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Search results for: ACTIVE%20LEARNING
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Progress in Community Health Partnerships-Research Education and Action
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Edyta Gołąb-Andrzejak dr hab.
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Expansion of the self of activists and nonactivists involved in mass gatherings for collective action
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C-reactive protein as a diagnostic and prognostic factor in inflammatory bowel diseases
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Molecular action of isoflavone genistein in the human epithelial cell line HaCaT
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The molecular mechanism of genistein action in lysosomal storage diseases: A transcriptomic approach
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Agomelatine's antiglycoxidative action—In vitro and in silico research and systematic literature review
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New Thiophene Imines Acting as Hole Transporting Materials in Photovoltaic Devices
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Thermal self-action effects of acoustic beam in a vibrationally relaxing gas
PublicationThermal self-action of acoustic beam in a molecular gas with excited internal degrees of molecules’ freedom, is studied. This kind of thermal self-action differs from that in a Newtonian fluid. Heating or cooling of a medium takes place due to transfer of internal vibrational energy. Equilibrium and non-equilibrium gases, which may be acoustically active, are considered. A beam in an acoustically active gas is self-focusing unlike...
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Action Research: Cooperation of Practitioners and Researchers for Knowledge Development in Public Organisations
PublicationAction Research (AR) is not only a research method or a research strategy for solving a research problem, but also an effective tool for developing knowledge and implementing changes in the organization. The aim of AR is to bring about a change within the studied area and get participants to initiate changes, in which the researcher and the recipient collaborate in investigating the problem and developing a relevant solution. AR...
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More on the poly(L-lactide) prepared using ferrous acetate as catalyst
PublicationPolilaktydy przygotowano w syntezie polegajacej na otworzeniu pierścienia (ROP). Syntezę przeprowadzono w bloku z różną ilością octanu żelaza, użytego jako katalizatora. Zbadano przebieg krystalizacji polilaktydów i podatnośc na biodegradację w osadzie czynnym.
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State Interventionism in Tax System - Example of Action in a COVID-19 Crisis
PublicationThe following article presents and classifies changes in tax systems of selected countries as well as counts them as the response to the emergence of the crisis caused by the COVID-19 pandemic. Such actions were undertaken the context of state interventionism in the tax system. In order to achieve the objective of presenting the state interventionism in the context of tax rates, an analysis of the literature on the phenomenon described,...
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Improvement of electrochemical action of zinc-rich paints by addition of nanoparticulate zinc
PublicationThe influence of nanosized particles on electrochemical action of standard zinc-rich paints by means of SEM as well as potential and impedance measurements has been investigated. The motivation for doing this was to obtain additional electrical connection between the spherical microparticles themselves and zinc particles and steel substrate. Overall zinc content was at the level of 92% by weight. Samples with different concentration...
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EFFECT OF ANTIOXIDANTS ON THE STABILITY OF PITCH- BASED POLYMER TO THERMO-OXIDATIVE ACTION
PublicationThe influence of stabilizers – hydrogen donors – on the processes of thermooxidative destruction of pitch-based polymer has been investigated. It is shown that Irganox has not stabilizing effect on pitch-based polymer and melamine slightly retards the destructive process. A mixture of melamine and Irganox exhibits synergetic stabilizing effect and at the optimum ratio it can be used to prevent unwanted thermooxidative processes...
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Two-step mechanism of J-domain action in driving Hsp70 function
PublicationJ-domain proteins (JDPs), obligatory Hsp70 cochaperones, play critical roles in protein homeostasis. They promote key allosteric transitions that stabilize Hsp70 interaction with substrate polypeptides upon hydrolysis of its bound ATP. Although a recent crystal structure revealed the physical mode of interaction between a J-domain and an Hsp70, the structural and dynamic consequences of J-domain action once bound and how Hsp70s...
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Comparative Analysis of Reactive Power Compensation Devices in a Real Electric Substation
PublicationA constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator...
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Analysis of efficiency of phosphates sorption by different granulation of selected reactive material
PublicationIn the light of the need to find an effective way to remove phosphorus from wastewater, studies on the suitability of sorption materials in this process should be conducted. The aim of the study was to examine the potential benefits of using selected adsorbents to reduce orthophosphates from the model solution under steady conditions. The study was conducted on a laboratory scale using synthetic wastewater with concentration of...
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Thermal Self-Action of Acoustic Beams Containing Several Shock Fronts
PublicationThermal self-action of an acoustic beam with one discontinuity or several shock fronts is studied in a Newtonian fluid. The stationary self-action of a single sawtooth wave with discontinuity (or some integer number of these waves), symmetric or asymmetric, is considered in the cases of self-focusing and self- defocusing media. The results are compared with the non-stationary thermal self-action of the periodic sound. Thermal self-action...
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Anita Maria Dąbrowicz-Tlałka dr
PeopleAnita Dąbrowicz-Tlałka graduated from the Faculty of Mathematics and Physics at the University of Gdańsk with an outstanding grade, having written her thesis in the field of geometric topology. She concurrently obtained a diploma in Postgraduate Studies in the Basics of Computer Science at the University of Gdańsk. In 2001 she received a Ph.D. degree in mathematical studies at the Poznań University of Technology after defending...
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A geophysical, geochemical and microbiological study of a newly discovered pockmark with active gas seepage and submarine groundwater discharge (MET1-BH, central Gulf of Gdańsk, southern Baltic Sea)
PublicationHigh-resolution bathymetric data were collected with a multi-beam echosounder in the southern part of the Baltic Sea (region MET1, Gulf of Gdańsk) revealing the presence of a 10 m deep and 50 m in diameter pockmark (MET1-BH) on the sea bottom (78.7 m). To date, no such structures have been observed to reach this size in the Baltic Sea. The salinity of the near-bottom water in the pockmark was about 2 PSU (about 31.22 mmol/l...
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Photoelectrochemically Active N‐Adsorbing Ultrathin TiO2 Layers for Water‐Splitting Applications Prepared by Pyrolysis of Oleic Acid on Iron Oxide Nanoparticle Surfaces under Nitrogen Environment
PublicationHighly performing photocatalytic surfaces are nowadays highly desirable in energy fields, mainly due to their applicability as photo water‐splitting electrodes. One of the current challenges in this field is the production of highly controllable and efficient photoactive surfaces on many substrates. Atomic layer deposition has allowed the deposition of photoactive TiO2 layers over wide range of materials and surfaces. However,...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Open source learning management systems at civil engineering and environmental department: TeleCAD and Moodle.
PublicationW rozdziale zaprezentowano dwa systemy zarządzania kształceniem, służące do przygotowania i prowadzenia e-kursów. Pierwszy z nich TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). Ostanie użycie systemu miało miejsce w roku akademickim 2003/2004 i był on wykorzystany w projekcie CURE (V Program Ramowy, 2003-2006). W roku 2003 dzięki wsparciu projektu Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji...
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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublicationThis 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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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-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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Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublicationArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating 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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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublicationThis study explores the influence of transformational leadership on internal innovativeness mediated by mistakes acceptance, including country and industry as factors to be considered and gender and risk-taking attitude as moderators. General findings, primarily based on the US samples (healthcare, construction, and IT industry), confirmed that transformational leadership and internal innovativeness are mediated by mistakes acceptance...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany 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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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublicationIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublicationPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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E-LEARNING NA POLITECHNICE GDAŃSKIEJ - HISTORIA ROZWOJU W LATACH 1995-2020
PublicationInternet oraz kształcenie oparte na wykorzystaniu e-technologii stały się nieodłącznym elementem edukacji. Artykuł przedstawia zarys historii rozwoju e-learningu na Politechnice Gdańskiej, przykładowe rozwiązania technologiczne, elementy tworzenia struktur organizacyjnych oraz związanych z legislacją, a także wybrane projekty wykorzystujące szeroko pojęte e-technologie w edukacji akademickiej realizowanej na Uczelni
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...