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Search results for: LARGE PACKET NETWORKS
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS 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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Radio Link Measurement Methodology for Location Service Applications
PublicationThe 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
PublicationOur 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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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn 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
PublicationA 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
PublicationBayesian 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
PublicationThe 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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Electromagnetic Simulations with 3D FEM and Intel Optane Persistent Memory
PublicationAbstract—Intel Optane persistent memory has the potential to induce a change in how high-performance calculations requiring a large system memory capacity are conducted. This article presents what this change may look like in the case of factorization of large sparse matrices describing electromagnetic problems arising in the 3D FEM analysis of passive highfrequency components. In numerical tests, the Intel oneAPI MKL PARDISO was...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublicationVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Multipath routing for quality of service differentiation and network capacity optimization in broadband low-earth orbit systems
PublicationThis 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"
PublicationCurrent 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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Statistical properties of a modified standard map in quantum and classical regimes
PublicationWe present a model—a modified standard map. This model has interesting properties that allow quantum–classical correspondences to be studied. For some range of parameters in the classical phase space of this model, there exist large accelerator modes. We can create a family of maps that have large accelerator modes.
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Performance evaluation of IEEE 802.11 fast BSS transition algorithms
PublicationSimultation 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
PublicationAutomated 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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On the Importance of Resilience Engineering for Networked Systems in a Changing World
PublicationResilience 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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Numerical analysis of open channel steady gradually varied flow using the simplified saint-venant equations
PublicationFor 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
PublicationNeural 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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Data augmentation for improving deep learning in image classification problem
PublicationThese 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
PublicationThe 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
PublicationThe 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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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe 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
PublicationABSTRACT 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
PublicationRNA 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
PublicationThe 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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Thermodynamics of solid phases containing rare earth oxides
PublicationRare earth elements (RE) are incorporated into a large variety of complex oxide phases to provide tailored mechanical, electrical, optical, and magnetic properties. Thermodynamics control phase stability, materials compatibility in use, corrosion, and transformation. This review presents, in one compilation, the thermodynamic properties of a large number of such materials and discusses systematic trends in energetics and the factors...
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Weak forms of shadowing in topological dynamics
PublicationWe 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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Application of BAN Network to Increase Security in Transport Systems
PublicationIn 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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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublicationThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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LTE as a Trunking - Dispatch System
PublicationIn 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
PublicationIn 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.
PublicationIn 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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Simulation Model for Application of the SDN Concept in IMS/NGN Network Transport Stratum
PublicationThe 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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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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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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Perspectives of Transport Systems Development in the Light of Radio Communication Systems Evolution Towards 5G
PublicationIn 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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Path Loss Analysis for the IoT Applications in the Urban and Indoor Environments
PublicationThe 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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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep 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
PublicationDeep 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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Possibility to use engine compression ignition engines in floating power plants marine
PublicationCompression-ignition engines used in ship technology as main propulsion engines are large units reaching even to 50-60 MW. The engines can be used in power industry for electricity generation in a simple or combined steam turbine system in combined heat and power plants. The leading engine in such an arrangement is an internal-combustion piston engine. The main propulsion engines are used in large piston internal-combustion engines...
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Networkig activities of general judiciary - from theory to practice
PublicationOver the last three decades, networks - as a field of research - have acquired a significant place among management sciences. Unfortunately, in the judiciary they have become a subject of more careful analyses only recently, which resulted in a large discrepancy of knowledge - both in theory and in its practical adaptation for the needs of the courts. In order to fill this cognitive gap, an attempt was made to identify levels of...
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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublicationElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
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Badawczo-rozwojowe laboratorium sieci optycznych wykorzystujące sprzęt ADVA Optical Networking
PublicationPrzedstawiono 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 CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe 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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Wirtualne sieci 5G, NGN i następne. Radioinformatyczna metamorfoza sieci komórkowych
PublicationPrzedstawiono problematykę ewolucyjnej, a w zasadzie rewolucyjnej, metamorfozy komórkowych systemów radiokomunikacyjnych w kontekście architektury sieci 5G, zasad jej działania oraz nowych możliwości implementacyjnych usług sieci NGN. Artykuł dotyczy w szczególności istoty działania sieci 5G, łączącej w sobie cechy sieci radiokomunikacyjnych poprzednich generacji, zwłaszcza 4G, oraz nowe właściwości charakterystyczne dla 5G. Dotyczą...
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Trade in value added of countries involved in TTIP: EU-USA comparison
PublicationThe aim of this paper is to present key facts concerning trade in the value added of those countries participating in the Transatlantic Trade and Investment Partnership (TTIP). In particular, we describe how involvement in global production networks (GPN) varies across EU countries with respect to the United States.
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Next Generation Digital
PublicationThe 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
PublicationWe 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....