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Wyniki wyszukiwania dla: ACTIVE%20LEARNING
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Amphotericin B and Its New Derivatives - Mode of Action
PublikacjaAmphotericin B (AmB) is a well known antifungal and antiprotozoal antibiotic used in the clinic for several decades. Clinicalapplications of AmB, however, are limited by its nephrotoxicity and many other acute side effects which are not acceptable by patientswhen their life is not threaten. In order to improve the therapeutic index of this drug, lipid formulations have been introduced and manyefforts have been made to obtain less...
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A New Epigenetic Mechanism of Temozolomide Action in Glioma Cells
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Tailoring Graphene to Achieve Negative Poisson's Ratio Properties
PublikacjaGraphene can be made auxetic through the introduction of vacancy defects. This results in the thinnest negative Poisson's ratio material at ambient conditions known so far, an effect achieved via a nanoscale de-wrinkling mechanism that mimics the behavior at the macroscale exhibited by a crumpled sheet of paper when stretched.
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Action-reaction based synthesis of acoustic wavefield equations
PublikacjaThe analysis of acoustic fields is usually based on the well-known mathematics of second order partial differential equations called wave equations. The author explores the duality and symmetry of linear fluid mechanics and develops two distinct equations of acoustics on the basis of a causal approach to local small-scale phenomena. Wavefields that are solutions of these equations have different composition, the spherical pressure...
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The mechanism of grouting action under the base of bored pile
PublikacjaThe grouting under the base of bored pile is carried out in order to reduce pile settlement and improve its bearing capacity. The principal aim of grouting is to introduce an initial force between the soil and the pile base. In non-cohesive soil, the grouting can also enlarge the pile base area and therefore improve the base resistance. The example of static load tests on instrumented bored piles installed with and without grouting...
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Degree product formula in the case of a finite group action
PublikacjaLet V, W be finite dimensional orthogonal representations of a finite group G. The equivariant degree with values in the Burnside ring of G has been studied extensively by many authors. We present a short proof of the degree product formula for local equivariant maps on V and W.
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Game-based Sprint retrospectives: multiple action research
PublikacjaIn today’s fast-paced world of rapid technological change, software development teams need to constantly revise their work practices. Not surprisingly, regular reflection on how to become more effective is perceived as one of the most important principles of Agile Software Development. Nevertheless, running an effective and enjoyable retrospective meeting is still a challenge in real environments. As reported by several studies,...
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Antecedents to Achieve Kanban Optimum Benefits in Software Companies
PublikacjaIn 2004, Kanban successfully entered into the Agile and Lean realm. Since then software companies have been increasingly using it in software development teams. The goal of this study is to perform an empirical investigation on antecedents considered as important for achieving optimum benefits of Kanban use and to discuss the practical implications of the findings. We conducted an online survey with software professionals from...
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Mosaic Structure of p1658/97, a 125-Kilobase Plasmid Harboring an Active Amplicon with the Extended-Spectrum β-Lactamase Gene bla SHV-5
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Photocatalytically Active TiO2/Ag2O Nanotube Arrays Interlaced with Silver Nanoparticles Obtained from the One-Step Anodic Oxidation of Ti–Ag Alloys
PublikacjaThe development of a photocatalyst with remarkable activity to degrade pollutants in aqueous and gas phase requires visible lightresponsive stable materials, easily organized in the form of a thin layer (to exclude the highly expensive separation step). In this work, we present a one-step strategy for synthesizing material in the form of a self-organized TiO2/Ag2O nanotube (NT) array interlaced with silver nanoparticles (as in a...
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Novel insights into conjugation of antitumor-active unsymmetrical bisacridine C-2028 with glutathione: characteristics of non-enzymatic and glutathione S-transferase-mediated reactions
PublikacjaUnsymmetrical bisacridines (UAs) are a novel potent class of antitumor-active therapeutics. A significant route of phase II drug metabolism is conjugation with glutathione (GSH), which can be non-enzymatic and/or catalyzed by GSH-dependent enzymes. The aim of this work was to investigate the GSH-mediated metabolic pathway of a representative UA, C 2028. GSH supplemented incubations of C-2028 with rat, but not with human, liver...
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Synthesis and Structure of Novel Copper(II) Complexes with N,O- or N,N-Donors as Radical Scavengers and a Functional Model of the Active Sites in Metalloenzymes
PublikacjaToevaluatetheantioxidantactivityofpotentialsyntheticenzymemimetics,wepreparednewfivecopper(II)complexesviaaself‐assemblymethodandnamedthem[Cu(2‐(HOCH2)py)3](ClO4)2(1),[Cu(2‐(HOCH2)py)2(H2O)2]SiF6(2),[Cu2(2‐(HOCH2CH2)py)2(2‐(OCH2CH2)py)2](ClO4)2(3),[Cu(pyBIm)3](BF4)2∙1.5H2O(4)and[Cu(py2C(OH)2)2](ClO4)2(5).ThesyntheticprotocolinvolvedN,O‐ orN,N‐donors:2‐(hydroxymethyl)pyridine(2‐(HOCH2)py),2‐(hydroxyethyl)pyridine(2‐(HOCH2CH2)py),2‐(2‐pyridyl)benzimidazole(pyBIm),di(2‐pyridyl)ke‐tone(py2CO).TheobtainedCu(II)complexeswerefullycharacterisedbyelementalanalysis,FTIR,EPR,UV‐Vis,single‐crystalX‐raydiffractionandHirshfeldsurfaceanalysis.Crystallographicandspectroscopicanalysesconfirmedchromophoresofbothmonomeric({CuN3O3}(1),{CuN2O4}(2),{CuN6}(4),{CuN4O2}(5))anddimericcomplex({CuN2O3}(3)).Mostoftheobtainedspeciespos‐sessedadistortedoctahedralenvironment,exceptdimer3,whichconsistedoftwocoppercentreswithsquarepyramidalgeometries.Thewater‐solublecompounds(1,3and5)wereselectedforbiologicaltesting.Theresultsofthestudyrevealedthatcomplex1insolutionsdisplayedbetterradicalscavengingactivitythancomplexes3,5andfreeligands.Therefore,complex1hasbeenselectedforfurtherstudiestotestitsactivityasanenzymemimetic.Thechosencompoundwastestedontheerythrocytelysateoftwogroupsofpatientsafterundergoingchemotherapyandchemoradiotherapy.Theeffectofthetestedcompound(1)onenzymeactivitylevels(TAS,SODandCAT)suggeststhattheselectedcomplexcanbetreatedasafunctionalmimeticoftheenzymes.
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The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders
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Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders
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IT support for OKNO broadband Internet-based distant learning system at WUT
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Reward Learning Requires Activity of Matrix Metalloproteinase-9 in the Central Amygdala
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Developing ICT-rich lifelong learning opportunities trough EU-projects.
PublikacjaArtykuł opisuje doświadczenia Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej od 1997 roku we wdrażaniu kształcenia na odległość. Głównym zadaniem CEN PG jest tworzenie dostępu do materiałów, skryptów, kursów i środowiska internetowego w sieciach LAN i WAN. Udostępniane moduły kursowe zostały opracowane głównie w międzynarodowych zespołach projektowych w wyniku realizowanych unijnych programów Leonardo da Vinci, Socrates...
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Efficient sampling of high-energy states by machine learning force fields
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Analysis of network infrastructure and QoS requirements for modern remote learning systems.
PublikacjaW referacie przedstawiono różne modele zdalnego nauczania. Podjęto próbę oceny wymagań nakładanych na infrastrukturę sieci. Ponadto przedstawiono mechanizmy QoS spotykane w sieciach teleinformatycznych oraz dokonano oceny możliwości ich współpracy w systemach edukacji zdalnej
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal
PublikacjaThe new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis 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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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Stacking and rotation-based technique for machine learning classification with data reduction
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System
PublikacjaVast majority of modern e-learning products are based on client-server architecture and utilization of web-based technologies (WBT). Such approach permits easy creation of e-learning systems that do not require a complex, operating system dependant client software. Unfortunately there are also drawbacks of such solution. Because of the majority of mechanisms are located on the server, its usage levels trend to build up quickly...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublikacjaThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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A Prototype of Educational Agent in Distance Learning Environment - Virtual Student Assistant
PublikacjaW zdalnym nauczaniu pojawia się wiele systemów wspierających, z których niezwykle ciekawym przykładem są agenty edukacyjne. Wśród wielu rodzajów agentów edukacyjnych wyróżnia się osobistych asystentów, których rolą jest organizacyjna pomoc osobie zdobywającej wiedzę. Artykuł jest poświęcony zaimplementowanemu na Wydziale ETI Politechniki Gdańskiej prototypowi agenta edukacyjnego o nazwie WAS (Wirtualny Asystent Studenta). Pokazana...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublikacjaThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublikacjaNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Beesybees-Agent-Based, Adaptive & Learning Workflow Execution Module for BeesyCluster
PublikacjaPrezentujemy projekt oraz implementację adaptacyjnego i uczącego się modułu przeznaczonego dowykonywania scenariuszy w środowisku BeesyCluster. BeesyCluster pozwala na modelowaniescenariuszy w formie acyklicznego grafu skierowanego, w którym wierzchołki oznaczają zadania,a krawędzie określają zależności między nimi. Przedstawiamy także kooperatywne wykonaniescenariusza przez grupę agentów zdolnych do zbierania, składowania i korzystania...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...