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Search results for: DISTRIBUTED MACHINE LEARNING
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English Language Learning Employing Developments in Multimedia IS
PublicationIn the realm of the development of information systems related to education, integrating multimedia technologies offers novel ways to enhance foreign language learning. This study investigates audio-video processing methods that leverage real-time speech rate adjustment and dynamic captioning to support English language acquisition. Through a mixed-methods analysis involving participants from a language school, we explore the impact...
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Towards Resource Theory of Coherence in Distributed Scenarios
PublicationThe search for a simple description of fundamental physical processes is an important part of quantum theory. One example for such an abstraction can be found in the distance lab paradigm: if two separated parties are connected via a classical channel, it is notoriously difficult to characterize all possible operations these parties can perform. This class of operations is widely known as local operations and classical communication....
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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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Affective computing and affective learning – methods, tools and prospects
PublicationEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Complementarity between entanglement-assisted and quantum distributed random access code
PublicationCollaborative communication tasks such as random access codes (RACs) employing quantum resources have manifested great potential in enhancing information processing capabilities beyond the classical limitations. The two quantum variants of RACs, namely, quantum random access code (QRAC) and the entanglement-assisted random access code (EARAC), have demonstrated equal prowess for a number of tasks. However, there do exist specific...
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VISUALIZATION OF SCANTER AND ARPA RADAR DATA IN THE DISTRIBUTED TELEINFORMATION SYSTEM FOR THE BORDER GUARD
PublicationMonitoring of country maritime border is an important task of the Border Guard. This activity can be enhanced with the use of the technology enabling gathering information from distributed sources, processing of that information and its visualization. The paper presents the next stage of development of the STRADAR project (Streaming of real-time data transmission in distributed dispatching and teleinformation systems of the Border...
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Results of timber material tests from a strength testing machine
Open Research DataThis dataset consists of an archive with TRA files with the results of timber (wooden rolls) material tests from an universal strength testing machine.
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Blended-learning w nauczaniu przedmiotów nieinformatycznych
PublicationBlended-learning jest coraz powszechniej wykorzystywany w nauczaniu przedmiotów informatycznych lub innych przedmiotów, w których ćwiczenia realizowane są w laboratoriach komputerowych. W przypadku przedmiotów bez dostępu do sal komputerowych, blended-learning wspomaga prowadzenie wykładów i ćwiczeń poprzez np. lekcje interaktywne. Artykuł opisuje zastosowanie form blended-learning w realizacji laboratoriów z przedmiotu Bezpieczeństwo...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Machine Design PG_00059691
e-Learning Courses -
Affective Learning Manifesto – 10 Years Later
PublicationIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Selected Problems of Machine Dynamics II
e-Learning CoursesThe following set of lectures is performed: 1. LECTURE No.1 - INTRODUCTION TO SELECTED PROBLEMS OF MACHINE DYNAMICS. STRUCTURES and MACHINES 2. LECTURE No.2 - ENVIRONMENT, LOADS ON STRUCTURES and MACHINES 3. LECTURE No.3 - DYNAMICS of STRUCTURES and MACHINES 4. LECTURE No.4 - STRENGTH of STRUCTURES and MACHINES 5. LECTURE No.5 - SPECIAL PROBLEMS ASSOCIATED with DYNAMICS and STRENGTH of STRUCTURES and MACHINES
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Selected Problems of Machine Dynamics - advances
e-Learning CoursesThe following set of lectures is performed: 1. LECTURE No.1 - INTRODUCTION TO SELECTED PROBLEMS OF MACHINE DYNAMICS. STRUCTURES and MACHINES 2. LECTURE No.2 - ENVIRONMENT, LOADS ON STRUCTURES and MACHINES 3. LECTURE No.3 - DYNAMICS of STRUCTURES and MACHINES 4. LECTURE No.4 - STRENGTH of STRUCTURES and MACHINES 5. LECTURE No.5 - SPECIAL PROBLEMS ASSOCIATED with DYNAMICS and STRENGTH of STRUCTURES and MACHINES
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Selected Problems of Machine Dynamics - advances
e-Learning CoursesThe following set of lectures is performed: 1. LECTURE No.1 - INTRODUCTION TO SELECTED PROBLEMS OF MACHINE DYNAMICS. STRUCTURES and MACHINES 2. LECTURE No.2 - ENVIRONMENT, LOADS ON STRUCTURES and MACHINES 3. LECTURE No.3 - DYNAMICS of STRUCTURES and MACHINES 4. LECTURE No.4 - STRENGTH of STRUCTURES and MACHINES 5. LECTURE No.5 - SPECIAL PROBLEMS ASSOCIATED with DYNAMICS and STRENGTH of STRUCTURES and MACHINES
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Learning design of a blended course in technical writing
PublicationBlending face-to-face classes with e-learning components can lead to a very successful outcome if the blend of approaches, methods, content, space, time, media and activities is carefully structured and approached from both the student’s and the tutor’s perspective. In order to blend synchronous and asynchronous e-learning activities with traditional ones, educators should make them inter-dependent and develop them according to...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublicationThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Distributed Representations Based on Geometric Algebra: the Continuous Model
PublicationAuthors revise the concept of a distributed representation of data as well as two previously developed models: Holographic Reduced Representation (HRR) and Binary Spatter Codes (BSC). A Geometric Analogue (GAc - ''c'' stands for continuous as opposed to its discrete version) of HRR is introduced - it employs role-filler binding based on geometric products. Atomic objects are real-valued vectors in n-dimensional Euclidean space...
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Open standards-based communication system for distributed intelligent surveillance solution
PublicationThe paper presents an open standards-based communication system being a part of a distributed surveillance solution. The paradigm of “intelligent” surveillance approach is introduced, and employed video processing is discussed briefly. Requirements analysis toward the design of communication subsystem architecture is presented. Special attention is paid to the multimedia streaming functionality of presented solution, which is based...
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Distributed measurement system with data transmission secured using XXTEA algorithm
PublicationThe paper deals with wireless data transmission security in the distributed measurement and control system. An overview of cryptographic algorithms was presented paying special attention to the algorithm dedicated to units with low processing power, which is important due to minimization of energy consumption. Measurement modules equipped with simple microcontrollers send data wirelessly to the central unit. The transmission was...
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MagMax: Leveraging Model Merging for Seamless Continual Learning
PublicationThis paper introduces a continual learning approach named MagMax, which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during task training, MagMax combines sequential fine-tuning with a maximum magnitude weight selection for effective knowledge integration...
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THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS
PublicationStructural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design
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Computer-assisted assessment of learning outcomes in the laboratory of metrology
PublicationIn the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...
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Profile irregularities of turned surfaces as a result of machine tool interactions
PublicationThe paper describes the influence of the machining operation on a surface, which disturbs the projection of the tool profile in the form of its relative movements with respect to the object. The elements of the machine tool undergo constant wear during the machining process, it is therefore important to recognize the effects of their influence on the surface's irregularities. Amplitude-frequency analysis of lateral profiles has...
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Asynchronous distributed state estimation for continuous-time stochastic processes
PublicationWe consider the problem of state estimation of a continuous-time stochastic process using an asynchronous distributed multi-sensor estimation system (ADES). In an ADES the state of a process of interest is estimated by a group of local estimators. Each local estimator based, for example, on a Kalman filter, performs single sensor filtration but also fusion of its local results and results from other (remote) processors to compute...
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Energy Versus Throughput Optimisation for Machine-to-Machine Communication
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo 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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Innovative method of localization airplanes in VCS (VCS-MLAT) distributed system
PublicationThe article presents the concept and the structure of the localization module. The prototype module is the part of the VCS (VCS-MLAT) localization distributed system. The device receives the audio signal transmitted in airplanes band (118 MHz – 136 MHz). Received data with the timestamps are send to the main server. The data from multiple devices estimates the localization of the airplane. The main aim of the project is the analysis...
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Bogdan Wiszniewski prof. dr hab. inż.
PeopleBogdan Wiszniewski graduated from Gdansk University of Technology in 1977 and was awarded an MSc in computer science and engineering with honours. In 1984 and 1998, respectively, has got his PhD and DSc. In 2006 was awarded a Professor title by the President of Poland. Lectured at the universities in Canada, US and UK. Principal investigator or coordinator in many national and international R&D projects with the significant...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublicationThe 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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Social Learning in Cluster Organizations and Accumulation of Technological Capability
PublicationThe purpose of the paper is to present how members of cluster organizations perceive their role in the accumulation of technological capability through social learning. The paper presents the results of a qualitative study of four cluster organizations. The theoretical foundation of the study are the communities of practice and the organizational inertia theories. The study indicates that the dynamics of technological capability...
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Distributed NVRAM Cache – Optimization and Evaluation with Power of Adjacency Matrix
PublicationIn this paper we build on our previously proposed MPI I/O NVRAM distributed cache for high performance computing. In each cluster node it incorporates NVRAMs which are used as an intermediate cache layer between an application and a file for fast read/write operations supported through wrappers of MPI I/O functions. In this paper we propose optimizations of the solution including handling of write requests with a synchronous mode,...
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An application of blended and collaborative learning in spatial planning course
PublicationSpatial 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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Distributed Framework for Visual Event Detection in Parking Lot Area
PublicationThe paper presents the framework for automatic detection of various events occurring in a parking lot basing on multiple camera video analysis. The framework is massively distributed, both in the logical and physical sense. It consists of several entities called node stations that use XMPP protocol for internal communication and SRTP protocol with Jingle extension for video streaming. Recognized events include detecting parking...
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Collaborative Data Acquisition and Learning Support
PublicationWith 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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Calculation of self and mutual inductances of the switched reluctance machine mathematical model.
PublicationA mathematical model of the switched reluctance machine (SRM) in a drive system obtained using Lagrange's energy method and a method of calculation of self and mutual inductances of the SRM are presented in the paper. The self and mutual inductances are elements of Lagrange's function in generalised coordinates and have been calculated using the finite element method (FEM). Selected calculation results for the particular machine...
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Hybrid Processing by Turning and Burnishing of Machine Components
PublicationThe paper presents a method of hybrid manufacturing process of long 5 shafts and deep holes by simultaneous turning and burnishing method. The tech- 6 nological results of the research focus on the influence of the basic technological 7 parameters of this process on the surface roughness of piston rods of hydraulic 8 cylinders. Research results are presented in the graphs as well as mathematical 9 formula. Set of samples were made...
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Employing Blended E-Learning to Improve Rate of Assignments Handing-In
PublicationIt 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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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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Enterprise Gamification - Learning as a Side Effect of Competition
PublicationGmification 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.
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On the complexity of distributed greedy coloring
PublicationW pracy rozważono problem kolorowania grafów przy dodatkowym założeniu, że kolor żadnego wierzchołka nie może zostać zmniejszony bez zmiany kolorów przynajmniej jednego z jego sąsiadów. Przeprowadzone rozważania dotyczyły złożoności obiczeniowej problemu w modelu Liniala obliczeń rozproszonych. Podano ograniczenia dolne i górne złożoności problemu oraz zestawiono problem z innymi pokrewnymi zagadnieniami grafowymi.
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A Mammography Data Management Application for Federated Learning
PublicationThis 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
PublicationBreast 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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Journal of Machine Engineering
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Nature Machine Intelligence
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Machine Intelligence Research
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MACHINE VISION AND APPLICATIONS
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Quantum Machine Intelligence
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