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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublikacjaThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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Education of Logisticians in Poland: Problems and Prospects in Students’ Opinion
PublikacjaLogistics is one of the key sectors of the Polish economy. Its value reflects not only its own capacity, but also the role it plays in ensuring the proper functioning of the entire economy. The rapid development of the industry and the highest demands on logistics solutions bring to the fore the problem of preparing a new generation of specialists in logistics. That is why the question of compliance to learning expectations of...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Solubility advantage of sulfanilamide and sulfacetamide in natural deep eutectic systems: experimental and theoretical investigations
PublikacjaObjective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing...
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How to choose drive’s rated power in electrified urban transport?
PublikacjaSelection of drive's rated power influences not only vehicle's dynamics, but also its energy efficiency. Mentioned above approach requires a multiphysical model, which covers both mechanical and electrical phenomena. This paper discusses how selection of traction drive's rated power influences vehicle energy consumption on example of a trolleybus. A complex mathematical model was developed in Matlab/Simulink to describe the multiphisical...
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Sławomir Jerzy Ambroziak dr hab. inż.
OsobySławomir J. Ambroziak urodził się w 1982 r. Uzyskał tytuł zawodowy magistra inżyniera w zakresie systemów i usług radiokomunikacyjnych w roku 2008, w 2013 r. uzyskał stopień doktora nauk technicznych w dyscyplinie telekomunikacja, w specjalności radiokomunikacja, natomiast w 2020 r. uzyskał stopień doktora habilitowanego. Od 2008 r. jest pracownikiem Katedry Systemów i Sieci Radiokomunikacyjnych na Wydziale Elektroniki, Telekomunikacji...
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Spotkanie informacyjne dla kandydatów do Szkoły Doktorskiej
WydarzeniaW dniu 29 czerwca, o godz. 11:00 (UTC+2) , odbędzie się spotkanie informacyjne dla kandydatów, dotyczące rekrutacji do Szkoły Doktorskiej PG na r.a. 2021/2022. Dostęp na hasło: PhD
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A coarse‐grained approach to NMR ‐data‐assisted modeling of protein structures
PublikacjaThe ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically...
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Piotr Krajewski dr
OsobyPiotr Krajewski pracuje jako starszy bibliotekarz w Bibliotece Politechniki Gdańskiej. Jako pracownik Sekcji Informacji Naukowo-Technicznej skupia się przede wszystkim na zagadnieniach związanych z ruchem Open Access oraz rolą repozytoriów instytucjonalnych w jego rozwoju. Jest także autorem artykułów poruszających kwestie standaryzacji statystyk wykorzystania zasobów elektronicznych jak również problematykę „drapieżnych wydawców”....
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Sławomir Ostrowski dr inż.
OsobySławomir Ostrowski jest pracownikiem naukowo-dydaktycznym zatrudnionym na stanowisku adiunkta w Katedrze Informatyki w Zarządzaniu na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W 2018 roku uzyskał stopień doktora nauk ekonomicznych w dyscyplinie: nauki o zarządzaniu. Absolwent jednolitych studiów magistersko-inżynierskich na kierunku Zarządzanie (specjalność Zarządzanie Technologiami IT) na Wydziale Zarządzania i Ekonomii...
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Arsalan Muhammad Soomar Doctoral Student
OsobyHi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan. Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio as a Solar Design Engineer. HEADLINE Currently Enrolled as a Doctoral...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublikacjaThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Viewpoint independent shape-based object classification for video surveillance
PublikacjaA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Uniform sampling in constrained domains for low-cost surrogate modeling of antenna input characteristics
PublikacjaIn this letter, a design of experiments technique that permits uniform sampling in constrained domains is proposed. The discussed method is applied to generate training data for construction of fast replacement models (surrogates) of antenna input characteristics. The modeling process is design-oriented with the surrogate domain spanned by a set of reference designs optimized with respect to the performance figures and/or operating...
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A survey of neural networks usage for intrusion detection systems
PublikacjaIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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CFD analysis of fluid flow through the labyrinth seal
PublikacjaSteam and gas turbines are some of the fundamental means of power generation. The energy efficiency of the turbines, however, is not satisfactory. Ever since the start-up of the first turbine in the world, engineers have been striving for their increased efficiency. Multiple solutions to the problem of steam loss in an operating turbine are available. The use of seals is one of them. Empirical methods or numerical calculations...
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The Taxonomy Spatial Measure of Development in the Standard of Living Analysis
PublikacjaIncorporation of spatial relationships in the construction of taxonomy measure of development is gaining popularity in Polish literature. However, there is no one common idea concerning how the spatial relationship should be taken into account when creating a synthetic variable nor, indeed, where the spatial weight matrix should be placed. It seems that the inclusion of spatial relationships is more important in smaller regions’...
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Recent Advances in Development of Waste-Based Polymer Materials: A Review
PublikacjaLimited petroleum sources, suitable law regulations, and higher awareness within society has caused sustainable development of manufacturing and recycling of polymer blends and composites to be gaining increasing attention. This work aims to report recent advances in the manufacturing of environmentally friendly and low-cost polymer materials based on post-production and postconsumer wastes. Sustainable development of three groups...
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Massive Open Online Courses: strategies and research areas
PublikacjaThe latest education revolution, the massive open online courses (MOOCs), is gaining momentum, accolades, and participation across industry and academia. These learning laboratory behemoths host and assess tens to hundreds of thousands of students in a single class, for free. Similar to their scope, MOOCs’ short- and long-term educational implications seem massive. Immediate MOOC educational outcomes vary widely from roaring successes...
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Data librarian and data steward – new tasks and responsibilities of academic libraries in the context of Open Research Data implementation in Poland
PublikacjaThesis/Objective – The policy of Open Access (OA) for researching resources in Europe has been implemented for more than 10 years. The first recommendations concerning providing OA to scientific materials were defined during the implementation of the 7th Framework Programme. Introducing another set of recommendations concerning OA to research data was the next stage. The recommendations were transformed into obligations under the...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublikacjaA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Pressure pulsations in turbine blade seal clearance
PublikacjaThe paper presents the results of numerical and experimental investigations into pressure forces generated in a turbine labyrinth seal. The experiments were performed on a single-stage air model turbine of the impulse type, while the numerical results were obtained by means of CFD Fluent Code. The performed experimental research and numerical calculations prove that in a shroud clearance the pressure pulsates and the effects of...
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Influence of Flat Lapping Kinematics on Machinability of Ceramics
PublikacjaNew tools for flat grinding of ceramics are presented in the paper. Electroplated CBN tools (B64 and B107) were used in a modified single-disc lapping machine configuration. The results from experiments, such as the material removal rate and surface roughness parameters are presented and analyzed. Numerical simulations, based on the model for the shape error and tool wear estimation in machining with flat lapping kinematics, are...
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POPRAWA OBIEKTYWNYCH WSKAŹNIKÓW JAKOŚCI MOWY W WARUNKACH HAŁASU
PublikacjaCelem pracy jest modyfikacja sygnału mowy, aby uzyskać zwiększenie poprawy obiektywnych wskaźników jakości mowy po zmiksowaniu sygnału użytecznego z szumem bądź z sygnałem zakłócającym. Wykonane modyfikacje sygnału bazują na cechach mowy lombardzkiej, a w szczególności na efekcie podniesienia częstotliwości podstawowej F0. Sesja nagraniowa obejmowała zestawy słów i zdań w języku polskim, nagrane w warunkach ciszy, jak również w...
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Human-computer interaction approach applied to the multimedia system of polysensory integration
PublikacjaIn the paper an approach of utilizing an interaction between the human and computer in a therapy of dyslexia and other sensory disorders is presented. Bakker's neuropsychological concept of dyslexia along with therapy methods are reviewed in the context of the Multimedia System of Polysensory Integration, proposed at the Multimedia Systems Department of Gdansk Univ. of Technology. The system is presented along with the training...
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Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublikacjaArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
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Neural network model of ship magnetic signature for different measurement depths
PublikacjaThis paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...
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TeleCAD w kształceniu studentów Wydziału Inżynierii Lądowej Politechniki Gdańskiej
PublikacjaPrzedstawiono system TeleCAD opracowany w ramach projektu Leonardo da Vinci - Teleworkers Training for CAD Systems Users (1998-2001). Głównym celem projektu było stworzenie środowiska obsługi kursów programu AutoCAD bazującego na Internecie jako medium do komunikacji między uczestnikami oraz do dostarczania materiałów kursowych. W artykule zaprezentowano również system służący do oceny jakości szkoleń na odległość. Szkolenie TeleCAD...
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Investigation of Performance and Energy Consumption of Tokenization Algorithms on Multi-core CPUs Under Power Capping
PublikacjaIn this paper we investigate performance-energy optimization of tokenizer algorithm training using power capping. We focus on parallel, multi-threaded implementations of Byte Pair Encoding (BPE), Unigram, WordPiece, and WordLevel run on two systems with different multi-core CPUs: Intel Xeon 6130 and desktop Intel i7-13700K. We analyze execution times and energy consumption for various numbers of threads and various power caps and...
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublikacjaIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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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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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublikacjaA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Using Eye-tracking to get information on the skills acquisition by the radiology residents
PublikacjaThis paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained...
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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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From Creative Thinking Techniques to Innovative Design Solutions - The Educators' Perspective
PublikacjaThe article presents a structure and basic tasks of a new original academic course, which was inaugurated in 2015 at the Faculty of Architecture in Gdańsk University of Technology and organized for the first year students of Spatial Planning.The title of the course was ‘Garden Cities and the Gardens in the Cities. A Course with Elements of Training Creativity’. The aim of the course was to encourage the participants to develop...
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Rapid surrogate-assisted statistical analysis of compact microstrip couplers
PublikacjaIn this paper, a technique for low-cost statistical analysis and yield estimation of compact microwave couplers has been presented. The analysis is executed at the level of a fast surrogate model representing selected characteristic points of the coupler response that are critical to determine satisfaction/violation of the prescribed design specifications. Because of less nonlinear dependence of the characteristic points on geometry...
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Multi-Aspect Quality Assessment Of Mobile Image Classifiers For Companion Applications In The Publishing Sector
PublikacjaThe paper presents the problem of quality assessment of image classifiers used in mobile phones for complimentary companion applications. The advantages of using this kind of applications have been described and a Narrator on Demand (NoD) functionality has been described as one of the examples, where the application plays an audio file related to a book page that is physically in front of the phone's camera. For such a NoD application,...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublikacjaA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Bridge Ergonomic Design: A Review
PublikacjaHuman error remains the most common cause of marine incidents and it is worth emphasizing that navigator’s performance is directly affected by ergonomic factors on the bridge. Studies regarding influence of bridge design and work environment on the operator are rare, thus the main purpose of this paper is to fill in this gap. Documents issued by recognized organizations, research publications and additional sources were reviewed...
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The evolution of education spaces - from plan as generator to regenerative architecture, virtual rooms and green campuses
PublikacjaThe study programmes are often considered the main formative factors in the process of educating future architects. Another highly influential component is the architectural characteristics of learning spaces, and consequently the impact of the physical built environment on the quality of education has been widely discussed. However, not often do we realise that the characteristics of education spaces correlate with the organisational...
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Surface Treatment of Rubber Waste
PublikacjaThis chapter deals with the study of different approaches to improve the compatibility of waste rubber with polymeric matrixes of high density polyethylene (HDPE) by using surface treatments to increase adhesion. Different surface treatments such as etching with sulphuric and nitric acids, the use of a silane as a coupling agent and chlorination with trichloroisocyanuric acid (TCI) have been applied. The modification of waste rubber...
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Toward Polyethylene–Polyester Block and Graft Copolymers with Tunable Polarity
PublikacjaThe synthesis and characterization of polyethylene–polyester block and graft copolymers and their potential as compatibilizers in polyethylene-based polymer blends are being described. The various routes to functionalized polyethylenes and the corresponding block/graft copolymers have been compared and evaluated for their scalability to industrial scale production. Hydroxyl chain-end and randomly OH-functionalized HDPE as well...
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Quality of Satellite Communication in Selected Mobile Android Smartphones
PublikacjaToday, thanks to mobile devices, satellite communication is available to anyone and everywhere. Gaining information on one’s position using GNSS (Global Navigation Satellite Systems), particularly in unknown urban environments, had become an everyday activity. With the widespread of mobile devices, particularly smartphones, each person can obtain information considering his or her location anytime and everywhere. This paper is...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublikacjaSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...