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    Wyświetlanie 1-12 z 12
    Tytuł:
    Educating epistemological principles, virtues and research skills. Review on Marina Klimenko’s textbook “Research Methods in the Social Sciences”
    Autorzy:
    Nowak, Ewa
    Powiązania:
    https://bibliotekanauki.pl/articles/1393967.pdf
    Data publikacji:
    2021-08-17
    Wydawca:
    Uniwersytet im. Adama Mickiewicza w Poznaniu
    Tematy:
    research excellence
    scientific and research virtues
    promoting students’ research competence
    investigative psychology
    advances in psychological education
    M. Klimenko’s textbook Research Methods in the Social Sciences
    science-based learning
    Opis:
    Improving university students’ research skills, research integrity and best standards for scientific excellence is crucial for all disciplines. Marina Klimenko, a senior lecturer at the Universi-ty of Florida, developed an innovative digital textbook entitled Research Methods in the Social Sciences (2020) with the focus on investigative psychology. The edition was powered by the e-learn-ing portal and published by Sentia Publishing. The author’s own epistemological and research expertise is combined here with her competence in higher education didactics. Klimenko’s textbook seems to be perfectly tailored for prospective researchers – and useful for various disciplines representing the social sciences and humanities.
    Źródło:
    Filozofia Publiczna i Edukacja Demokratyczna; 2020, 9, 1; 66-77
    2299-1875
    Pojawia się w:
    Filozofia Publiczna i Edukacja Demokratyczna
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Inquiry based learning in science education and mathematics for developing bilinguals
    Autorzy:
    Pavlova, Nataliya H.
    Marchev, Dragomir V.
    Borisov, Borislav St.
    Harizanov, Krasimir V.
    Powiązania:
    https://bibliotekanauki.pl/articles/628413.pdf
    Data publikacji:
    2015
    Wydawca:
    Fundacja Pro Scientia Publica
    Tematy:
    developing bilinguals, inquiry-based learning, science education, teachers
    Opis:
    This article studies the problem of teaching bilingual children. A definition of “developing bilingual” is proposed. The article presents an example of the application of inquiry based learning through which students develop not only math skills but also lexical capabilities. This study offers levels of differentiation in different groups of students. The paper determines advantages and disadvantages of the use of Inquiry Based Learning in developing bilingual groups.
    Źródło:
    Journal of Education Culture and Society; 2015, 6, 1; 65-74
    2081-1640
    Pojawia się w:
    Journal of Education Culture and Society
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Developing Scientific Work Practice in Business Informatics - Digital Support for a Design Science-based Research Project
    Autorzy:
    Stary, Christian
    Powiązania:
    https://bibliotekanauki.pl/articles/426363.pdf
    Data publikacji:
    2019
    Wydawca:
    Szkoła Główna Handlowa w Warszawie
    Tematy:
    scientific work
    research practice
    research proposal
    design science
    learning support
    social interaction
    self-managed learning
    cognitive apprenticeship
    scaffolding
    learning management
    Opis:
    When academic students are introduced to scientific work, they need to become familiar with how to select a research topic, to identify research goals, and to structure a research project accordingly. In Business Informatics, research practice is increasingly following a design science approach. In this contribution, we introduce a corresponding digital support scheme. It is based on cognitive apprenticeship and scaffolding to specify the research questions and derive requirements from a problem statement for possible solutions. Learners are supported in a socio-cognitive way, as the set of digital learning-support features comprises peer-to-peer interactions, content co-construction, and a portfolio-like documentation scheme. Context-sensitive (focused) interaction and organizing group work facilitate content co-creation and effective information sharing. They support self-managed scientific skill development while being able to follow structured research procedures.
    Źródło:
    e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie; 2019, 5 (82); 4-17
    1731-6758
    1731-7428
    Pojawia się w:
    e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Barriers in Distance Education Based on the Example of Computer Science Studies
    Autorzy:
    Krupski, M.
    Cader, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/108678.pdf
    Data publikacji:
    2011
    Wydawca:
    Społeczna Akademia Nauk w Łodzi
    Tematy:
    distance education
    information tools
    e-learning quality
    Opis:
    The following work briefly presents a research project that aims at identifying barriers obstructing distance education. The research was conducted on the overall number of 158 distance students. The comparative group consisted of 430 traditional students. The attention was focused on the problems associated with Internet studies and there was a comparative analysis conducted on the perception of described factors by e-learning and traditional students (day and weekend studies). The results suggest that factors commonly perceived as the main disadvantages of distance studies are not more onerous than for traditional students.
    Źródło:
    Journal of Applied Computer Science Methods; 2011, 3 No. 1; 47-65
    1689-9636
    Pojawia się w:
    Journal of Applied Computer Science Methods
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A cough-based COVID-19 detection system using PCA and machine learning classifiers
    Autorzy:
    Benmalek, Elmehdi
    Mhamdi, Jamal El
    Jilbab, Abdelilah
    Jbari, Atman
    Powiązania:
    https://bibliotekanauki.pl/articles/38431179.pdf
    Data publikacji:
    2022
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    COVID-19
    cough recordings
    machine learning
    PCA
    classification
    Opis:
    In 2019, the whole world is facing a health emergency due to the emergence of the coronavirus (COVID-19). About 223 countries are affected by the coronavirus. Medical and health services face difficulties to manage the disease, which requires a significant amount of health system resources. Several artificial intelligence-based systems are designed to automatically detect COVID-19 for limiting the spread of the virus. Researchers have found that this virus has a major impact on voice production due to the respiratory system's dysfunction. In this paper, we investigate and analyze the effectiveness of cough analysis to accurately detect COVID-19. To do so, we per-formed binary classification, distinguishing positive COVID patients from healthy controls. The records are collected from the Coswara Dataset, a crowdsourcing project from the Indian Institute of Science (IIS). After data collection, we extracted the MFCC from the cough records. These acoustic features are mapped directly to the Decision Tree (DT), k-nearest neighbor (kNN) for k equals to 3, support vector machine (SVM), and deep neural network (DNN), or after a dimensionality reduction using principal component analysis (PCA), with 95 percent variance or 6 principal components. The 3NN classifier with all features has produced the best classification results. It detects COVID-19 patients with an accuracy of 97.48 percent, 96.96 percent f1-score, and 0.95 MCC. Suggesting that this method can accurately distinguish healthy controls and COVID-19 patients.
    Źródło:
    Applied Computer Science; 2022, 18, 4; 96-115
    1895-3735
    2353-6977
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Teoria wielostronnego kształcenia osobowości podstawą sytuacji edukacyjnych z informatyki w gimnazjum
    Theory Multilateral Education of Personality Based on Educationally Situations of Computer Science Learning in Junior High School
    Autorzy:
    Miterka, Elżbieta
    Powiązania:
    https://bibliotekanauki.pl/articles/1811105.pdf
    Data publikacji:
    2015
    Wydawca:
    Katolicki Uniwersytet Lubelski Jana Pawła II. Towarzystwo Naukowe KUL
    Tematy:
    sytuacja edukacyjna
    teoria wielostronnego kształcenia
    proces nauczania--uczenia się informatyki w gimnazjum
    model mobilnego kształcenia
    educational situation
    multilateral theory of education
    the process of teaching-learning of computer science in junior high school
    the model of mobile learning
    Opis:
    Artykuł prezentuje podstawy procesu kształcenia informatycznego dla III etapu edukacyjnego w świetle teorii wielostronnego kształcenia osobowości i sytuacji edukacyjnych, które mogą stanowić fundament w procesie jego realizacji. Teoria ta, opierając się na złożonym procesie rozwoju człowieka, dokonującym się pod wpływem kształcenia, traktuje wychowanka i jego osobowość jako harmonijną całość, której kształcenie następuje poprzez rozbudzanie i rozwijanie zdolności poznawczych, motywacji i życia uczuciowego oraz zdolności do twórczej działalności praktycznej. Efektem takiego procesu nauczania-uczenia się jest spójnie ukształtowana osobowość ucznia, gotowa na wybór i przyswajanie dostępnych informacji, jak i rozwiązywanie zagadnień teoretycznych i praktycznych, a zarazem przeżywająca treści naukowe, społeczne, moralne i estetyczne oraz biorąca czynny udział w przekształcaniu otaczającej rzeczywistości.
    Article presents the theoretical foundations of computer education process for the third stage of education in the light of the theory multilateral education of personality and educationally situations that can be the foundation in the process of computer science learning. This theory is based on the complex process of human development, maked under the influence of education with treats juvenile and his personality as a harmonious whole, which education takes through the awakening and development of cognitive skills, motivation and emotional life and the ability to creative practical activity. The result of such a process of teaching-learning is consistently shaped the personality of the student, ready for selection and assimilation of available information and solving theoretical and practical problems, surviving scientific content, social, moral, and aesthetic and taking an active part in the transformation of the surrounding reality.
    Źródło:
    Roczniki Pedagogiczne; 2015, 7(43), 2; 23-38
    2080-850X
    Pojawia się w:
    Roczniki Pedagogiczne
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Machine learning-based business rule engine data transformation over high-speed networks
    Autorzy:
    Neelima, Kenpi
    Vasundra, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/38700094.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Podstawowych Problemów Techniki PAN
    Tematy:
    CRISP-DM
    data mining algorithms
    business rule
    prediction
    classification
    machine learning
    deep learning
    AI design
    algorytmy eksploracji danych
    reguła biznesowa
    prognoza
    klasyfikacja
    nauczanie maszynowe
    uczenie głębokie
    projekt Sztucznej Inteligencji
    Opis:
    Raw data processing is a key business operation. Business-specific rules determine howthe raw data should be transformed into business-required formats. When source datacontinuously changes its formats and has keying errors and invalid data, then the effectiveness of the data transformation is a big challenge. The conventional data extraction andtransformation technique produces a delay in handling such data because of continuousfluctuations in data formats and requires continuous development of a business rule engine.The best business rule engines require near real-time detection of business rule and datatransformation mechanisms utilizing machine learning classification models. Since data iscombined from numerous sources and older systems, it is challenging to categorize andcluster the data and apply suitable business rules to turn raw data into the business-required format. This paper proposes a methodology for designing ensemble machine learning techniques and approaches for classifying and segmenting registered numbersof registered title records to choose the most suitable business rule that can convert theregistered number into the format the business expects, allowing businesses to provide customers with the most recent data in less time. This study evaluates the suggested modelby gathering sample data and analyzing classification machine learning (ML) models todetermine the relevant business rule. Experimentation employed Python, R, SQL storedprocedures, Impala scripts, and Datameer tools.
    Źródło:
    Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 55-71
    2299-3649
    Pojawia się w:
    Computer Assisted Methods in Engineering and Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The spike-timing-dependent plasticity function based on a brain sequential learning system using a recurrent neuronal network
    Autorzy:
    Ogata, G.
    Natsume, K.
    Ishizuka, S.
    Hayashi, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/384197.pdf
    Data publikacji:
    2010
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    hippocampus
    entorhinal cortex
    STDP function
    brain science
    Opis:
    This paper examines the spike-timing-dependent plasticity (STDP) at the synapses of the medial entorhinal cortex (EC) and the dentate gyrus (DG) in the hippocampus. The medial and lateral ECs respectively convey spatial and non-spatial information to the hippocampus, and the DG of the hippocampus integrates or binds them. There is a recurrent neuronal network between the EC and the hippocampus called the EC-hippocampus loop. A computational study has shown that using this loop and STDP phenomena at the recurrent EC synapse, sequential learning can be accomplished. But the STDP functions at the synapses of the EC and DG have not yet been studied by neurophysiological experiments. Experiments on STDP phenomena were performed in rats. The STDP function was asymmetrical in the EC synapse and symmetrical in the DG. The medial EC mainly processes the time-series signals for spatial information about visual landmarks when a rat is running in an environment, the lateral EC processes their features, and the DG binds or integrates the information on the positions and features of the landmarks. Thus, the EC-hippocampus loop processes sequential learning of spatial and non-spatial information in parallel, and the DG binds or integrates the two kinds of signals. A system based on this biological phenomenon could have similar characteristics of parallel processing of object features and positions, and their binding.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 2; 25-30
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Sparse data classifier based on first-past-the-post voting system
    Autorzy:
    Cudak, Magdalena
    Piech, Mateusz
    Marcjan, Robert
    Powiązania:
    https://bibliotekanauki.pl/articles/27312911.pdf
    Data publikacji:
    2022
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    POI
    machine learning
    geospatial data
    data science
    first-past-the-post
    random forest
    point of interest
    Opis:
    A point of interest (POI) is a general term for objects that describe places from the real world. The concept of POI matching (i.e., determining whether two sets of attributes represent the same location) is not a trivial challenge due to the large variety of data sources. The representations of POIs may vary depending on the basis of how they are stored. A manual comparison of objects is not achievable in real time; therefore, there are multiple solutions for automatic merging. However, there is no yet the efficient solution solves the missing of the attributes. In this paper, we propose a multi-layered hybrid classifier that is composed of machine-learning and deep-learning techniques and supported by a first-past-the-post voting system. We examined different weights for the constituencies that were taken into consideration during a majority (or supermajority) decision. As a result, we achieved slightly higher accuracy than the best current model (random forest), which also is based on voting.
    Źródło:
    Computer Science; 2022, 23 (2); 277--296
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Navigation strategy for mobile robot based on computer vision and YOLOv5 network in the unknown environment
    Autorzy:
    Bui, Thanh-Lam
    Tran, Ngoc-Tien
    Powiązania:
    https://bibliotekanauki.pl/articles/30148249.pdf
    Data publikacji:
    2023
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    mobile robot
    navigation
    deep learning
    computer vision
    Opis:
    The capacity to navigate effectively in complex environments is a crucial prerequisite for mobile robots. In this study, the YOLOv5 model is utilized to identify objects to aid the mobile robot in determining movement conditions. However, the limitation of deep learning models being trained on insufficient data, leading to inaccurate recognition in unforeseen scenarios, is addressed by introducing an innovative computer vision technology that detects lanes in real-time. Combining the deep learning model with computer vision technology, the robot can identify different types of objects, allowing it to estimate distance and adjust speed accordingly. Additionally, the paper investigates the recognition reliability in varying light intensities. When the light illumination increases from 300 lux to 1000 lux, the reliability of the recognition model on different objects also improves, from about 75% to 98%, respectively. The findings of this study offer promising directions for future breakthroughs in mobile robot navigation.
    Źródło:
    Applied Computer Science; 2023, 19, 2; 82-95
    1895-3735
    2353-6977
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A lightweight multi-person pose estimation scheme based on Jetson Nano
    Autorzy:
    Liu, Lei
    Blancaflor, Eric B.
    Abisado, Mideth
    Powiązania:
    https://bibliotekanauki.pl/articles/30148243.pdf
    Data publikacji:
    2023
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    human pose estimation
    lightweight model
    Edge AI
    deep learning
    computer vision
    Opis:
    As the basic technology of human action recognition, pose estimation is attracting more and more researchers' attention, while edge application scenarios pose a higher challenge. This paper proposes a lightweight multi-person pose estimation scheme to meet the needs of real-time human action recognition on the edge end. This scheme uses AlphaPose to extract human skeleton nodes, and adds ResNet and Dense Upsampling Revolution to improve its accuracy. Meanwhile, we use YOLO to enhance AlphaPose’s support for multi-person pose estimation, and optimize the proposed model with TensorRT. In addition, this paper sets Jetson Nano as the Edge AI deployment device of the proposed model and successfully realizes the model migration to the edge end. The experimental results show that the speed of the optimized object detection model can reach 20 FPS, and the optimized multi-person pose estimation model can reach 10 FPS. With the image resolution of 320×240, the model’s accuracy is 73.2%, which can meet the real-time requirements. In short, our scheme can provide a basis for lightweight multi-person action recognition scheme on the edge end.
    Źródło:
    Applied Computer Science; 2023, 19, 1; 1-14
    1895-3735
    2353-6977
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Classification and detection of skin disease based on machine learning and image processing evolutionary models
    Autorzy:
    Bordoloi, Dibyahash
    Singh, Vijay
    Kaliyaperumal, Karthikeyan
    Ritonga, Mahyudin
    Jawarneh, Malik
    Kassanuk, Thanwamas
    Quiñonez-Choquecota, Jose
    Powiązania:
    https://bibliotekanauki.pl/articles/38700501.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Podstawowych Problemów Techniki PAN
    Tematy:
    skin disorder
    machine learning
    classification
    image enhancement
    image segmentation
    disease detection
    schorzenie skóry
    nauczanie maszynowe
    klasyfikacja
    ulepszenie obrazu
    segmentacja obrazów
    wykrywanie choroby
    Opis:
    Skin disorders, a prevalent cause of illnesses, may be identified by studying their physical structure and history of the condition. Currently, skin diseases are diagnosed using invasive procedures such as clinical examination and histology. The examinations are quite effective and beneficial. This paper describes an evolutionary model for skin disease classification and detection based on machine learning and image processing. This model integrates image preprocessing, image augmentation, segmentation, and machine learning algorithms. The experimental investigation makes use of a dermatology data set. The model employs the machine learning methods: the support vector machine (SVM), the k-nearest neighbors (KNN), and random forest algorithms for image categorization and detection. This suggested methodology is beneficial for the accurate identification of skin disease using image analysis. The SVM algorithm achieved an accuracy of 98.8%. The KNN algorithm achieved a sensitivity of 91%. The specificity of KNN was 99%.
    Źródło:
    Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 247-256
    2299-3649
    Pojawia się w:
    Computer Assisted Methods in Engineering and Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-12 z 12

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