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Search results for: data driven planning
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The Use of Big Data in Regenerative Planning
PublicationWith the increasing significance of Big Data sources and their reliability for studying current urban development processes, new possibilities have appeared for analyzing the urban planning of contemporary cities. At the same time, the new urban development paradigm related to regenerative sustainability requires a new approach and hence a better understanding of the processes changing cities today, which will allow more efficient...
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Fundamentals of Data-Driven Surrogate Modeling
PublicationThe 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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Dis/Trust and data-driven technologies
PublicationThis 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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Multilevel pharmacokinetics-driven modeling of metabolomics data
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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics
PublicationData-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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Improved Uniform Sampling in Constrained Domains for Data-Driven Modelling of Antennas
PublicationData-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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Integrating modelling, simulation and data management tools to create a planning support system for the improvement of air quality by urban planning solutions
PublicationThe urbanization pressure requires urban planners, designers, and policy makers to be more responsive to the challenges related to improving the quality of the urban environment and the living conditions of the inhabitants. One of the many environmental issues that need to be taken into account is urban air pollution. As the process of urban ventilation and air pollution dis-persion is significantly affected by the urban layout,...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublicationFull-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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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn 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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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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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-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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Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublicationWide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn 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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA 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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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis 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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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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis 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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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublicationDesign 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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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublicationArticle 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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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel 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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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen 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
PublicationData-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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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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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublicationFast 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 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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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publication3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
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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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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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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Dorota Dominika Kamrowska-Załuska dr hab. inż. arch.
PeopleProf. Dorota Kamrowska-Zaluska, architect and urban planner, Associate Professor and Director of mid-career program on Urban development and management of metropolitan areas, at the Department of Urban Design and Regional Planning at Faculty of Architecture, Gdansk University of Technology; Visiting Scholar and Research Fellow at several research institutions incl. Massachusetts Institute of Technology (2013), Charted Urban Planner...
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Natalia Sokół dr inż.
PeopleBACKGROUND Master of Science in Light and Lighting (2008-2009/11) The UCL Bartlett School of Graduate Studies, Faculty of the Built Environment, London, UK, www.bartlett.ucl.ac.uk MA Degree in Interior Architecture (1999-2004), The Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl MA Degree in Art Education (1997-2002), Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl MAIN RESEARCH AREAS · ...
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David Duenas Cid dr hab.
PeopleHe is an Associate Professor at Kozminski University and the director of the Pub-Tech (Public Sector Data-Driven Technologies) Research Center. Previously, he served as an H2020 Marie Skłodowska-Curie Widening Fellow at Gdansk University of Technology, as a Researcher at the Johan Skytte Institute of Political Studies of the University of Tartu, as a Postdoctoral Researcher at the Ragnar Nurkse Department of Innovation and Governance...
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Small Urban Hacks - Big Impact! Tackling major urban challenges through acupunctural smallness
PublicationSmall urban hacks, acupunctural action and process-oriented planning approaches might appear to address quite a socio-romantic attitude towards our urban environments. In this chapter, our aim is to remedy such a biased view, demonstrating the impact and potential of smallness in the context of major urban challenges. Small urban hacks and their multi-faceted and creativity-driven approaches of small is beautiful are selected from...
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Hossein Nejatbakhsh Esfahani Dr.
PeopleMy research interests lie primarily in the area of Learning-based Safety-Critical Control Systems, for which I leverage the following concepts and tools:-Robust/Optimal Control-Reinforcement Learning-Model Predictive Control-Data-Driven Control-Control Barrier Function-Risk-Averse Controland with applications to:-Aerial and Marine robotics (fixed-wing UAVs, autonomous ships and underwater vehicles)-Multi-Robot and Networked Control...
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Stefan Niewitecki dr inż. arch.
PeopleW dniu 29.07.1977 r. ukończenie Studium Podyplomowego Kształcenia Pedagogicznego Nauczycieli Akademickich (świadectwo Nr 301, wynik dobry). Dnia 29.04.1982 r. nagroda III stopnia Rektora Politechniki Gdańskiej, zespołowa za ''Studium wpływu ujęcia wody Gdańsk-Lipce na stateczność obiektów budowlanych w rejonie leja depresyjnego.'' W 1986 r. nagroda Rektora Politechniki Gdańskiej za ''Orzeczenie i projekt techniczny wzmocnienia...
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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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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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High Rise Building: The Mega Sculpture Made Of Steel, Concrete and Glass
PublicationHigh rise building has transformed from providing not only the expansion of floor space but functioning as mega sculpture in the city. The shift away from economic efficiency driven need is only expected to grow in the future. Based on literature studies; after analysing planning documents and case studies, it was examined whether the presumption that gaining the maximum amount of usable area is the only driving factor; or if the...
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Izabela Mironowicz dr hab. inż. arch.
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Mohsan Ali Master of Science in Computer Science
PeopleMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Syntetyczne wskaźniki oceny stanu toru
PublicationJakość geometryczna toru analizowana jest w różnych celach, a dane podlegają różnemu stopniowi agregacji. Pojedyncze nierówności toru analizowane są zazwyczaj z uwagi na bezpieczeństwo i służą do planowanie napraw w krótkich terminach. Natomiast agregacja pomierzonych parametrów pozwala na planowanie robót w terminach średniookresowych i budowę modeli predykcji. W artykule przedstawiono zagregowane wskaźniki jakości geometrycznej...
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Numerical Solution of the Two-Dimensional Richards Equation Using Alternate Splitting Methods for Dimensional Decomposition
PublicationResearch on seepage flow in the vadose zone has largely been driven by engineering and environmental problems affecting many fields of geotechnics, hydrology, and agricultural science. Mathematical modeling of the subsurface flow under unsaturated conditions is an essential part of water resource management and planning. In order to determine such subsurface flow, the two-dimensional (2D) Richards equation can be used. However,...
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Wykorzystanie systemu komputerowego ALEP-PL w planowaniu rozwoju lokalnych systemów energetycznych
PublicationZaprezentowano autorski system komputerowy ALEP-PL, który wspomaga proces planowania rozwoju lokalnych systemów energetycznych. Narzędzie zostało przygotowane z uwzględnieniem metodyki planowania zaawansowanego. System składa się z serwisu internetowego, bazy danych i modułów logiki biznesowej. Serwis internetowy został stworzony w technologii ASP.NET z użyciem środowiska Visual Studio 2010 i serwera baz danych MS SQL Server 2008...
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Dominika Wróblewska dr inż. arch.
PeopleDr. Eng. arch. Dominika Wróblewska, university professor, obtained the title of doctor of technical sciences in 2000. In 2002, she started working at the Faculty of Hydro and Environmental Engineering at the Gdańsk University of Technology (currently the Faculty of Civil and Environmental Engineering) as an assistant professor. Since 2019, he has been working as a university professor. The areas of interest are changes, introducing...
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Koncepcja systemu wspomagania decyzji nawigatora statku opartego na ewolucyjnym planowaniu manewrów antykolizyjnych
PublicationArtykuł przedstawia koncepcję systemu wspomagania decyzji nawigatora statku opartego na wątkach badań prowadzonych wcześniej przez autora. System będzie rozszerzał funkcjonalność systemów dotychczasowych o możliwość szczegółowego planowania bezpiecznej trajektorii statku na wodach zamkniętych, z dużą liczbą statków obcych i ograniczeniami toru wodnego. Artykuł zawiera dyskusję możliwych podejść do planowania manewrów, optymalizacji...
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Piotr Lorens prof. dr hab. inż. arch.
PeopleProf. Piotr Lorens - PhD, DSc., urban planner. Lecturer in urban design and development and - since 2007 - Head of the Department of Urban Design and Regional Planning at the Faculty of Architecture, Gdansk University of Technology. His university activities also include coordination of the research and EU Social Fund projects. Based on these projects he was responsible for organization and coordination of the post-graduate studies...