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Wyniki wyszukiwania dla: DESIGNING LEARNING ENVIRONMENTS
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublikacjaThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublikacjaThis paper aims to show how universities interact with Internet users by webcasting selected courses. Paper has exploratory case-study character, presenting example of Berkeley Webcast initiative of University of California, Berkeley, webcasting undergraduate courses and on-campus events. On the base of short introduction to webcasting usage as an e-learning and promotional tool, the analysis of 3 purposely chosen different courses...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Designing sustainable school facilities for public health promotion. Selected issues and examples of good practice
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Designing optimal operational-point trajectories using an intelligent sub-strategy agent-based approach
PublikacjaW rozdziale opisuje się metodę projektowania optymalnej i bezpiecznego sterowania nieliniowymi procesami dynamicznymi. Poszukiwane sterowanie jest wynikiem zastosowania elementarnej strategii poszczególnych agentów, realizujšcych zadanie minimalizacji wspólnej miary kosztu sterowania. Zagadnienie projektowania optymalnego sterowania traktowane jest jako proces decyzyjny, w którym decyzje podejmowane sš w kolejnych regionach przestrzeni...
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On designing minimax adjustable wideband fractional delay FIR filters using two-rate approach
PublikacjaZaprezentowano nowe rozwiązanie problemu projektowania numerycznie oszczędnego, przestrajalnego, szerokopasmowego filtru ułamkowo opóźniającego o skończonej odpowiedzi impulsowej (FIR) w strukturze Farrowa. Innowacja polega na zagregowaniu dwóch podejść. Pierwsze z nich polega na równoczesnej optymalizacji wszystkich podfiltrów struktury Farrowa. Drugie wykorzystuje dwuszybkościową aranżację dwustopniową. Docelowe rozwiązanie jest...
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Designing a magnetoacoustic emission measurement configuration for measurement of creep damage in power plant boiler tubes
PublikacjaOpisywane są własności skonstruowanego detektora emisji magneto-akustycznej (EMA) służącego dla pomiaru stopnia degradacji rurociągów w przemyśle energetycznym. Specjalna budowa biegunów magnesu umożliwia ich dopasowanie do zakrzywionych powierzchni. Układ pomiarowy pozwala na badanie natężenia EMA dla pola wzdłuż osi rury, a także w kierunku obwodowym. Wykazano, iż możliwa jest detekcja zmiany stopnia degradacji materiału na obwodzie...
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Designing optimal operational-point trajectories using an intelligent sub-strategy agent-based approach
PublikacjaW rozdziale opisuje się metodę projektowania optymalnej i bezpiecznego sterowania nieliniowymi procesami dynamicznymi. Poszukiwane sterowanie jest wynikiem zastosowania elementarnej strategii poszczególnych agentów, realizujących zadanie minimalizacji wspólnej miary kosztu sterowania. Zagadnienie projektowania optymalnego sterowania traktowane jest jako proces decyzyjny, w którym decyzje podejmowane są w kolejnych regionach przestrzeni...
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THE MANAGEMENT OF DESIGNING PROCESSES IN THE CREATION OF THE KNOWLEDGE BASE SYSTEM : Proceedings of International Computer Science Convention
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Quality negotiation mechanism for e-learning platforms
PublikacjaZarządzanie jakością w aplikacjach działających w środowiskach sieci WEB opiera się na zadaniach związanych z wykrywaniem jakości połączenia klient - serwer oraz na optymalnym przydziale zasobów wedle jakości takowego połączenia. Optymalne zarządzanie jakością zależy od wypracowanego kompromisu pomiędzy jakością łącza a jakości transportowanego łączem zasobu. Artykuł opisuje możliwy do implementacji mechanizm odpowiedzialny za...
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Comparative study of learning methods for artificial network
PublikacjaW artykule przedstawiono wyniki badań porównawczych metod uczenia sieci neuronowych takich jak: metoda propagacji wstecznej błędów, rekurencyjna metoda najmniejszych kwadratów, metoda Zangwill'a, metoda algorytmów ewolucyjnych. Celem tych badań jest dobieranie najefektywniejszej metody uczenia do projektowania adaptacyjnego neuronowego regulatora napięcia generatora synchronicznego.metody uczenia, sieć neuronowa, neuronowy regulator...
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Impact of technology on learning paradigms and teaching practices
PublikacjaArtykuł stara się omówić różne kwestie dotyczące wpływu technologii na proces nauczania poprzez zaprezentowanie określonych przykładów. Jest próbą sformułowania ogólnych wniosków oraz zweryfikowania kontrowersyjnych opinii.
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Intelligent video and audio applications for learning enhancement
PublikacjaThe role of computers in school education is briefly discussed. Multimodal interfaces development history is shortly reviewed. Examples of applications of multimodal interfaces for learners with special educational needs are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with facial expression and speech stretching audio interface representing audio modality....
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The Use of Photographs in the Teaching/Learning of Descriptive Geometry
PublikacjaThe article presents the concept of enriching the Descriptive Geometry course with photographs and several simplified real-life engineering tasks. The photographic images used for the exercises are tightly linked to engineering structures, the given specialization and the surrounding world. The photo image as a record of central projection of a real space can be useful for presentation and analysis of the properties of perspective....
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Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Wioleta Kucharska dr hab. inż.
OsobyWioleta Kucharska holds a position as an Associate Professor at the Faculty of Management and Economics of the Gdansk TECH, Gdansk University of Technology, Fahrenheit Universities Union, Poland. Authored 66 peer-reviewed studies published with Wiley, Springer, Taylor & Francis, Emerald, Elsevier, IGI Global, and Routledge. Recently involved in such topics as tacit knowledge and company culture of knowledge, learning, and collaboration....
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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High temperature corrosion of steel equipment in modern rafinery environments with high and low sulphur content
PublikacjaPrzedstawiono charakterystykę i mechanizmy procesów wysokotemperaturowej korozji elementów ze stali we współczesnych rafineriach ropy naftowej podczas eksploatacji we frakcjach węglowodorowych o niskiej i wysokiej zawartości siarki. Zwrócono uwagę na procesy korozji siarkowej w obecności wodoru i bez obecności wodoru oraz proces pylenia metalu pod wpływem węgla ze środowiska - w wypadku niskiej zawartości siarki w środowisku.
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The Sonocatalytic Activation of Persulfates on Iron Nanoparticle Decorated Zeolite for the Degradation of 1,4-Dioxane in Aquatic Environments
PublikacjaIn the chemical industry, 1,4-diethylene dioxide, commonly called dioxane, is widely used as a solvent as well as a stabilizing agent for chlorinated solvents. Due to its high miscibility, dioxane is a ubiquitous water contaminant. This study investigates the effectiveness of catalyst- and ultrasound (US)-assisted persulfate (PS) activation with regard to degrading dioxane. As a first step, a composite catalyst was prepared using...
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Design of OFDM-based radio communication systems for coast-to-sea and coast-to-air propagation environments
PublikacjaIn the paper the study of radio communication system design process for systems based on OFDM transmission is considered. The signal propagation model for 1.4 GHz frequency band is discussed, and the study of signal propagation characteristics, important from the point of view of OFDM system design, is presented. The methodology of OFDM interface design is proposed and some characteristics of the OFDM-based radio communication...
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Performance and Security Testing for Improving Quality of Distributed Applications Working in Public/Private Network Environments
PublikacjaThe goal of this dissertation is to create an integrated testing approach to distributed applications, combining both security and performance testing methodologies, allowing computer scientist to achieve appropriate balance between security and performance charakterstics from application requirements point of view. The constructed method: Multidimensional Approach to Quality Analysis (MA2QA) allows researcher to represent software...
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Port Cities within Port Regions: Shaping Complex Urban Environments in Gdańsk Bay, Poland
PublikacjaPort cities located within various metropolitan or functional regions face very different development scenarios. This applies not only to entire municipalities but also to particular areas that play important roles in urban development—including ports as well as their specialized parts. This refers also to the various types of maritime industries, including the processing of goods, logistics operations, shipbuilding, or ship repairing,...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublikacjaThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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MICROBES AND ENVIRONMENTS
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublikacjaThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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Learning Communities-International Journal of Learning in Social Contexts
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Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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On the usefulness of selected radio waves propagation models for designing mobile wireless systems in container terminal environment
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Biopolymers in designing modern antimicrobial medical materials. Part I. Biopolymer medical materials - collagen, chitosan
PublikacjaThe article is a review of the literature concerning the possible use of biopolymers for the preparation of dressings with antimicrobial activity. Authors show the potential of biopolymers: collagen and chitosan - which have the ability to immobilize and control the release of various active compounds - for providing the appropriate antibacterial, bacteriostatic and wound healing properties. Types of threats, for which the dressing...
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ANALYSIS OF WIND CONDITIONS AROUND A BUILDING DEVELOPMENT AS A PART OF ITS FORM DESIGNING PROCESS, A CASE STUDY
PublikacjaAerodynamic phenomena that occurs around building developments exert a significant impact on the quality of climate in cities. Environmental wind engineering is a dynamically developing field of knowledge that offers a chance to study and, in consequence, regulates the air flow around buildings and complexes of building developments. The following paper discusses the issue of wind conditions that may be experienced on pedestrian...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...