Wyniki wyszukiwania dla: E-LEARNING - MOST Wiedzy

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Wyniki wyszukiwania dla: E-LEARNING

Wyniki wyszukiwania dla: E-LEARNING

  • Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech

    Publikacja
    • D. Korzekwa
    • R. Barra-Chicote
    • B. Kostek
    • T. Drugman
    • M. Łajszczak

    - Rok 2019

    We present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...

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  • Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence

    Research, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...

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  • Physical models in the education of architectural history

    In this article, the authors present the long tradition and common use of physical models in the process of teaching the history of architecture in higher education institutions. The research described in the article is focused on the use of physical models and mock-ups as stimulants during architectural history classes to support lectures and increase the learning capabilities of students. The authors also cover the general use...

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  • Neural networks and deep learning

    Publikacja

    - Rok 2022

    In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

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  • Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning

    Publikacja

    - PLOS ONE - Rok 2022

    In this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...

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  • Comparative Analysis of Text Representation Methods Using Classification

    Publikacja

    In our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...

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  • Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy

    Publikacja

    - Rok 2018

    The diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...

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  • Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble

    This paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...

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  • Psychological capital and happiness at work: The mediating role of employee thriving in multinational corporations

    Publikacja

    - CURRENT PSYCHOLOGY - Rok 2022

    Working in multicultural work environments of multinational corporations (MNCs) creates challenges whose expected impact on happiness is equivocal. In the following paper, we examine the relationship between psychological capital and happiness at work in the specific MNCs’ context. We assume that thriving (eudemonic well-being) at work fosters individuals’ development and enhances their happiness composed of both the affective...

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  • Assessing the attractiveness of human face based on machine learning

    Publikacja

    The attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...

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  • Empirical analysis of tree-based classification models for customer churn prediction

    Publikacja
    • F. E. Usman-Hamza
    • A. O. Balogun
    • S. K. Nasiru
    • L. F. Capretz
    • H. A. Mojeed
    • S. A. Salihu
    • A. G. Akintola
    • M. A. Mabayoje
    • J. B. Awotunde

    - Scientific African - Rok 2023

    Customer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...

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  • Leadership, culture, intellectual capital and knowledge processes for organizational innovativeness across industries: the case of Poland

    Purpose – This study aims to present the overview of intellectual capital creation micro-mechanisms concerning formal and informal knowledge processes. The organizational culture, transformational leadership and innovativeness are also included in the investigation as ascendants and consequences of the focal relation of intellectual capital and knowledge processes. Design/methodology/approach – Based on a sample of 1,418 Polish...

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  • Factors Affecting the Effectiveness of Military Training in Virtual Reality Environment

    Publikacja
    • M. Gawlik-Kobylińska
    • P. Maciejewski
    • J. Lebiedź
    • A. Wysokińska-Senkus

    - Rok 2020

    In this paper, we explored the factors influencing the effectiveness of military trainings performed in a virtual reality environment. The rationale for taking up the topic is the fact that such trainings are often conducted under specific operational procedures. These procedures may create rigorous frameworks for all elements of the learning environment, including the teacher’s performance. Therefore, to ensure the most conducive...

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  • POSITIVE PSYCHOLOGICAL CAPITAL ENHANCES THRIVING IN THE MULTICULTURAL WORK ENVIRONMENT OF MULTINATIONAL CORPORATIONS

    Publikacja

    - Rok 2016

    The aim of the paper is to examine positive psychological capital (PsyCap) as well as individual factors in the relationship with thriving in the multicultural work environment of multinational corporations (MNCs). We conducted a quantitative study on the sample of 127 individuals from subsidiaries of various MNCs located in Poland and involved in intercultural interactions. The results of cross-sectional study show that employees...

  • An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key

    Publikacja

    - Rok 2019

    The topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...

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  • Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms

    Lymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...

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  • Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation

    Publikacja

    - Rok 2023

    Machine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...

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  • Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?

    Publikacja

    - Rok 2022

    In this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...

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  • Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition

    Publikacja

    - Biomedical Signal Processing and Control - Rok 2023

    Brain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....

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  • TWO-SHAFT GAS TURBINE TEACHING AND TESTING STATION

    Publikacja

    The station was established as part of a project co-financed by the European Union with the funds of the European Regional Development Fund as part of the Infrastructure and Environment Operational Programme titled: “Establishment of state-of-the-art technical infrastructure for the Engineers of the Future learning programme at the Gdańsk University of Technology” executed in 2013-2015.

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  • Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise

    Publikacja

    Purpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...

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  • Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective

    Publikacja

    Purpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...

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  • PSYCHOLOGICAL CAPITAL AND CHALLENGE APPRAISAL FOSTER THRIVING IN THE GLOBALIZED MULTICULTURAL WORKPLACE

    Publikacja

    - Rok 2016

    The purpose of the study was to examine the psychological resources which foster thriving in multicultural work settings of multinational corporations (MNCs) - the companies that are evident manifestation of globalization. Although globalized multicultural workplace creates specific job demands that pose unique occupational stress to individuals, some personal resources enable them to deal with these demands and to thrive. Thriving...

  • MOODLE MOOCS - PRZYPADKI UŻYCIA W PROJEKCIE SP4CE (PARTNERSTWO STRATEGICZNE NA RZECZ KREATYWNOŚCI I PRZEDSIĘBIORCZOŚCI)

    Projekt SP4CE (Partnerstwo strategiczne na rzecz kreatywności i przedsiębiorczości) jest odpowiedzią na potrzeby zidentyfikowane w komunikacie z Brugii w sprawie ściślejszej europejskiej współpracy w dziedzinie kształcenia i szkolenia zawodowego w latach 2011 - 2020. Do realizacji portalu SP4CE wykorzystano oprogramowanie WordPress i Moodle. WordPress wykorzystano m.in. do udostępnienia materiałów informacyjnych oraz szkoleniowych...

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

    Publikacja

    - Cancers - Rok 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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  • A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study

    Publikacja
    • S. Yang
    • Z. He
    • J. Chai
    • D. Meng
    • W. Macek
    • R. Branco
    • S. Zhu

    - Structures - Rok 2023

    This study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...

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  • Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models

    Publikacja

    - Rok 2023

    Breast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...

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  • Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE)

    Dane Badawcze
    open access

    Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium...

  • Investigating Feature Spaces for Isolated Word Recognition

    Publikacja
    • P. Treigys
    • G. Korvel
    • G. Tamulevicius
    • J. Bernataviciene
    • B. Kostek

    - Rok 2020

    The study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...

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  • Novel approach to ecotoxicological risk assessment of sediments cores around the shipwreck by the use of self-organizing maps

    Publikacja

    - ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY - Rok 2014

    Marine and coastal pollution plays an increasingly important role due to recent severe accidents which drew attention to the consequences of oil spills causing widespread devastation of marine ecosystems. All these problems cannot be solved without conducting environmental studies in the area of possible oil spill and performing chemometric evaluation of the data obtained looking for similar patterns among pollutants and optimize...

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  • Bridging theory and practice in postgraduate education on development and planning: Gdynia Urban Summer Schools 2016-2018

    In this article, the authors discuss results achieved by the Gdynia Urban Summer School (GUSS) organised annually (between 2016 and 2018) in Gdynia, Poland. The GUSS was meant for young practitioners from various professions such as urban and regional planning, urban design, architecture, civil engineering and transport planning. The objective was to give workshop participantspractical interdisciplinary...

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  • The Neural Knowledge DNA Based Smart Internet of Things

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2020

    ABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...

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  • User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning

    Publikacja

    - SENSORS - Rok 2024

    In this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...

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  • LOS and NLOS identification in real indoor environment using deep learning approach

    Visibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...

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  • Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

    Publikacja

    - Applied Sciences-Basel - Rok 2023

    Background: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...

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  • Projektowanie środowiskowe - edukacja architektoniczna

    Publikacja

    - Rok 2009

    Przedstawiono krytykę obecnej edukacji architektonicznej oraz dyskusję nad kierunkami jej zmian. Omówiono dokumenty międzynarodowych organizacji zajmujących się teoria i praktyką edukacji architektonicznej ze szczególnym uwzględnieniem edukacji w zakresie projektowania środowiskowego oraz systemów samoksztalcenia (learning to learn) i kształcenia ustawicznego.

  • Mobile Activity Plan Applications for Behavioral Therapy of Autistic Children

    This paper concerns technological support for behavioral therapy of autistic children. A family of tools dedicated for mobile devices is presented, that allows to design and perform an activity schedule in behavioral therapy. The paper describes the main challenges, that were encountered, especially in meeting the non-functional requirements of the application: simplicity, repeatability, robustness, personalization, re-usability...

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  • Machine Learning and Electronic Noses for Medical Diagnostics

    Publikacja

    The need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...

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  • Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks

    Publikacja

    - CMC-Computers Materials & Continua - Rok 2020

    The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...

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  • From Knowledge based Vision Systems to Cognitive Vision Systems: A Review

    Publikacja

    - Rok 2018

    Computer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...

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  • WebCT - platforma i tłumaczenie.

    Publikacja

    W artykule przedstawiono doświadczenia Centrum Edukacji Niestacjonarnej i Międzywydziałowego Koła Naukowego Studentów Politechniki Gdańskiej DEC@TUG w tłumaczeniu i implementacji platform LMS (ang. Learning Management System). Krótko scharakteryzowano funkcjonalność platform BSCW I Moodle, których interfejsy zostały przetłumaczone przez członków Koła DEC@TUG w latach 2000-2003. Opisano główne funkcje platformy WebCT, takie jak...

  • Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.

    Publikacja

    - Rok 2005

    W referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...

  • Deep learning for ultra-fast and high precision screening of energy materials

    Publikacja
    • Z. Wang
    • Q. Wang
    • Y. Han
    • Y. Ma
    • H. Zhao
    • A. Nowak
    • J. Li

    - Energy Storage Materials - Rok 2021

    Semiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...

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  • Smart Knowledge Engineering for Cognitive Systems: A Brief Overview

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2022

    Cognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...

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  • BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION

    Publikacja

    - Rok 2018

    The following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...

  • Creating a radiological database for automatic liver segmentation using artificial intelligence.

    Publikacja

    - EJSO-EUR J SURG ONC - Rok 2022

    Imaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.

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  • COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)

    Publikacja

    - Rok 2020

    Collaborative Learning Environment for Engineering Education is a European project implemented under the Erasmus + program, The main goal of 5 partners from 4 different European countries – Bulgaria, Poland, Portugal and Romania is to develop an innovative collaborative training approach, encompassing curricula related to the introduction of enterprise automation. Project activities are carried out in the period from Dctober 2018...

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  • Tomasz Deręgowski dr inż.

    Osoby

    Tomasz Deręgowski jest adiunktem w Katedrze Informatyki w Zarządzaniu na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej, oraz kierownikiem Departamentu Inżynierii Platform Danych, pracującego nad rozwiązaniami Big Data, uczenia maszynowego i inżynierii danych w Nordea Bank AB - największej Skandynawskiej instytucji finansowej. Wcześniej pracował przez 15 lat w branży IT  jako programista, lider zespołu, kierownik programu...

  • A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings

    Publikacja

    Traffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...

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  • Predictions of cervical cancer identification by photonic method combined with machine learning

    Publikacja
    • M. Kruczkowski
    • A. Drabik-Kruczkowska
    • A. Marciniak
    • M. Tarczewska
    • M. Kosowska
    • M. Szczerska

    - Scientific Reports - Rok 2022

    Cervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...

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