networks
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International Conference on Collaborative Computing: Networks, Applications and Worksharing
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Workshop on Localized Algorithms and Protocols for Wireless Sensor Networks
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IEEE International Workshop on Cellular Nanoscale Networks and Applications
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International Conference on Artificial Neural Networks and Genetic Algorithms
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International Conference on Analysis of Images, Social Networks and Texts
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IEEE International Symposium on Security in Networks and Distributed Systems
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International Work-Conference on Artificial and Natural Neural Networks
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International Conference on Mobile and Ubiquitous Systems: Networks and Services
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IEEE International Workshop on Neural Networks for Signal Processing
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Sensitivity analysis as a tool to optimise Human Development Index
PublikacjaResearch background: Composite indicators are commonly used as an approximation tool to measure economic development, the standard of living, competitiveness, fairness, effectiveness, and many others being willingly implemented into many different research disciplines. However, it seems that in most cases, the variable weighting procedure is avoided or erroneous since, in most cases, the so-called...
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Performance evaluation of IEEE 802.11 fast BSS transition algorithms
PublikacjaSimultation experiments are conducted to answer the questions if multimedia services can be properly supported in IEEE 802.11r networks. The authors prove that handover delay can be reduced to 22 ms in the average case.
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Numerical analysis of open channel steady gradually varied flow using the simplified saint-venant equations
PublikacjaFor one-dimensional open-channel flow modeling, the energy equation is usually used. There exist numerous approaches using the energy equation for open-channel flow computations, which resulted in the development of several very efficient methods for solving this problem applied to channel networks. However, the dynamic equation can be used for this purpose as well. This paper introduces a method for solving a system of non-linear...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublikacjaNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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On the Importance of Resilience Engineering for Networked Systems in a Changing World
PublikacjaResilience is featured increasingly often in the media, usually applied to society when faced, for example, with disasters such as flooding and the enormous challenges that the Covid-19 pandemic posed. There are now many resilience-related discussion groups worldwide, and some standards initiatives devoted in particular to city resilience. However, there is relatively little explicit interest in resilience engineering for communication...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Bounds on isolated scattering number
PublikacjaThe isolated scattering number is a parameter that measures the vulnerability of networks. This measure is bounded by formulas de- pending on the independence number. We present new bounds on the isolated scattering number that can be calculated in polynomial time.
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Bounds on isolated scattering number
PublikacjaThe isolated scattering number is a parameter that measures the vulnerability of networks. This measure is bounded by formulas de- pending on the independence number. We present new bounds on the isolated scattering number that can be calculated in polynomial time.
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Determining QoS in the Video Telephony Service in an IP Environment
PublikacjaIP networks are indispensable nowadays. They are among the most efficient platforms. The constantly growing number of users and new services in these networks - the largest being the Internet - requires a good quality of any application used.Determining the QoS in real-time services is particularly important. This work is dedicated to exactly this aspect of the real-time service Video Telephony over IP (VToIP). First, the ITU-T...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublikacjaABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Factors that strengthen and weaken the identity of the cluster structures
PublikacjaThe main aim of this paper is the application of "identity" to the issues related to "clustering process" and particularly - to the cooperation in the clusters and the cluster initiatives. The authors distinguish these factors that have the greatest influence on the formation and maintenance of identity in mentioned networks of cooperation.
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublikacjaCelem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...
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Application of BAN Network to Increase Security in Transport Systems
PublikacjaIn the article general characteristics of the BAN network with M2M communications are presented. These are networks that enable the implementation of wireless transmission of signals using special sensors located on the body or implanted subcutaneously. These sensors allow monitoring of different type life parameters of a human. In the next part of work there is proposed the implementation of BAN networks to transport systems as...
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Weak forms of shadowing in topological dynamics
PublikacjaWe consider continuous maps of compact metric spaces. It is proved that every pseudotrajectory with sufficiently small errors contains a subsequence of positive density that is point-wise close to a subsequence of an exact trajectory with the same indices. Also, we study homeomor- phisms such that any pseudotrajectory can be shadowed by a finite number of exact orbits. In terms of numerical methods this property (we call it multishadowing)...
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LTE as a Trunking - Dispatch System
PublikacjaIn the paper solutions of trunking-dispatch systems based on the LTE system are presented. The solution in the form of separate LTE/TDD trunking system is discussed, and the concept of the LTE/FDD trunking system operating in the infrastructure of public, mobile networks is characterised.
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Trends in Locally Balanced Energy Systems without the Use of Fossil Fuels: A Review
PublikacjaIn recent years, the idea of the operation of energy systems (power systems, heating systems) has changed significantly. This paper is an overview of locally balanced energy systems without the use of fossil fuels. The paper justifies the concept of local energy balancing in a new energy system that does not use fossil fuels (coal, natural gas, and crude oil), based on European Union guidelines and formal documents as well as the...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublikacjaIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublikacjaThe 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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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently 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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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Perspectives of Transport Systems Development in the Light of Radio Communication Systems Evolution Towards 5G
PublikacjaIn the paper conditions of development and implementation of transport systems with reference to the development of radio communication networks towards 5G are presented. First, general properties of next generation systems are mentioned and their architecture. Moreover, planned characteristics of B4G and 5G systems are depicted which can significantly contribute to the promotion and development of transport systems. In particular...
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Simulation Model for Application of the SDN Concept in IMS/NGN Network Transport Stratum
PublikacjaThe paper presents a simulation model allowing examination of cooperation between two currently used telecommunication networks concepts: IP Multimedia Subsystem/Next Generation Network (IMS/NGN) and Software-Defined Networking (SDN). Application of the SDN architecture elements in IMS/NGN networks will enable unified control and management of transport resources for various transport technologies and equipment manufacturers. However,...
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Path Loss Analysis for the IoT Applications in the Urban and Indoor Environments
PublikacjaThe Internet of Things (IoT) networks concept implies their presence in a various and untypical locations, usually with a disturbed radio signals propagation. In the presented paper an investigation of an additional path loss observed in an underground environment was described. The proposed measurement locations correspond to the operation areas of rapidly growing narrowband IoT (NBIoT) networks, the ones using the Long Term Evolution...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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European Workshop on Security and Privacy in Ad -Hoc and Sensor Networks
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IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks
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Workshop on Theoretical and Algorithmic Aspects of Sensor and Ad-hoc Networks
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Badawczo-rozwojowe laboratorium sieci optycznych wykorzystujące sprzęt ADVA Optical Networking
PublikacjaPrzedstawiono uwarunkowania i kierunki zmian w sieciach optycznych, a następnie wskazano na potrzebę posiadania laboratorium, w którym możliwe byłoby prowadzenie prac badawczo-rozwojowych oraz kształcenie. Przedstawiono koncepcję takiej sieci opartej na sprzęcie ADVA Optical Networking zrealizowaną w Katedrze Sieci Teleinformacyjnych Wydziału ETI PG. Opisano możliwości sprzętowo-funkcjonalne tego laboratorium oraz prowadzone prace...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Next Generation Digital
PublikacjaThe paper outlines the major objectives of the MENAID research project, eimed at novel architectures of digital documents. Such documents will enable reduction of information overflow and strain, a major threat to the growth of a digital society. They will be forward compatible, technology neutral and lightweight, allowing workers of network organizations to use personal devices of any type.
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Performance Analysis of Interaction between Smart Glasses and Smart Objects Using Image-Based Object Identification
PublikacjaWe propose the use of smart glasses to collaborate with smart objects in the Internet of Things environment. Particularly we are focusing on new interaction methods and the analysis of acceptable reaction times in the process of object recognition using smart glasses. We evaluated the proposed method using user studies and experiments with three different smart glasses: Google Glass, Epson Moverio, and the developed eGlasses platform....