Search results for: artificial intelligence - Bridge of Knowledge

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Search results for: artificial intelligence

Search results for: artificial intelligence

  • Case Study NEB Atlas / part II - Autodesk Forma analysis / Garnizon district in Gdansk, Poland

    Open Research Data
    embargo

    The data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....

  • Case Study NEB Atlas / part II - Autodesk Forma analysis / Seestadt Aspern, Vienna, Austria

    Open Research Data
    embargo

    The data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....

  • Case Study NEB Atlas / part II - Autodesk Forma analysis / Västra Hamnen, Malmö, Sweden.

    Open Research Data
    embargo

    The data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....

  • Case Study NEB Atlas / part II - Autodesk Forma analysis / Hammarby-Sjöstad, Stockholm, Sweden.

    Open Research Data
    embargo

    The data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....

  • Automatic Watercraft Recognition and Identification on Water Areas Covered by Video Monitoring as Extension for Sea and River Traffic Supervision Systems

    Publication

    - Polish Maritime Research - Year 2018

    The article presents the watercraft recognition and identification system as an extension for the presently used visual water area monitoring systems, such as VTS (Vessel Traffic Service) or RIS (River Information Service). The watercraft identification systems (AIS - Automatic Identification Systems) which are presently used in both sea and inland navigation require purchase and installation of relatively expensive transceivers...

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  • Global energy transition: From the main determinants to economic challenges regions

    Publication

    - EQUILIBRIUM Quarterly Journal of Economics and Economic Policy - Year 2023

    Dynamic global energy transition has been accelerating for the last decade. Interestingly, the energy transition is multidimensional and concerns both the dimensions of technique/ technology and the economic, social, institu-tional, and legal spheres (Shuguang et al., 2022; Tzeremes et al., 2022; Ram-zan et al., 2022; Tzeremes et al., 2022). The literature also points to the signif-icant impact of the digitization of the global...

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  • The impact of the AC922 Architecture on Performance of Deep Neural Network Training

    Publication

    - Year 2020

    Practical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...

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  • Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks

    Publication

    - IEEE Access - Year 2022

    Object detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...

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  • Optimisation of turbine shaft heating process under steam turbine run-up conditions

    Publication

    - Archives of Thermodynamics - Year 2020

    An important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...

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  • Błażej Prusak dr hab.

    Błażej Prusak is Head of the Department of Finance at the Faculty of Management and Economics, Gdansk University of Technology and Editor-in-Chief of the journal Research on Enterprise in Modern Economy - theory and practice (REME), as well as a member of editorial boards of such journals as Intellectual Economics; Space. Economics. Society; Academy of Management. He is the author or co-author of several scientific monographs including:...

  • Abdalraheem Ijjeh Ph.D. Eng.

    People

    The primary research areas of interest are artificial intelligence (AI), machine learning, deep learning, and computer vision, as well as modeling physical phenomena (i.e., guided waves in composite laminates). The research interests described above are utilized for SHM and NDE applications, namely damage detection and localization in composite materials.  

  • Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach

    Publication

    - Cancers - Year 2023

    Breast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...

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  • Comparison and Analysis of Service Selection Algorithms

    Publication

    - Year 2013

    In Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...

  • Spectrum-based modal parameters identification with Particle Swarm Optimization

    Publication

    - MECHATRONICS - Year 2016

    The paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....

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  • To Survive in a CBRN Hostile Environment: Application of CAVE Automatic Virtual Environments in First Responder Training

    Publication
    • P. Maciejewski
    • M. Gawlik-Kobylińska
    • J. Lebiedź
    • W. Ostant
    • D. Aydın

    - Year 2020

    This paper is of a conceptual nature and focuses on the use of a specific virtual reality environment in civil-military training. We analyzed the didactic potential of so-called CAVE automatic virtual environments for First Responder training, a type of training that fills the gap between First Aid training and the training received by emergency medical technicians. Since real training involves live drills based on unexpected situations,...

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  • Machine learning approach to packaging compatibility testing in the new product development process

    The paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...

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  • How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends

    Illegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....

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  • Metal–Organic Frameworks (MOFs) for Cancer Therapy

    Publication
    • M. Saeb
    • N. Rabiee
    • M. Mozafari
    • F. Verpoort
    • L. G. Voskressensky
    • R. Luque

    - Materials - Year 2021

    MOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...

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  • (eng)aging! 2021 Technologies for Active and Independent Living in Old Age in V4

    Projects

    Project manager: dr inż. Adam Kaczmarek   Financial Program Name: Międzynarodowy Fundusz Wyszehradzki

    Project realized in Department of Intelligent Interactive Systems according to 22020301/1 agreement from 2021-01-08

  • Ontology-Aided Software Engineering

    Publication

    - Year 2012

    This thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...

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  • How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?

    Publication

    - Year 2023

    Electrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...

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  • Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm

    Publication

    This paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...

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  • Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych

    Automation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...

  • Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych

    Automation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...

  • Predicting emotion from color present in images and video excerpts by machine learning

    Publication

    This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

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  • Explainable machine learning for diffraction patterns

    Publication
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Year 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

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  • Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems

    Publication
    • A. Kwaśniewska
    • S. Raghava
    • C. Davila
    • M. Sevenier
    • D. Gamba
    • J. Rumiński

    - Year 2022

    The rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...

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  • Condition-Based Monitoring of DC Motors Performed with Autoencoders

    Publication

    - Year 2022

    This paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...

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  • Neural network training with limited precision and asymmetric exponent

    Publication

    Along 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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  • Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover

    Publication

    The process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...

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  • Smart metering - social risk perception and risk governance (10h, 2 ECTS credits)

    e-Learning Courses
    • M. Galik
    • A. Klej

    The goal of the course is to broaden the understanding of technology-related risks and to present the concepts of social risk perception and risk governance in the context of smart metering technology. In current phase of technological development – known as the fourth industrial revolution – rapid and profound changes are setting up new and particularly destabilizing risks. In more and more complex technological systems that constitute...

  • Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

    Publication
    • S. Donghui
    • L. Zhigang
    • J. Zurada
    • A. Manikas
    • J. Guan
    • P. Weichbroth

    - KNOWLEDGE AND INFORMATION SYSTEMS - Year 2024

    The construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...

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  • Tomasz Korol dr hab. inż.

    Education Gdańsk University of Technology, Faculty of Management and Economics (2001) University of Applied Sciences Stralsund (1999) Degree / scientific title Habilitation – Gdańsk University of Technology, Faculty of Management and Economics (2015) Ph.D. – Gdańsk University of Technology, Faculty of Management and Economics (2004) Employment Gdańsk University of Technology - associate professor (since 2017); assistant professor...

  • ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda

    Publication
    • E. Loukis
    • S. Saxena
    • N. Rizun
    • M. I. Maratsi
    • M. Ali
    • C. H. Alexopoulos

    - Year 2023

    As a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...

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  • Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling

    Publication

    - Scientific Reports - Year 2023

    Over the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...

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  • Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea

    The operation of offshore structures at sea requires the implementation of advanced systems for their permanent monitoring. There is a set of novel technologies that could be implemented to deliver a higher level of effective and safe operation of these systems. A possible novel solution may be the application of a new maritime unmanned (USV) surface and underwater vehicles/platforms (AUV). Application of such vehicles/platforms...

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  • Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review

    Publication

    - ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING - Year 2024

    Fiber-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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  • The potential interaction of environmental pollutants and circadian rhythm regulations that may cause leukemia

    Publication
    • F. A. Lagunas-Rangel
    • B. Kudłak
    • W. Liu
    • M. Williams
    • H. B. Schiöth

    - CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY - Year 2022

    Tumor suppressor genes are highly affected during the development of leukemia, including circadian clock genes. Circadian rhythms constitute an evolutionary molecular machinery involving many genes, such as BMAL1, CLOCK, CRY1, CRY2, PER1, PER2, REV-ERBa, and RORA, for tracking time and optimizing daily life during day-night cycles and seasonal changes. For circulating blood cells many of these genes coordinate their proliferation,...

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  • How Machine Learning Contributes to Solve Acoustical Problems

    Publication
    • M. A. Roch
    • P. Gerstoft
    • B. Kostek
    • Z. Michalopoulou

    - Journal of the Acoustical Society of America - Year 2021

    Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...

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  • Arsalan Muhammad Soomar Doctoral Student

    People

    Hi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan.  Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio  as a Solar Design Engineer.   HEADLINE Currently Enrolled as a Doctoral...

  • Interactive Decision Making, Inżynieria Środowiska, Environmental Engineering, 2023/2024 (summer semester)

    e-Learning Courses
    • A. Jakubczyk-Gałczyńska
    • A. Siemaszko

    The course is designed for students of MSc Studies in Environmental Engineering (studies in Polish and English) Person responsible for the subject, carrying out lectures and tutorials: mgr inż. Agata.Siemaszko; agata.siemaszko@pg.edu.pl The person conducting the lectures and tutorials: dr inż. Anna Jakubczyk-Gałczyńska; anna.jakubczyk@pg.edu.pl The course is conducted using the Project-Based Learning (PBL) method. It provides...

  • Adam Dąbrowski dr inż.

    People

    Adam Dabrowski has obtained a PhD in mechanical engineering from Gdańsk University of Technology and MSc. degree in mechatronics from Technische Universität Hamburg. He has an industry experience in Institute of Aviation Engineering Design Center (Warsaw, Poland) and SICK AG (Hamburg, Germany). Additionally, as an assistant at Gdansk University of Technology he teaught courses on mechanics, space mechanisms and dynamics of space...

  • Łukasz Szeremeta

    People

    My current research areas are issues related to the Property Graphs, Cheminformatics and Semantic Web. I am also interested in the latest applications of Artificial Intelligence.

  • Bożena Kostek prof. dr hab. inż.

  • Enhancing Customer Engagement in Social Media with AI – a Higher Education case study

    Publication

    - Year 2022

    Purpose. The study aims to demonstrate the importance of artificial intelligence (AI) and examples of tools based on it in the process of enhancing (building, measuring, and managing) customer engagement (CE) in social media in the higher education industry. CE is one of the current essential non-financial indicators of company performance in Digital Marketing strategy. The article presents a decision support system (DSS) based...

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  • Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

    In this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...

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  • Forecasting risks and challenges of digital innovations

    Publication

    - Year 2020

    Forecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...

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  • Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale

    Publication
    • K. Mikołajewski
    • M. Ruman
    • K. Kosek
    • M. Glixelli
    • P. Dzimińska
    • P. Ziętara
    • P. Licznar

    - SCIENCE OF THE TOTAL ENVIRONMENT - Year 2022

    Despite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....

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  • The Impact of Generative AI and ChatGPT on Creating Digital Advertising Campaigns

    Publication

    The use of AI-based solutions is currently discussed in relation to various industries. The proliferation of tools based on generative artificial intelligence (GAI), including the emergence of ChatGPT, has resulted in testing as a first step and implementations in further areas of business life, including marketing, as a second step. Still only a few studies have analysed and evaluated specific solutions for different areas of...

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  • Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?

    Publication

    - Year 2023

    Open 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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