Search results for: QUALITY OF LEARNING
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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A novel architecture for e-learning knowledge assessment systems
PublicationAbstract. In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture,while well suited for didactic content distribution systems is ill-suited for knowledge assessment...
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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The Double Cognitive Bias of Mistakes: A Measurement Method
PublicationThere is no learning without mistakes. However, making mistakes among knowledge workers is s�ll seeing shameful. There is a clash between posi�ve a�tudes and beliefs regarding the power of gaining new (tacit) knowledge by ac�ng in new contexts and nega�ve a�tudes and beliefs toward accompanying mistakes that are sources of learning. These contradictory a�tudes create a bias that is doubled by the other shared solid belief...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublicationThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Learning from Mistakes. A Study on Maturity and Adaptability to Change
PublicationLearning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublicationComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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THRIVING AND JOB SATISFACTION IN MULTICULTURAL ENVIRONMENTS OF MNCS
PublicationPurpose of the article The aim of the paper is to analyze the relationship between thriving and job satisfaction in multicultural environments of multinational corporations (MNCs). Methodology/methods The quantitative cross-sectional study was conducted on the sample of 128 individuals from subsidiaries of various MNCs located in Poland involved in intercultural interactions. Scientific aim The aim of this study was to examine...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublicationE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Between therapy effect and false-positive result in animal experimentation
PublicationDespite the animal models’ complexity, researchers tend to reduce the number of animals in experiments for expenses and ethical concerns. This tendency makes the risk of false-positive results, as statistical significance, the primary criterion to validate findings, often fails if testing small samples. This study aims to highlight such risks using an example from experimental regenerative therapy and propose a machine-learning...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublicationDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Acquisition and indexing of RGB-D recordings for facial expressions and emotion recognition
PublicationIn this paper KinectRecorder comprehensive tool is described which provides for convenient and fast acquisition, indexing and storing of RGB-D video streams from Microsoft Kinect sensor. The application is especially useful as a supporting tool for creation of fully indexed databases of facial expressions and emotions that can be further used for learning and testing of emotion recognition algorithms for affect-aware applications....
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Transformational leadership for researcher’s innovativeness in the context of tacit knowledge and change adaptability
PublicationThis study explores how a learning culture supported by transformational leadership influences tacit knowledge sharing and change adaptability in higher education and how these relations impact this sector’s internal and external innovativeness. The empirical model was tested on a sample of 368 Polish scientific staff using the structural equation modeling (SEM) method. Then results were expanded by applying OLS regression using...
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Aktywności stymulujące refleksję w nauczaniu języka pisanego w wirtualnej klasie
PublicationThe paper aims to show how to engage students attending an online language course in various activities which by stimulating reflection enhance the learning process and result in better learning outcomes. By blending cognitivist, constructivist, constructionist and behavioural ideas, course developers and tutors can produce materials and use methods which satisfy the varied needs of adults who want to improve their writing skills....
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Uczenie się przez całe życie
PublicationW pracy przedstawiono genezę ustanowienia europejskiego obszaru uczenia się przez całe życie oraz podstawowe zasady Lifelong Learning. Omówiono krajowe uwarunkowania procesu LLL oraz walidację efektów uczenia się.
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Gender as a Moderator of the Double Bias of Mistakes – Knowledge Culture and Knowledge Sharing Effects
PublicationThere is no learning without mistakes. The essence of the double bias of mistakes is the contradiction between an often-declared positive attitude towards learning from mistakes, and negative experiences when mistakes occur. Financial and personal consequences, shame, and blame force desperate employees to hide their mistakes. These adverse outcomes are doubled in organizations by the common belief that managers never make mistakes,...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Machine Learning Techniques in Concrete Mix Design
PublicationConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Online Interactivity – Shift Towards E-textbook-based Medical Education
PublicationTextbooks have played the leading role in academic education for centuries and their form has evolved, adapting to the needs of students, teachers and technological possibilities. Advances in technology have caused educators to look for new sources of knowledge development, which students could use inside and outside the classroom. Today’s sophisticated learning tools range from virtual environments to interactive multimedia resources,...
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The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)
PublicationThis book focuses on seeing, understanding, and learning to shape an organization’s essential cultures. The book is grounded on a fundamental assumption that every organization has a de facto culture. These “de facto cultures” appear at first glance to be serendipitous, vague, invisible, and unmanaged. An invisible and unrecognized de facto culture can undermine business goals and strategies and lead to business failures. The authors...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis 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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Projekt Leonardo da Vinci ''Wirtualne kursy zawodowego języka angielskiego oraz system ich ewaluacji VENOCES''.
PublicationProject VENOCES ma na celu podniesienie poziomu nauczania języków obcych oraz ułatwienie dostępu do wiedzy specjalistycznej przez stworzenie wirtualnych kursów językowych w dziedzinach istotnych dla wszystkich partnerów stosując nowoczesne technologie multimedialne oraz innowacyjne podejście metodologiczne CLIL (ang. Content and Language Learning Approach). Niewątpliwą innowacją założoną przez twórców projektu będzie zastosowanie,...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Rozwijanie kreatywności ucznia w procesie kształtowania umiejętności językowych. Innowacja pedagogiczna z elementami neurodydaktyki w edukacji wczesnoszkolnej
PublicationThis text is a ready-to-use pedagogical innovation program combining teaching English and classes developing creativity in early childhood education. Classes developing creativity are a unique opportunity to implement innovative solutions and ideas to develop language competencies and key competencies, which can be difficult during a standard English lesson. The...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublicationResearch, 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
PublicationIn 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
PublicationIn 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
PublicationIn 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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CHALK & TALK OR SWIPE & SKYPE?
PublicationTechnology in classroom is a matter of heated discussions in the field of education development, especially when multidisciplinary education goes along with language skills. Engineers’ education requires theoretical and practical knowledge. Moreover, dedicated computer skills become crucial for both young graduates and experienced educators on the labor market. Teaching online with or without using different Learning Management...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe 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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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublicationThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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Social media for e-learning of citizens in smart city
PublicationThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis 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
PublicationWorking 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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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe 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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Assessing the attractiveness of human face based on machine learning
PublicationThe 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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Leadership, culture, intellectual capital and knowledge processes for organizational innovativeness across industries: the case of Poland
PublicationPurpose – 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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POSITIVE PSYCHOLOGICAL CAPITAL ENHANCES THRIVING IN THE MULTICULTURAL WORK ENVIRONMENT OF MULTINATIONAL CORPORATIONS
PublicationThe 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...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublicationIn 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...