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New type T-Source inverter
PublicationThis 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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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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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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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublicationML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
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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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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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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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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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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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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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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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Mieszalnikowa instalacja gazowa w IMP - PAN
PublicationW pracy zaproponowana została wstępna koncepcja układu odpowiedzialnego za doprowadzanie paliwa syngazowego (syngaz) do silnika o zapłonie iskrowym. Stworzony układ gazowy ma umożliwić zasilanie dwóch agregatów prądotwórczych – zespołu prądotwórczego ZGT-60/D/MA/PE o mocy ciągłej , oraz drugiego, mniejszego o mocy z 3 cylindrowym silnikiem AD 3.152 –Perkins. Przedstawiona została propozycja wytwarzania niskokalorycznych gazów...
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Therapeutic biomaterials - application in neurology and cardiology
PublicationBiomaterials are of interest in most medical fields. It's hard to imagine life without them. And due to the ever-increasing demand, scientists are developing new materials. Diseases of the nervous and cardiovascular systems are still a big problem, which are associated with a limited ability to regenerate brain or heart tissues. Therefore, this review discusses the advancement in biomaterial engineering for the treatment of neurological...
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Therapeutic biomaterials – application in neurology and cardiology
PublicationBiomaterials are of interest in most medical fields. It's hard to imagine life without them. And due to the ever-increasing demand, scientists are developing new materials. Diseases of the nervous and cardiovascular systems are still a big problem, which are associated with a limited ability to regenerate brain or heart tissues. Therefore, this review discusses the advancement in biomaterial engineering for the treatment of neurological...
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Con l’introduzione
PublicationNata nel 1953 con l’obiettivo di portare l’Italia tra le nazioni avanzate anche in campo energetico, Eni rappresenta una delle principali imprese ad aver influenzato l’innovazione economica del Paese. La sua storia, legata a doppio filo alla figura di Enrico Mattei, consente di seguirne le traiettorie di sviluppo e le strategie di internazionalizzazione, nel quadro di un contesto in continua evoluzione. Questo volume ripercorre...
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Integration of natural and artificial intelligence in production systems
PublicationIntegration processes play an increasingly important role in modern economy, and seriously co-decide about the effectiveness of the company. Integration phase occurs in the system life cycle by preceding the final stages of its implementation and activation. In turn, used in software engineering (SE) iteration-evolutionary models, such as spiral model make that the integration activities can occur in varying degrees in all phases...
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Determining QoS in the Video Telephony Service in an IP Environment
PublicationIP 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"
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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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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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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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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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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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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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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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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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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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast 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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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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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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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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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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Energy and valuable organic products recovery from anaerobic processes
PublicationChapter 8 contains: Introduction, Energy balance in wastewater treatment plants and potential energy recovery, Potential valuable products recovery, Anaerobic processes focused on liquid products recovery; Anaerobic digestion (AD) processes focused on gaseous products recovery, Processes enhancing energy and valuable organic products recovery, Conclusions and perspectives. Anaerobic processes offer different pathways for the recovery...
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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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Degradation kinetics and mechanism of pentoxifylline by ultraviolet activated peroxydisulfate
PublicationDegradation of pentoxifylline (PTX) by sodium peroxydisulfate (SPDS) assisted by UV irradiation has been investigated in deionized water. The treatment was more favorable over direct photolysis or peroxydisulfate oxidation alone. The effects of various parameters, including different dosage of oxidant agent, PTX concentration, initial solution pH levels, and the presence of inorganic ions like chloride, nitrate and carbonate have...