Search results for: DATA-DRIVEN DECISION TECHNIQUES
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Data and knowledge supporting decision-making for the urban Food-Water-Energy nexus
PublicationCities 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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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject 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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Direct Constraint Control for EM-Based Miniaturization of Microwave Passives
PublicationHandling 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
PublicationThe 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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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
PublicationOpen 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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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
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublicationDesign 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
PublicationTe 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.
PublicationSzybkość 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.
PublicationW 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
PublicationPurpose 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
PublicationThe 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.
PeopleBorn on April 7, 1984 in Gdańsk. In 2012, he defended his doctorate with honors, in 2017 he obtained his habilitation on the basis of the scientific achievement "Development of analytical procedures and solvents for the assessment of environmental nuisance". He has been working at the Department of Analytical Chemistry since 2012. His research interests includes analytical chemistry, especially the analytics of organic compounds...
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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
PeopleHead of the Scientific and Technical Information Services at the Gdansk University of Technology Library and the Leader of the Open Science Competence Center. She is also a Plenipotentiary of the Rector of the Gdańsk University of Technology for open science. She is a PhD Candidate. Her main areas of research and interests include research productivity, motivation, management of HEs, Open Access, Open Research Data, information...
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Decisional DNA and Optimization Problem
PublicationMany 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.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
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Nina Rizun dr
PeopleNina Rizun is an assistant professor at the Faculty of Management and Economics at the Gdańsk University of Technology. In October 1999 she obtained a PhD degree in technical sciences in the Faculty of Enterprise Economy and Production Organization, National Mining Academy, Dnipropetrovsk, Ukraine. PhD thesis title: Development of Complex Subsystem of the Organization and Planning of Mining and Transport Processes. In the years...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis 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
PublicationClinical 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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Internal legal acts of technical and medical universities in Poland regulating classes conducted in-person during the Covid-19 pandemic
Open Research DataA 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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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe 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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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationDesign 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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IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Electrical responses of nanostructured ZrS3 as field-effect transistor for nitrogen dioxide, ethanol, and acetone detection enhanced by visible light
Open Research DataSmall-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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Expedited Variable-Resolution Surrogate Modeling of Miniaturized Microwave Passives in Confined Domains
PublicationDesign 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
PublicationThis 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
PublicationAn 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
PublicationContext 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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Knowledge management driven leadership, culture and innovation success – an integrative model
PublicationPurpose – 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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Neural network training with limited precision and asymmetric exponent
PublicationAlong 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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Electrochemical data for carbonized metal-organic framworks with cobalt
Open Research DataThe 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
PublicationElectromagnetic (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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Individual corporate reputation, perception of collective corporate reputation, stock market investments
Open Research DataThere 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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Hazard Control in Industrial Environments: A Knowledge-Vision-Based Approach
PublicationThis 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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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublicationCost 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
Open Research DataThe 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
Open Research DataThe 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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Hanna Obracht-Prondzyńska dr inż. arch.
PeopleHanna Obracht-Prondzyńska, PhD MArch, Eng. Assistant Professor at the University of Gdańsk, Department of Spatial Management, academic teacher of urban design and spatial data analyses. Architect and urban planner experienced in data driven urban design and planning. She defended her PhD with distinction in engineering and technical sciences in the discipline of architecture and urban planning in 2020 at the Faculty of Architecture...
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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationThe 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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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublicationIn 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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Macroeconomic Reports - Nowy
e-Learning CoursesThis 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.