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Search results for: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES
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Selected manufacturing difficulties encountered during setup of machining on cnc multi-axis linear automatic lathe and on cnc multi-spindle turning centers
PublicationThe article presents the observed manufacturing technology implementation difficulties in workshop practice, resulting from the construction and principles of operation on the DMG’s SPRINT 32/5 CNC linear automatic lathe and on the Mazak’s HQR 150 MSY and QTN 200 MS CNC turn - mill centers, and discusses possible rules for solving the production problems encountered. The article also discusses the principles of dividing the machining...
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Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants
PublicationThis review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents...
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Globalized parametric optimization of microwave components by means of response features and inverse metamodels
PublicationSimulation-based optimization of geometry parameters is an inherent and important stage of microwave design process. To ensure reliability, the optimization process is normally carried out using full-wave electromagnetic (EM) simulation tools, which entails significant computational overhead. This becomes a serious bottleneck especially if global search is required (e.g., design of miniaturized structures, dimension scaling over...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublicationMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
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Identification of regions of interest in video for a traffic monitoring system
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Organizational innovativeness and coopetition: a study of video game developers
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CDN for Live and On-Demand Video Services over IP
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Identification of regions of interest in video for a traffic monitoring system
PublicationA system for automatic event detection in the camera image is presented in this paper. A method of limiting a region of interest to relevant parts of the image using a set of processing procedures is proposed. Image processing includes object detection with shadow removal performed in the modified YCbCr color space instead of RGB. The proposed procedures help to reduce the complexity of image processing algorithm and result in...
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Automatic system for audio-video material reconstruction and archiving
PublicationReferat przedstawia propozycję modelu systemu automatycznej archiwizacji i rekonstrukcji nagrań audio-wideo. Założeniem tego rozwiązania jest uczynienie procesu rekonstrukcji nagrań bardziej niezależnym od człowieka. Ma to na celu redukcję kosztów rekonstrukcji przetwarzanych nagrań. Z powodu dużej liczby archiwalnych nagrań audio-wideo istnieje potrzeba stworzenia systemu który umożliwi automatyczną indeksację ich treści. Pomoże...
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The effects of graphical interface design characteristics on human–computer interaction task efficiency
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Task Allocation and Scalability Evaluation for Real-Time Multimedia Processing in a Cluster Envirinment
PublicationAn allocation algorithm for stream processing tasks is proposed (Modified best Fit Descendent, MBFD). A comparison with another solution (BFD) is provided. Tests of the algorithms in an HPC environment are descrobed and the results are presented. A proper scalability metric is proposed and used for the evaluation of the allocation algorithm.
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Numerical studies on the influence of selected construction features and road conditions on the performance of road cable barriers
PublicationCable barriers are commonly used on Polish roads, including motorways and local roads. Their main elements are pre-stressed wire ropes, which are usually anchored at two ends in concrete blocks buried in the soil. In this work numerical studies concerning the influence of selected construction features and parameters of the vehicle motion on the performance of cable barriers were performed. Numerical simulations are a useful tool...
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How to model temporal changes in nontargeted metabolomics study? A Bayesian multilevel perspective
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Analysis of the Spatial and Temporal Distribution of Process Gases within Municipal Biowaste Compost
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Multi-core and Multiprocessor Implementation of Numerical Integration in Finite Element Method
PublicationThe paper presents techniques for accelerating a numerical integration process which appears in the Finite Element Method. The acceleration is achieved by taking advantages of multi-core and multiprocessor devices. It is shown that using multi-core implementation with OpenMP and a GPU acceleration using CUDA architecture allows one to achieve the speedups by a factor of 5 and 10 on a CPU and GPUs, respectively.
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublicationNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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TRANSPORT POSSIBILITY FOR MPEG-4/AVC- AND MPEG-2-ENCODED VIDEO DATA IN IPTV: A COMPARISON STUDY
PublicationIPTV (Television over IP) is a modern service with a great potential to expand. It uses the IP transport platform, that is already in worldwide operation. At the time of writing, two techniques are used to transport the video and audio data of IPTV: MPEG-2 TS and Native RTP. The two techniques quite definitely have an influence on both quality of service (QoS) and quality of experience (QoE). This paper sets out to demonstrate...
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Properties of an innovative multi-functional finish for the improvement of indoor air quality
PublicationDue to lifestyle changes, people spend most of their time indoors at present; thus, Indoor Air Quality (IAQ) is a matter of utmost importance. Multi-functional and innovative finishes can help to passively improve the IAQ, benefitting the health and comfort of occupants. For this study, reference and pre-mixed commercial mortars are compared to a new multi-functional hydraulic lime mortar for indoor finishes, in which conventional...
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Issues relating to the efficient Application of passive solar protection in multi-family residential buildings
PublicationThe following article is intended to discuss the issues concerning the introduction of passive measures aimed at improving solar protection in multi-family buildings. A system of classifying these methods into two groups of solutions (architectural and material-building) was applied. The first group includes issues concerning facade design, the spatial features of which (such as loggias, balconies and other overhangs) can be treated...
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Novel molecules containing structural features of NSAIDs and 1,2,3-triazole ring: Design, synthesis and evaluation as potential cytotoxic agents
PublicationFor the first time the template containing structural features of more than one NSAIDs and the 1,2,3-triazole ring was explored for the identification of potential cytotoxic agents. These new and complex molecules were predicted to be effective inhibitors of PDE4B by molecular modelling studies in silico. The multi-step synthesis of these compounds were carried out starting from the well-known drug nimesulide and involved the use...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Video Classification Technology in a Knowledge-Vision-Integration Platform for Personal Protective Equipment Detection: An Evaluation
PublicationThis work is part of an effort for the development of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. This paper focuses on hazards resulted from the non-use of personal protective equipment (PPE), and examines a few supervised learning techniques to compose the proposed system for the purpose of recognition of three protective...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Accelerated Parameter Tuning of Antenna Structures by Means of Response Features and Principal Directions
PublicationPopularity of numerical optimization has been steadily on the rise in the design of modern antenna systems. Resorting to mathematically rigorous parameter tuning methods is a matter of practical necessity as interactive techniques (e.g., parameter sweeping) are no longer adequate when handling several performance figures over multi-dimensional parameter spaces. The most common design scenarios involve local tuning since decent...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe 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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Serwisy WWW jako instrument kształtowania relacji z klientem usług medycznych
PublicationWprowadzenie: W artykule podjęto problem oceny użyteczności serwisów WWW i badania postaw lojalnościowych e-klientów korzystających z serwisów WWW usług medycznych. Celem badania była wstępna walidacja metody do oceny jakości użytkowej serwisów WWW usług medycznych oraz określenie związków pomiędzy cechami jakości użytkowej serwisów WWW a cechami relacyjnymi, takimi jak: satysfakcja, chęć powrotu oraz zamiar rekomendowania serwisu...
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Segmentation-Based BI-RADS Ensemble Classification of Breast Tumours in Ultrasound Images
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Validation of the Polish version of WHO-5 as a screening instrument for depression in adults with diabetes
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Virtual instrument using bilinear transformation for parameter identification of high impedance objects.
PublicationArtykuł przedstawia przyrząd wirtualny do pomiaru parametrów obiektów wysokoimpedancyjnych (/Zx/<10GOhm). Opracowano metodę identyfikacji elementów składowych dwójników wieloelementowych opartą na przekształceniu biliniowym.Metoda jest predestynowana do identyfikacji parametrów różnych powłok antykorozyjnych. Dla identyfikacji konieczne są wektorowe pomiary impedancji obiektu na kilku wybranych częstotliwościach, których liczba...
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Musical Instrument Classification and Duet Analysis Employing Music Information Retrieval Techniques.
PublicationArtykuł przedstawia w sposób przeglądowy prace Katedry Systemów Multimedialnych Politechniki Gdańskiej związane z wyszukiwaniem informacji muzycznej, a w szczególności z klasyfikacją dźwięków instrumentów muzycznych. W opisywanych eksperymentach wykorzystano sztuczne sieci neuronowe.
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Ontology management in the multi-agent system for the it evaluation
PublicationThe team of researchers at the Gdańsk University of Technology is currently developing a model of the multi-agent system (MAS_IT) that would aid the IT managers to find the most appropriate technology to the goals assumed. The knowledge is to be provided by experts and stored in the facts and rules bases. The responsibility of the verification process-on the input and query stages-is given to the ontology, making it to some extend...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublicationUtilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response...
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Systematic Management of Simulation State for Multi-Branch Simulations in Simulink
PublicationSystematic simulation is a technique related and motivated by the formal analysis of hybrid dynamic systems. It combines the exhaustive and conservative nature of traditional model checking with numerical simulation for providing efficient algorithms to manage simulations. Multi-branch simulation is the concept advancing simulation efficiency by reducing the number of state transitions. This paper introduces an approach to implement...
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<p>Nanoparticles And Human Saliva: A Step Towards Drug Delivery Systems For Dental And Craniofacial Biomaterials</p>
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Chosen single nucleotide polymorphisms (SNPs) of enamel formation genes and dental caries in a population of Polish children
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Finite element method (FEM) implementation in some chosen areas in dental tytanium-ceramic crown design
PublicationAnaliza rozkładu naprężeń wykazała, że szczególnie duże spiętrzenia naprężeń powstają w częściach przyszyjkowych tytanowo-ceramicznej korony stomatologicznej. W przyszyjkowej części modelu występują największe naprężenia rozciągające, szczególnie niebezpieczne dla ceramiki nieodpornej na tego typu obciążenia. Mogą one stanowić przyczynę spękania i odprysków w części przyszyjkowej korony. Wyniki symulacji komputerowej metodą MES...
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublicationIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...