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Wyniki wyszukiwania dla: DATA-DRIVEN DECISION TECHNIQUES
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Decision making techniques for electronic communication: an example for Turkey
PublikacjaCommunication is the way for people exchanging information with each other by using various tools. Electronic communication or Ecommunication is the process of sending, receiving and processing information or messages electronically. Electronic communication that is closely related to the development levels of countries, has made considerable progress especially in terms technology, innovation and entrepreneur. In this study, it...
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Advances in soft modelling techniques and decision support
PublikacjaPostępy w technikach miękkiego modelowania i wspomagania decyzji. W edytorialu przybliżono najnowsze osiągnięcia w zakresie miękkiego modelowania opartego na teorii zbiorów rozmytych i systemów z bazami wiedzy. Omówiono postępy teoretyczne w tej dziedzinie, jak również obszary obecnych i przyszłych zastosowań.
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Experience-Driven Model of Decision-Making Processes in Project Teams
PublikacjaThis article presents a model of decision-making processes in project teams. Project teams constitute a specific type of organization appointed to implement a project. Decisions made by project teams result from the methods of project management and best management practices. The authors have undertaken the task of formalizing these processes using the classical method of constructing decision trees. It has been established that...
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Regarding the “Review of surgical techniques and guide for decision making in the treatment of benign parotid tumors”
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Dimensionality-Reduced Antenna Modeling with Stochastically Established Constrained Domain
PublikacjaOver the recent years, surrogate modeling methods have become increasingly widespread in the design of contemporary antenna systems. On the one hand, it is associated with a growing awareness of numerical optimization, instrumental in achieving high-performance structures. On the other hand, considerable computational expenses incurred by massive full-wave electromagnetic (EM) analyses, routinely employed as a major design tool,...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Innovations in Wastewater Treatment: Harnessing Mathematical Modeling and Computer Simulations with Cutting-Edge Technologies and Advanced Control Systems
PublikacjaThe wastewater treatment landscape in Central Europe, particularly in Poland, has undergone a profound transformation due to European Union (EU) integration. Fueled by EU funding and rapid technological advancements, wastewater treatment plants (WWTPs) have adopted cutting-edge control methods to adhere to EU Water Framework Directive mandates. WWTPs contend with complexities such as variable flow rates, temperature fluctuations,...
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Digital Government as Implementation Means for Sustainable Development Goals
PublikacjaOne of the challenges for implementing Sustainable Development Goals (SDGs) is the measurement of indicators that represent progress towards such goals. Measuring such progress enables data-driven decision-making and management of SDG-relevant projects and strategies. The premise of this research is that measuring such indicators depends on measuring so-called means of implementation, i.e. activities that directly contribute to...
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Milena Marycz dr inż.
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Computer controlled systems - 2022/2023
Kursy Onlinemateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution...
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CCS-lecture-2023-2024
Kursy Onlinemateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution optimization...
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Train the trainer course
PublikacjaThis chapter presents the concept, evaluation and evaluation results for the train the trainer. This concept of train the trainers is prepared within Workpackage 5 of EU-funded project: MASTER BSR (Erasmus+ Strategic Partnership Programme). Due to the nature of adult learning the content is designed for the use of participatory methods (involved, active). This method uses various techniques of active learning e.g. group work,...
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Automated Reasoning Based User Interface
PublikacjaMotivation: The ability to directly trace how requirements are implemented in a software system is crucial in domains that require a high level of trust (e.g. medicine, law, crisis management). This paper describes an approach that allows a high level of traceability to be achieved with model-driven engineering supported by automated reasoning. The paper gives an introduction to the novel, automated user interface synthesis in...
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Fundamentals of Data-Driven Surrogate Modeling
PublikacjaThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Method of Decision-Making Logic Discovery in the Business Process Textual Data
PublikacjaGrowing amount of complexity and enterprise data creates a need for novel business process (BP) analysis methods to assess the process optimization opportunities. This paper proposes a method of BP analysis while extracting the knowledge about Decision-Making Logic (DML) in a form of taxonomy. In this taxonomy, researchers consider the routine, semi-cognitive and cognitive DML levels as functions of BP conceptual aspects of Resources,...
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Low-Cost Yield-Driven Design of Antenna Structures Using Response-Variability Essential Directions and Parameter Space Reduction
PublikacjaQuantifying the effects of fabrication tolerances and uncertainties of other types is fundamental to improve antenna design immunity to limited accuracy of manufacturing procedures and technological spread of material parameters. This is of paramount importance especially for antenna design in the industrial context. Degradation of electrical and field properties due to geometry parameter deviations often manifests itself as, e.g.,...
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Influence of algorithmic management practices on workplace well-being – evidence from European organisations
PublikacjaPurpose Existing literature on algorithmic management practices –defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice...
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Dis/Trust and data-driven technologies
PublikacjaThis concept paper contextualises, defines, and systematises the concepts of trust and distrust (and their interrelations), providing a critical review of existing literature so as to identify gaps, disjuncture, and continuities in the use of these concepts across the social sciences and in the context of the consolidation of the digital society. Firstly, the development of the concept of trust is explored by looking at its use...
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Mariusz Figurski prof. dr hab. inż.
OsobyDyrektor Centrum Modelowania Meteorologicznego Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy. Urodził się 27 kwietnia 1964 roku w Łasinie. Egzamin maturalny złożył w 1983 roku po ukończeniu II Liceum Ogólnokształcącego im. Jana III Sobieskiego w Grudziądzu, Studia wyższe w trybie indywidualnym ukończył w 1989 (10.07.1989) na Wydziałach Elektromechanicznym i Inżynierii Lądowej i Geodezji Wojskowej Akademii...
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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics
PublikacjaData-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality which limits the number of independent parameters that can be accounted for in the modelling process. Recently, a performance-driven modelling technique has been proposed where the constrained domain of the...
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Narratives on cutting down trees on private land. A comparison of urban and rural municipalities in Poland using the Q-deliberation method
PublikacjaIncreased development in rural and urban areas leads to a decrease in tree cover and reduces the ecosystem services that trees provide. Municipal authorities must consider managing trees on private land to ensure that residents have access to trees and green spaces. In doing so, they must frequently confront conflicting stakeholder views, which are driven by diverse public and private interests and impacted by the type of landscape...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublikacjaElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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Impact of the Artificial Strait in the Vistula Spit on the Hydrodynamics of the Vistula Lagoon (Baltic Sea)
PublikacjaIn the Vistula Lagoon, storm surges are induced by variable sea levels in the Gulf of Gdańsk and wind action. The rising of the water level in the southern part of the basin, exceeding 1.0 m above mean sea level, can be dangerous for the lowland area of Żuławy Elbląskie, causing the inundation of the polders adjacent to the lagoon. One of the potential possibilities to limit the flood risk is to decrease the water level in the...
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Long-Term Impact of Wind Erosion on the Particle Size Distribution of Soils in the Eastern Part of the European Union
PublikacjaWind erosion is the leading cause of soil degradation and air pollution in many regionsof the world. As wind erosion is controlled by climatic factors, research on this phenomenon isurgently needed in soil and land management in order to better adapt to climate change. In thispaper, the impact of wind erosion on the soil surface in relation to particle size distribution wasinvestigated. Changes in percentage of sand, silt and...
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Improved Uniform Sampling in Constrained Domains for Data-Driven Modelling of Antennas
PublikacjaData-driven surrogate modelling of antenna structures is an attractive way of accelerating the design process, in particular, parametric optimization. In practice, construction of surrogates is hindered by curse of dimensionality as well as wide ranges of geometry parameters that need to be covered in order to make the model useful. These difficulties can be alleviated by constrained performance-driven modelling with the surrogate...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublikacjaFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublikacjaThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
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Using wavelet techniques for multibeam sonar bathymetry data compression
PublikacjaMultibeam sonars are widely used in applications like high resolution bathymetry measurements or underwater object imaging. One of the significant problems in multibeam sensing of the marine environment is large amount of data which must be transmitted from the sonar processing unit to an operator station using a limited bit rate channel. For instance, such a situation would be in the case when the multibeam sonar was mounted on...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Size reduction of ultra-wideband antennas with efficiency and matching constraints
PublikacjaAntenna design is a multifaceted task that involves handling of various performance figures concerning both electrical performance of the structure as well as its geometry. Simultaneous control of several objectives through rigorous optimization is very challenging and virtually impossible through conventional approaches such as parameter sweeping. In this work, we investigate size reduction of ultra‐wideband antenna structures...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Deisgning the Data Warehouse for Decision Support System
PublikacjaRozdział w monografii jest poświecony problematyce budowy systemów z bazami wiedzy dla wspomagania procesów zarządzania. W rozdziale tym przedstawiono metody budowy hurtowni danych Na zakończenie przedstawiono przykład wykorzystania tych hurtowni na potrzeby systemów wspomagania decyzji
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Ireneusz Czarnowski Prof.
OsobyIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Multilevel pharmacokinetics-driven modeling of metabolomics data
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublikacjaArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA 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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Corporate social responsibility and forward default risk mediated by financial performance and goodwill
PublikacjaIn today’s business environment, corporate social responsibility (CSR) has become an increasingly significant factor for firms. This study is driven by the motivation to add to the current literature by investigating the mediating elements that explain the relationship between CSR and forward default risk. In this paper, we attempt to identify the important mediators and give a more comprehensive explanation of this connection...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Sensor data fusion techniques for environment modelling
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublikacjaOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublikacjaData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublikacjaFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Ranking decision variants by subjective paird comparisons in cases with incomplete data.
PublikacjaMetoda porównań parami wykorzystywana jest do szeregowania skończonej,zwykle niewielkiej liczby wariantów decyzyjnych. W metodzie tej ekspert lub grupa ekspertów proszona jest o wyrażenie swojej opinii dotyczącej każdej pary wariantów w postaci względnej preferenecji jednego wariantu nad drugim.Zdarza się jednak często, że ekspert nie jest w stanie ocenić pary lub par wiariantów i mamy wtedy do czynienia z sytuacją...
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On Decision-Making Strategies for Improved-Reliability Size Reduction of Microwave Passives: Intermittent Correction of Equality Constraints and Adaptive Handling of Inequality Constraints
PublikacjaDesign optimization of passive microwave components is an intricate process, especially if the primary objective is a reduction of the physical size of the structure. The latter has become an important design consideration for a growing number of modern applications (mobile communications, wearable/implantable devices, internet of things), where miniaturization is imperative due to a limited space allocated for the electronic circuitry....
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublikacjaProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Data and knowledge supporting decision-making for the urban Food-Water-Energy nexus
PublikacjaCities are hubs of innovation and wealth creation, and magnets for an increasing urban population. Cities also face unprecedented challenges in terms of food, water and energy scarcity, and governance and management. Urban environmental issues are no longer problems for experts to address but have become issues of public debate, in which knowledge from multiple sectors is needed to support inclusive governance approaches. Consequently,...
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Direct Constraint Control for EM-Based Miniaturization of Microwave Passives
PublikacjaHandling constraints imposed on physical dimensions of microwave circuits has become an important design consideration over the recent years. It is primarily fostered by the needs of emerging application areas such as 5G mobile communications, internet of things, or wearable/implantable devices. The size of conventional passive components is determined by the guided wavelength, and its reduction requires topological modifications,...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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International Journal of Data Analysis Techniques and Strategies
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn 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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublikacjaOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
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High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublikacjaDesign of modern antenna systems has become highly dependent on computational tools, especially full-wave electromagnetic (EM) simulation models. EM analysis is capable of yielding accurate representation of antenna characteristics at the expense of considerable evaluation time. Consequently, execution of simulation-driven design procedures (optimization, statistical analysis, multi-criterial design) is severely hindered by the...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Wide-band modulation and adaptive equalization techniques for fast and reliable underwater data transmission.
PublikacjaSzybkość transmisji w płytkim kanale podwodnym jest ograniczona ze względu na wielokrotne odbicia fal dźwiękowych oraz niestacjonarność kanału. Dla zapewnienia szybkiej i niezawodnej transmisji danych w systemach komunikacji stosowane są złożone techniki modulacji oraz equalizacji kanału. W artykule zaproponowano zastosowanie modulacji OFDM oraz equalizacji adaptacyjnej w systemie komunikacji podwodnej. Modulacja OFDM stosowana...
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublikacjaW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublikacjaThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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Marek Tobiszewski dr hab. inż.
OsobyUrodzony 07.04.1984 roku w Gdańsku. W 2012 roku obronił z wyróżnieniem doktorat, w 2017 roku uzyskał habilitację na podstawie osiągnięcia naukowego „Opracowanie służących do oceny uciążliwości środowiskowej procedur analitycznych i rozpuszczalników”. Pracuje w Katedrze Chemii Analitycznej od 2012 roku. Jego zainteresowania naukowe łączą analitykę chemiczną, zwłaszcza analityka związków organicznych w próbkach środowiskowych, z...
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International Conference on Informatics & Data-Driven Medicine
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International Workshop on Domain Driven Data Mining
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Magdalena Szuflita-Żurawska
OsobyMagdalena Szuflita-Żurawska jest kierownikiem Sekcji Informacji Naukowo-Technicznej na Politechnice Gdańskiej oraz Liderem Centrum Kompetencji Otwartej Nauki przy Bibliotece Politechniki Gdańskiej. Jej główne zainteresowania badawcze koncentrują się w obszarze komunikacji naukowej oraz otwartych danych badawczych, a także motywacji i produktywności naukowej. Jest odpowiedzialna między innymi za prowadzenie szkoleń dla pracowników...
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Decisional DNA and Optimization Problem
PublikacjaMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Zdzisław Kowalczuk prof. dr hab. inż.
OsobyW 1978 ukończył studia w zakresie automatyki i informatyki na Wydziale Elektroniki Politechniki Gdańskiej, następnie rozpoczął pracę na macierzystej uczelni. W 1986 obronił pracę doktorską, w 1993 habilitował się na Politechnice Śląskiej na podstawie pracy Dyskretne modele w projektowaniu układów sterowania. W 1996 mianowany profesorem nadzwyczajnym, w 2003 otrzymał tytuł profesora nauk technicznych. W 2006 założył i od tego czasu...
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Nina Rizun dr
OsobyNina Rizun jest adiunktem na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W październiku 1999 r. uzyskała stopień doktora nauk technicznych za specjalizacją Gospodarka przedsiębiorstwa i organizacja produkcji. W latach 1993–2000 pracowała na Wydziale Informatyki Ekonomicznej w Akademji Metalurgicznej, Dnipro, Ukraina. W latach 2000–2016 – na Wydziale Cybernetyki Ekonomicznej i Metod Matematycznych na Uniwersytecie Alfreda...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublikacjaThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublikacjaClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Internal legal acts of technical and medical universities in Poland regulating classes conducted in-person during the Covid-19 pandemic
Dane BadawczeA database of legal acts and other internal documents of medical and technical universities in Poland regulating the way of organizing in-person or hybrid classes during the COVID-19 pandemic from the summer semester 2019/2020 to the winter semester 2020/2021.Documents were encoded in two separate coding systems using the MAXQDA program for qualitative...
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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublikacjaDesign of high‐frequency structures, including microwave and antenna components, heavily relies on full‐wave electromagnetic (EM) simulation models. Their reliability comes at a price of a considerable computational cost. This may lead to practical issues whenever numerous EM analyses are to be executed, e.g., in the case of parametric optimization. The difficulties entailed by massive simulations may be mitigated by the use of...
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Electrical responses of nanostructured ZrS3 as field-effect transistor for nitrogen dioxide, ethanol, and acetone detection enhanced by visible light
Dane BadawczeSmall-area layers of nanostructured ZrS3 were fabricated and measured in the field-effect transistor configuration. Irradiation with visible light enabled generating photocurrent and increasing the sensitivity to selected ambient gases: nitrogen dioxide, ethanol, and acetone. The data set consists of electrical responses (current vs. voltage characteristics...
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IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
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Expedited Variable-Resolution Surrogate Modeling of Miniaturized Microwave Passives in Confined Domains
PublikacjaDesign of miniaturized microwave components is largely based on computational models, primarily, full-wave electromagnetic (EM) simulations. EM analysis is capable of giving an accurate account for cross-coupling effects, substrate and radiation losses, or interactions with environmental components (e.g., connectors). Unfortunately, direct execution of EM-based design tasks such as parametric optimization or uncertainty quantification,...
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Experience Based Clinical Decision Support Systems: An Overview and Case Studies
PublikacjaThis chapter briefly overviews the evolution of the application of the Decisional DNA and the Set of Experience Knowledge Structure (SOEKS) in the medical domain and in particular in the specific case of the experience-based decision support systems. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making...
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Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application
PublikacjaAn evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application...
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Towards a Framework for Context Awareness Based on Textual Process Data
PublikacjaContext awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it be-comes essential to employ relevant text analytics techniques to increase the awareness of business process (BP) workers,...
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Knowledge management driven leadership, culture and innovation success – an integrative model
PublikacjaPurpose – This article examines the relation between knowledge management (KM) driven leadership, culture and innovation success of knowledge-intensive small and medium sized companies. By building on the previously reported research on leadership, culture, innovation, and knowledge management, we synergistically integrated KM-driven leadership and innovation success while exploring the meditational role of culture in that. Design/methodology/approach...
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Individual corporate reputation, perception of collective corporate reputation, stock market investments
Dane BadawczeThere are two ways of conceiving of corporate reputation: individual and collective. Although related, they are not driven by the same factors. Thus, each of them may have a distinct impact on investment decisions. The following dataset includes the data obtained in an incentivized economic experiment based on vignette studies. We induced the perception...
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Electrochemical data for carbonized metal-organic framworks with cobalt
Dane BadawczeThe data includes the Metal-Organic Frameworks (MOF) measurements, where cobalt was added. The research focuses on the impact of aluminium on Oxygen Evolution Reaction (OER). The measurements were conducted on [EC Lab]. The techniques included are Linear Sweep Voltammetry (LSV), Tafel slope, Chronopotentiometry (CP) and Electrochemical Impedance Spectroscopy...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublikacjaElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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Hazard Control in Industrial Environments: A Knowledge-Vision-Based Approach
PublikacjaThis paper proposes the integration of image processing techniques (such as image segmentation, feature extraction and selection) and a knowledge representation approach in a framework for the development of an automatic system able to identify, in real time, unsafe activities in industrial environments. In this framework, the visual information (feature extraction) acquired from video-camera images and other context based gathered...
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Macroeconomic Reports - Nowy
Kursy OnlineThis course intends to teach and train students in their analytical skills. Students are supposed to search data and information through international databases and then, using various analytical techniques, prepare a macroeconomic report in selected topic.
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublikacjaCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Data from the survey on factors determining the employment of the Gdańsk University of Technology graduates’ in the opinion of entrepreneurs
Dane BadawczeThe dataset includes data from the survey on factors determining the employment of the Gdańsk University of Technology (GUT) graduates’ in the opinion of entrepreneurs. The survey was conducted in 2017. The research sample included 102 respondents representing various firms from Pomeranian Voivodship. The study concerned i.a. factors determining the...
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A synthetic result of the development of personnel risk factors in the A, B, C, D enterprise
Dane BadawczeThe data below presents the shape of all the researched personnel risk factors in the A, B, C, D enterprise (which were tested by the author). Further considerations should be started with the presentation of the synthesis of the obtained results, which is presented in this research data.
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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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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublikacjaThe development of modern high-frequency structures, including microwave and antenna components, heavily relies on full-wave electromagnetic (EM) simulation models. Notwithstanding, EM-driven design entails considerable computational expenses. This is especially troublesome when solving tasks that require massive EM analyzes, parametric optimization and uncertainty quantification be-ing representative examples. The employment of...
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Simultaneous grouping and ranking with combination of SOM and TOPSIS for selection of preferable analytical procedure for furan determination in food
PublikacjaNovel methodology for grouping and ranking with application of self-organizing maps and multicriteria decision analysis is presented. The dataset consists of 22 objects that are analytical procedures applied to furan determination in food samples. They are described by 10 variables, referred to their analytical performance, environmental and economic aspects. Multivariate statistics analysis allows to limit the amount of input...
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Hanna Obracht-Prondzyńska dr inż. arch.
OsobyDr inż. arch. Hanna Obracht-Prondzyńska Adiunktka na Uniwersytecie Gdańskim w Zakładzie Gospodarki Przestrzennej, nauczycielka akademicka ucząca projektowania urbanistycznego i analizy danych. Architektka i urbanistka zajmującą się projektowaniem w oparciu o dane. Tytuł doktora nauk inżynieryjno-technicznych w dyscyplinie architektura i urbanistyka obroniła z wyróżnieniem w 2020 r. na Wydziale Architektury Politechniki Gdańskiej,...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging
PublikacjaUtilization of fast surrogate models has become a viable alternative to direct handling of fullwave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques...