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Search results for: COGNITIVE RADIO NETWORKS
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Joint Analysis of National Eco-Efficiency, Eco-Innovation and SDGs in Europe: DEA Approach
PublicationThe growing complexity and intertwining of different socio-economic issues both in individual countries and internationally mean that single-theme analyses do not consider all the relationships and thus have cognitive limitations. Therefore, studies that combine several research areas are increasingly common in the literature to clarify the connections and relationships. In this study, considering the sequential nature of the...
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Experience-based Intelligence Augmentation with Decisional DNA: Upcoming direction
PublicationIntelligence amplification systems and technologies have gained significant interest from academia and industry during the past few decades. One of the main reasons behind this trend is the fact that most experts agree that truly intelligent artificial system is yet to be developed. The question increasing often asked is this: Is full replication of human intelligence desirable key aim in intelligence related technology and research?...
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Cross-Cultural Interactions between Expatriates and Local Managers in the Light of Positive Organizational Behaviour
PublicationThe main purpose of this article is to identify the ‘individual positive deviance’ presented by expatriates and local managers in their mutual cooperation. The theoretical basis for the publication is the discussion of the Positive Organizational Behaviour (POB) essence and the application of this approach in the area of expatriation. Attitudes, behaviour, working style and personality traits of employees of different nationalities...
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New methods for assessment and stimulation of non-communicative patients employing advanced multimodal HCI . Nowe metody oceny i stymulacji pacjentów niekomunikatywnych z wykorzystaniem zaawansowanych interfejsów multimodalnych człowiek-komputer
PublicationIn most cases of patients with locomotor system damage it is possible to find a solution to the medical problems originating from the injury. However, it is much more difficult to prevent cognitive and emotional impairments. Therefore, we believe that the technological support of therapists working with such patients on an everyday basis may be essential. We have acquired experience in designing and providing diagnostic and therapeutic...
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Chemistry of human breast milk – a comprehensive review of the composition and role of milk metabolites in child development
PublicationEarly nutrition has an enormous influence on a child's physiological function, immune system maturation and cognitive development. Human breast milk (HBM) is recognized as the gold standard for human infant nutrition. Accordingly to WHO report breastfeeding is consider as an unequalled way of providing ideal food to the infant, which is required for his healthy growth and development. HBM contains various macronutrients (carbohydrates,...
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The Cluster Organization. Analyzing the Development of Cooperative Relationships
PublicationCluster organizations are becoming more and more popular, both in developing and developed countries. Considering the development of cluster policy and the related dynamic growth of cluster initiatives in the world, the lack of sufficient knowledge on the development of cooperation in cluster organizations inhibits their development and, in many cases, causes their complete disintegration. The book provides new important elements...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublicationA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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Novel Family of Single-Phase Modified Impedance-Source Buck-Boost Multilevel Inverters With Reduced Switch Count
Publicationhis paper describes novel single-phase solutions with increased inverter voltage levels derived by means of a nonstandard inverter configuration and impedance source networks. Operation principles based on special modulation techniques are presented. Detailed component design guidelines along with simulation and experimental verification are also provided. Possible application fields are discussed, as well as advantages and disadvantages....
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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublicationRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Pomiar odpowiedzi impulsowej kanału radiowego na obszarze morskim i przybrzeżnym
PublicationW artykule zaprezentowano wyniki pomiarów odpowiedzi impulsowej kanału radiowego na obszarze morskim i przybrzeżnym. Pomiary przeprowadzono na częstotliwości 1457 MHz a sygnałem sondującym był sygnał o paśmie 10 MHz z modulacją BPSK i pseudoprzypadkową zawartością binarną. Odbierane sygnały były rejestrowane przez dwie stacje ruchome, zainstalowane w samolocie i na łodzi patrolowej. Podczas późniejszej obróbki danych zastosowano...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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A strategy for GPS data processing in a precise local network during high solar activity
PublicationThis paper presents the analyses connected with reduction of errors from ionospheric refraction using GPS data from local satellite networks. This is particularly essential during rising solar activity. The Bernese GPS Software v. 4.2 was used, as an analytical tool. The test data included measurements from a geodynamic network SUDETES situated in the Sudety Mountains across the border between the Czech Republic and Poland. A local...
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Problems of varistor quality assessment during exploitation
PublicationVaristors are commonly used elements which protect power supply networks against high-voltage surges or lightning. Therefore, quality and endurance of these elements is important to avoid losses when an expensive laboratory equipment would not be protected from random overvoltages. Additionally, excessive leakage currents generate serious costs due to high energy consumption. The paper presents shortly properties of varistors that...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network
PublicationWe analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative...
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Control of the cultivation of cartilages for using in the biobearings.
PublicationBiotribologiczne charakterystyki biołożysk są zależne od procesu hodowli żywej tkanki chrząstki w bioreaktorze. Z kolei proces ten, jest wielowymiarowym procesem dynamicznym sterowanym za pomocą odpowiedniego układu automatycznej regulacji. Praca przedstawia prawo i algorytm sterowania takiego procesu. W tym celu zastosowano sztuczne sieci neuronowe (Artificial Neural Networks - ANN) i zaprezentowano wyniki obliczeń.
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MODEL FOR MEASUREMENT OF FLOW INSTALLATION TIME IN SDN SWITCH
PublicationSDN is the approach in telecommunication networks that separates control plane from data forwarding plane by specifying a single network entity as a controller that defines rules (called flows) of traffic forwarding for the switches connected to it. The time that is required for installation of these rules might be a hindrance for the overall performance of SDN network. In the paper, a model for testing and evaluating the influence...
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublicationW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
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Performance analysis of standard and modified EY-NPMA channel access algo-rithms
PublicationPodczas minionego 10-ciolecia notuje się szybki rozwój lokalnych sieci bezprzewodowych (WLANy). Proponowane rozwiązania dotyczą zarówno sieci opartych o przesył komórek (zgodnych z ATM), jak i sieci pakietowych (zgodnych z E-thernetem). Po rozważeniu drugiego z wymienionych typów sieci, wydaje się dzisiaj, iż pakietowe WLANy będą oparte głównie na dwóch standardach, mianowicie: IEEE 802.11 [6]) - wykorzystującym protokół dostępu...
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Measurements of Path Loss in Off-Body Channels in Indoor Environments
PublicationThis paper presents a measurements of the path loss for validation of a statistical model for off-body radio channels in an indoor multipath environment, which considers the distance dependent mean path loss, and describes body shadowing and fast fading components in a statistical way. The measurement equipment and propagation indoor environment have been presented. Two different bodies and five static and two walking scenarios...
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Metamaterial-Based Sub-Microwave Electromagnetic Field Energy Harvesting System
PublicationThis paper presents the comprehensive analysis of the sub-microwave, radio frequency band resonant metastructures’ electromagnetic properties with a particular emphasis on the possibility of their application in energy harvesting systems. Selected structures based on representative topologies of metamaterials have been implemented in the simulation environment. The models have been analyzed and their substitute average electromagnetic...
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Adaptive CAD-Model Construction Schemes
PublicationTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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The determinants of the Region's and its SMEs' Competitive Position in the Context of Mega Events - the Case of the Euro 2012
PublicationIn this paper a modified Preuss model was used to assess the factors to enhance the competitiveness of the region and the SMEs located in the region. To accomplish the above, six types of event-structure were applied: infrastructure, knowledge, networks, culture, image and emotions. They were described in detail in reference to the case of Euro 2012 in Poland in general and Pomeranian region in particular. Finally the Authors take...
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BENEFITS FROM BREAKING UP WITH LINUX NATIVE PACKET PROCESSING WHILE USING INTEL DPDK LIBRARIES
PublicationThe Intel Data Plane Development Kit (DPDK) is a set of libraries and drivers for fast packet processing in Linux. It is a dedicated framework for building efficient high-speed data plane applications supporting QoS features with poll mode drivers which are supporting virtual and physical NIC’s so environment can be used to build efficient data plane applications for packet networks. The results of test on Quality of Service Metering...
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Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation
PublicationA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various low and high frequencies are spatiotemporally coordinated across the human brain during memory processing is inconclusive. They can either be coordinated together across a wide range of the frequency spectrum or induced in specific bands. We used a large dataset of human intracranial electroencephalography...
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Proximity and Innovation in Clusters: How Close, How Far?
PublicationThe concept of proximity, whilst attractive cognitively, is still a poorly explored area in management sciences. The earliest publications on proximity were published at the end of the twentieth century and the development of this concept was strongly influenced by The French School of Proximity (Kirat & Lung, 1999; Rallet & Torre, 1999; Torre & Gilly, 2000; Carrincazeaux et al., 2001; Torre & Rallet, 2005). However, the most influential...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Urban scene semantic segmentation using the U-Net model
PublicationVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Voltage variations and their reduction in a rural low-voltage network with PV sources of energy
PublicationRenewable sources of energy (RES), especially photovoltaic (PV) micro-sources, are very popular in many countries. This way of clean power production is applied on a wide scale in Poland as well. The Polish legal regulations and tariffs specify that every prosumer in a low-voltage network may feed this network with a power not higher than the maximum declared consumed power. In power networks with RES, the voltage level changes...
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On-Line Partitioning for On-Line Scheduling with Resource Conflicts
PublicationWithin this paper, we consider the problem of on-line partitioning the sequence of jobs which are competing for non-sharable resources. As a result of partitioning we get the subsets of jobs that form separate instances of the on-line scheduling problem. The objective is to generate a partition into the minimum number of instances such that the response time of any job in each instance is bounded by a given constant. Our research...
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Introduction to the ONDM 2022 special issue
PublicationThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Power electronic systems as a crucial part of Smart Grid infrastructure - a survey
PublicationThis article gives a tutorial overview of the most important issues related to the use of power electronic systems in power engineering, with respect to the urgent need for modernization of existing grids in the direction of intelligent networks. The main problems and conditions bound up with the construction of Smart Grids and the location, as well as functioning in them of the most important power electronic systems are presented...
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Specyfikacja Systemu IP QoS opartego na architekturze DiffServ
PublicationArtykuł przedstawia ogólną specyfikację systemu IP QoS (ang. Internet Protocol Quality of Service), który to system jest obecnie implementowany w ramach projektu krajowego "Zarządzanie ruchemw sieciach IP". System ten jest zgodny z architekturą DiffServ (ang. Differentiated Services) i architekturą NGN (Next Generation Networks). W szczególności, artykuł pokrótce omawia architekturęsystemu, oferowane klasy usług w systemie oraz...
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublicationThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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Security Evaluation of IT Systems Underlying Critical Networked Infrastructures
PublicationCritical infrastructures have become highly dependent on information and communication technology (ICT). The drawback of this situation is that the consequences of disturbances of the underlying ICT networks may be serious as cascading effects can occur. This raises a high demand for security assurance, with a high importance assigned to security evaluations. In this paper we present an experiment-centric approach for the characterisation...
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AUTOMATED NEGOTIATIONS OVER COLLABORATION PROTOCOL AGREEMENTS
PublicationThe dissertation focuses on the augmentation of proactive document - agents with built-in intelligence to recognize execution context provided by devices visited during a business process, and to reach collaboration agreement despite conflicting requirements. The proposed solution, based on intelligent bargaining using neural networks to improve simple multi-issue negotiation between the document and thedevice, requires practically...
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Multichannel Human Body Communication
PublicationHuman Body Communication is an attractive alternative for traditional wireless communication (Bluetooth, ZigBee) in case of Body Sensor Networks. Low power, high data rates and data security makes it ideal solution for medical applications. In this paper, signal attenuation for different frequencies, using FR4 electrodes, has been investigated. Performance of single and multichannel transmission with frequency modulation of analog...
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublicationAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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Qualitative Indicators Used to Select the Placement and Parameters of Energy Storage Installed in the Distribution Network
PublicationThe technology related to energy storage has developed in recent years. Continuous improvement of the solutions available on the market resulted in wider usability of energy storage. They are also increasingly used in a distribution network. This study contains a synthesised description of physical features of the energy storage used in distribution networks. Several criteria of algorithms used to determine the placement and...
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Selection of Features for Multimodal Vocalic Segments Classification
PublicationEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Modelowanie ryzyka inwestycyjnego przy użyciu OOBN
PublicationCelem artykułu jest przedstawienie sieci Bayesa zorientowanych obiektowo (ang. Object Oriented Bayesian Networks – OOBN). Umożliwiają one dekompozycję złożonego modelu na pojedyncze obiekty, które reprezentują nie tylko różne grupy zagadnień, ale także pozwalają na modelowanie zależności czasowychmiędzy obiektami.Wykorzystanie obiektowych sieci Bayesa zaprezentowano na przykładzie projektu rewitalizacji. Przedstawiono zarówno wady,...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Jakość oprogramowania w zwinnym podejściu do zarządzania projektami informatycznymi
PublicationCel: Celem artykułu jest ocena, czy wykorzystanie podejścia zwinnego Scrum w organizacji podnosi jakość wytwarzanego oprogramowania oraz próba uzyskania odpowiedzi na pytanie, jak nowelizacja Przewodnika po Scrumie (Scrum Guide) z listopada 2020 roku wpłynęła na proces wytwarzania oprogramowania. Projekt badania/metodyka badawcza/koncepcja: Przyjętą metodyką badawczą jest przegląd literatury przedmiotu oraz badania własne autora....
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GNSS INVENTORY OF HISTORIC NARROW-GAUGE RAILWAY LINE IN KOSZALIN UNDER EXTREMELY UNFAVORABLE MEASUREMENTS CONDITIONS FROM THE POINT OF VIEW OF SATELLITE SIGNALS AVAILABILITY
PublicationA team of academic researchers from the Gdańsk University of Technology, Gdynia Maritime University and the Polish Naval Academy have been working since 2009 on the methodology of using active GNSS geodetic networks for geodetic inventory of railways and on adapting this measurement technique for designing geometric layouts of railway and tram lines. Over the years, the team tested a variety of configurations of receivers and settings...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...