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DentalSegmentator: robust deep learning-based CBCT image segmentation
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Agent-Based Population Learning Algorithm for RBF Network Tuning
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Comparison of reproduction strategies in genetic algorithm approach to graph searching
Publikacjagenetic algorithms (ga) are a well-known tool used to obtain approximate solutions to optimization problems. successful application of genetic algorithm in solving given problem is largely dependant on selecting appropriate genetic operators. selection, mutation and crossover techniques play a fundamental role in both time needed to obtain results and their accuracy. in this paper we focus on applying genetic algorithms in calculating...
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Deep learning-based waste detection in natural and urban environments
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Becoming a Learning Organization Through Dynamic Business Process Management
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Searching of the buried objects in the sea bottom by means of noninvasive methods
PublikacjaSearching of objects on the seabed or under its surface currently is a challenge for a number of researchers interested in the sea bottom. The problem relates to the objects on the depths of up to several tens of meters from the surface of the seabed. Finding the objects is the subject of interest for a wide group of users starting from archaeologists, and ending on groups interested in marine safety, as well as in military application...
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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublikacjaThe 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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Digital competence learning in secondary adult education in Finland and Poland
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Model of distributed learning objects repository for a heterogenic internet environment
PublikacjaW artykule wprowadzono pojęcie komponentu edukacyjnego jako rozszerzenie obiektu edukacyjnego o elementy zachowania (metody). Zaproponowane podejście jest zgodne z paradygmatem obiektowym. W oparciu o komponent edukacyjny zaprojektowano model budowy repozytorium materiałów edukacyjnych. Model ten jest oparty o usługi sieciowe i rejestry UDDI. Komponent edukacyjny oraz model repozytorium mogą znaleźć zastosowanie w konstrukcji zbiorów...
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublikacjaPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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Employing Blended E-Learning to Improve Rate of Assignments Handing-In
PublikacjaIt 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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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublikacjaIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublikacjaClass-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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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast 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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Data augmentation for improving deep learning in image classification problem
PublikacjaThese 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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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe 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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: 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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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis 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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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublikacjaThe national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn 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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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Gas-phase quasi-degeneracy of zwitterionic and canonical tautomers of glycine and proline induced by the presence of the MAlF4(M = Li, Na, K) salts
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Leading Behavioral Characteristics and Investors’ Decisions: An Experimental Approach
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Psychogenic Polydipsia leading to Hyponatremia induced Seizure in Schizophrenia.
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Application of Intelligent Conversational Agents in E-learing Environments
PublikacjaThe paper concerns intelligent tutoring systems and concentrates on apliaction of virtual mentors in distance learning environments. Different educational agent types are described. The prototype of an agent developed at Gdansk University of Technology is also presented, as well as its internal representation and construction. Benefits of virtual mentors applied in distance learning are also pointed out.
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Unusual behavior of secondary amine group as a leaving group
PublikacjaIn our recent project we focused on reactivity of2,2-dimethyl-4,6-dioxane-1,3-dione carbamoilo- and thiocarbamoylo- derivatives as a ketenesource. Meldrum`s acid derivatives after thermal decomposition gives substituted keteneswith stoichiometric yield, that can be trapped with various spectrum of nucleophiles likealcohols, thiols, amine, imines etc. In case of5-[3-(dimethylamino)-sulfanyl-propyliden]-2,2-dimethyl-1,3-dioxane-4,6-dione...
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Improving web user experience with caching user interface
PublikacjaOften, Web technologies are used to operate or to configure network-enabled equipment, to configure and administer modular applications, or as teaching environments. The comfort of human work requires a similar response time in these applications as in the Internet. To improve response time, various forms of caching at different levels are employed. To improve the user experience in regard to response time when performing specific...
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Improving web user experience with caching user interface
PublikacjaIn human-computer interaction, response time is assumed generally not to exceed significantly 1-2 seconds. While the natural competition in the Internet public Web serving ensures adhering widely to such limits, some Web environments are less competitive and offer much worse user experience in terms of response time. This paper describes a solution to significantly improve user experience in terms of response time with only modification...
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Stosunek pracy a leasing pracowniczy(agencje pracy tymczasowej).
PublikacjaW obecnie obowiązujacym sytstemie prawa pracodawca ma do wyboru szereg podstaw nawiązania stosunku prawnego w oparciu,o który dochodzi do zatrunienia pracowników.Oczywiście najwazniejsze z punktu widzenia osoby zatrudnionej są regulowane kodeksem pracy.Podmiot zatrudniający coraz częściej jednak dokonuje wyboru innych podstaw i metod zatrudnienia,choć nie zawsze czyni to w sposób prawidłowy.Niewątpliwie wybór podstawy zatrudnienia...
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Chuzhdoezikovo Obuchenie-Foreign Language Teaching
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Iranian Journal of Language Teaching Research
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Journal of Technology and Chinese Language Teaching
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Journal of Information Technology Teaching Cases
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Electronic Journal of Foreign Language Teaching
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Modern Journal of Language Teaching Methods
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Brazilian English Language Teaching Journal
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In search of the new: American volunteers’ opinions about their participation in the Teaching English in Poland (TEIP) Program
PublikacjaThe Teaching English in Poland (TEIP) program relies on summer camps during which native English speakers, American volunteers, teach Polish children and adolescents using the language immersion method – during everyday activities, sports and art classes, and similar occasions. A vital aspect of the evaluation of the program is researching its impact on the young people; however, the opinions of the volunteers regarding their...
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Methodology of entrepreneurship teaching in tertiary education - experiences of the Faculty of Economics and Management on the Gdansk University of Technology
PublikacjaThe purpose of the chapter is an overview of the available methods and techniques of teaching entrepreneurship at the academic level, as well as the presentation of the methodology of the work with students within the framework of the Entrepreneurship course at the Faculty of Management and Economics of the Gdańsk University of Technology.
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Teaching management skills to software develop- ment teams through the lean start-up methodology
PublikacjaIn order for development teams to understand the impact of software development on value delivery it is important that all team members, including software engineers, possess adequate management skills which not always have been acquired during university education. The lean start-up methodology techniques enable new ventures to test hypothesis, gather customer feed- back and create a minimum viable product. The obtained information...