Search results for: weakly supervised learning - Bridge of Knowledge

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Search results for: weakly supervised learning

Search results for: weakly supervised learning

  • An application of blended and collaborative learning in spatial planning course

    Publication

    Spatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...

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  • Collaborative Data Acquisition and Learning Support

    With the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...

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  • Personal bankruptcy prediction using machine learning techniques

    It has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...

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  • Employing Blended E-Learning to Improve Rate of Assignments Handing-In

    Publication

    - Year 2011

    It has been observed that students hand in homework assignments at a notably low rate in introductory C programming course. A survey has revealed that the real issue was not student learning but instructor work organization. Based on survey results, the physical course has been complemented with an e-learning component to guide the homework process. Assignment handing-in rate significantly improved, as e-learning allowed the homework...

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  • Enterprise Gamification - Learning as a Side Effect of Competition

    Publication

    - Year 2017

    Gmification in companies can be used for driving desired employees behaviour that are advantageous to their development and performance improvement. This paper presents tools acquired from online social networking services and game mechanisms to encourage managers to compete by providing extended statistics and user profiles features in e-learning system.

  • A Mammography Data Management Application for Federated Learning

    Publication

    This study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....

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  • Breast MRI segmentation by deep learning: key gaps and challenges

    Publication

    Breast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...

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  • Weakly nonlinear dynamics of short acoustic waves in exponentially stratified gas

    Publication

    Rozpatruje się dynamika krótkich (w porównywaniu z charakterystyczną skalą zmiany gęstości gazu atmosferycznego) fal akustycznych. Wyprowadzone nowe równanie ewolucyjne, które uwzględnia dyspersję i nieliniowy charakter propagacji tych fal. Porównuje sie liniowa i nieliniowa dynamika. Ilustracje propagacji, numeryczne wyliczione na podstawie nowych wzorów, są przedstawione. Indexed and abstracted (from vol. 32(1) 2007) in Science...

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  • NP-completeness of convex and weakly convex domiating set decision problems.

    Publication

    Liczby dominowania wypukłego i słabo wypukłego są nowymi rodzajami liczb dominowania. W tym artykule pokazujemy, że problemy decyzyjne dominowania wypukłegi i słabo wypukłego są NP-zupełne w przypadku grafów dwudzielnych oraz split grafów. Posługując się zmodyfikowanym algorytmem Washalla możemy w czasie wielomianowym określić, czy dany podzbiór wierzchołków grafu jest spójny bądź słabo spójny.

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  • Fixed point theorems for weakly commuting and compatible multi-valued mappings.

    Publication

    - Year 2004

    W pracy podano twierdzenia o wspólnych punktach stałych czwórki odwzorowań: dwóch jednowartościowych T i S oraz dwóch wielowartościowych F i G, spełniających nieliniowy uogólniony warunek kontrakcyjny, przy pewnych założeniach dotyczących uogólnionej komutatywności T,S i F,G. W pracy zamieszczono przykłady ilustrujące udowodnione twierdzenia.

  • Machine Learning and Electronic Noses for Medical Diagnostics

    Publication

    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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  • A novel architecture for e-learning knowledge assessment systems

    Publication

    Abstract. 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...

  • Active Learning Based on Crowdsourced Data

    The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...

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  • COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)

    Publication

    - Year 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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  • Limitations of Emotion Recognition from Facial Expressions in e-Learning Context

    Publication

    The paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...

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  • Assessment of student language skills in an e-learning environment

    Publication

    This article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....

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  • Learning from Mistakes. A Study on Maturity and Adaptability to Change

    Publication

    - Year 2020

    Learning 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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  • Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers

    The process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...

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  • Learning

    Journals

    ISSN: 2373-5082 , eISSN: 2373-5090

  • The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)

    Publication

    - Year 2023

    This 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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  • Designing acoustic scattering elements using machine learning methods

    Publication

    - Year 2021

    In the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...

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  • Assessing the attractiveness of human face based on machine learning

    Publication

    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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  • Social media for e-learning of citizens in smart city

    Publication

    - Year 2018

    The 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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  • E-learning workshops with Norbert Berger

    e-Learning Courses
    • J. Makowski

    The series of workshops supports MBA faculty in planning, designing, delivering and assessing blended and online modules for their cohorts. It is supplemented by individual coaching to create Moodle and conferencing solutions and their delivery.

  • Basics of Deep Learning 24/25

    e-Learning Courses
    • K. Draszawka

  • Evaluation of ChatGPT Applicability to Learning Quantum Physics

    Publication

    - Year 2023

    ChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...

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  • Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal

    Publication

    - Year 2024

    The new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...

  • Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System

    Publication

    Vast majority of modern e-learning products are based on client-server architecture and utilization of web-based technologies (WBT). Such approach permits easy creation of e-learning systems that do not require a complex, operating system dependant client software. Unfortunately there are also drawbacks of such solution. Because of the majority of mechanisms are located on the server, its usage levels trend to build up quickly...

  • Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits

    Publication

    The Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...

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  • Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study

    Publication

    Flipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...

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  • Interfacial behavior of polar, weakly polar, and nonpolar compounds bound to activated carbons

    Publication
    • V. Gun’ko
    • V. Turov
    • V. Zarko
    • O. Goncharuk
    • Y. Nychiporuk
    • O. Kozynchenko
    • J. Skubiszewska-Zięba
    • R. Leboda
    • B. Charmas
    • D. Balakin... and 2 others

    - Journal of Colloid and Interface Science - Year 2013

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  • Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines

    Publication

    The acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...

  • Data augmentation for improving deep learning in image classification problem

    Publication

    These days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...

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  • Internet photogrammetry as a tool for e-learning

    Publication

    - Year 2015

    Along with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...

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  • Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem

    We are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated...

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  • Innovative e-learning approach in teaching based on case studies - Innocase project

    The article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...

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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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  • MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG

    Publication
    • A. Kastrau
    • M. Koronowski
    • M. Liksza
    • P. Jasik

    - Year 2021

    This 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,...

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

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

    - Year 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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  • Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output

    This research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...

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  • Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing

    The paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...

  • Towards Scalable Simulation of Federated Learning

    Federated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...

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

    Publication

    - European Research Studies Journal - Year 2020

    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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  • E-Learning Service Management System For Migration Towards Future Internet Architectures

    As access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...

  • A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems

    Publication

    In this chapter, the authors 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. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...

  • Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations

    Publication

    - Year 2014

    Continuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...

  • Weakly non-local theories of damage and plasticity based on balance of dissipative material forces

    Publication

    - Year 2005

    Wykazano, że założenie o siłach materialnych oraz odpowiadających im równaniach równowagi w połączeniu z klasycznymi prawami dynamiki w przestrzeni fizycznej, pozwoliło na sformułowanie teoretycznych podstaw w zakresie słabo-nielokalnych gradientowych modeli zniszczenia i plastyczności. Odpowiednie równania równowagi w przestrzeni fizycznej i materialnej oraz pierwsze i drugie prawo termodynamiki zapisano w postaci całkowej. Następnie...

  • Divide and not forget: Ensemble of selectively trained experts in Continual Learning

    Publication
    • G. Rypeść
    • S. Cygert
    • V. Khan
    • T. Trzciński
    • B. Zieliński
    • B. Twardowski

    - Year 2024

    Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...

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  • Multimedia industrial and medical applications supported by machine learning

    Publication

    - Year 2023

    This article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...

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  • Karol Flisikowski dr inż.

    Karol Flisikowski works as Associate Professor at the Department of Statistics and Econometrics, Faculty of Management and Economics, Gdansk University of Technology. He is responsible for teaching descriptive and mathematical statistics (in Polish and English), as well as scientific research in the field of social statistics. He has been a participant in many national and international conferences, where he has presented the results...