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Search results for: ACTIVE%20LEARNING
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue 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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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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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublicationThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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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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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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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn 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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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...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublicationE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublicationNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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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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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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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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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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VSC converters control for offshore wind farms HVDC grid connection
PublicationThe paper proposes a voltage sourced converter (VSC) new control method. A well-known in the electric power systems correlation between voltage angle and active power and correlation between voltage and reactive power is used instead of feedforward control. This allows for a fast and almost independent control of active and reactive power flow.
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Multiple group membership and collective action: study 1&2
Open Research DataDatasets from two studies, conducted in Poland, on the relation between identity fusion, group identification, multiple group membership, perceived injustice, and collective action intention. The purpose of the present studies was to examine (a) whether multiple group membership (in the context of opinion-based groups) relates to collective action (CA)...
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Collective action against same-sex marriages_online research in Poland
Open Research DataThe study was conducted in the context of people opposing the equality of sexual minorities. At the beginning of the survey, each respondent was asked to mark their support for the equality of rights of heterosexual and homosexual persons, on a scale from -3 (definitely not) to 3 (definitely yes). The subsequent questions of the survey were formulated...
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Collective angst and collective action for progressive city policies: study4
Open Research DataWe conducted this study before the second term of the presidential election in Poland in 2020. Conservative-nationalist President Andrzej Duda’s rival was Rafał Trzaskowski, the liberal Mayor of Warsaw supported by Civic Platform [pol. Platforma Obywatelska] party. 456 residents of Gdańsk participated in the study (313 women, 3 non-binary) with M age...
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Collective angst and collective action for progressive city policies: study1
Open Research DataPaweł Adamowicz, the liberal mayor of Gdańsk, died on January 14, 2019, after being stabbed by a man who rushed onstage during a charity event. Three studies were carried out to analyze the predictors of willingness to engage in collective action for the support of the progressive city policies he initiated. In this study 1 (N = 214), the questionnaire,...
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Collective angst and collective action for progressive city policies: study3
Open Research DataPaweł Adamowicz, the liberal mayor of Gdańsk, died on January 14, 2019, after being stabbed by a man who rushed onstage during a charity event. Three studies were carried out to analyze the predictors of willingness to engage in collective action for the support of the progressive city policies he initiated. We conducted Study 3 to test the model with...
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Collective angst and collective action for progressive city policies: study2
Open Research DataPaweł Adamowicz, the liberal mayor of Gdańsk, died on January 14, 2019, after being stabbed by a man who rushed onstage during a charity event. Three studies were carried out to analyze the predictors of willingness to engage in collective action for the support of the progressive city policies he initiated. Since we assumed that the time after the...
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Experimental validation and comparison of a SiC MOSFET based 100 kW 1.2 kV 20 kHz three-phase dual active bridge converter using two vector groups
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Corrigendum to “Synthesis and photoelectrochemical behaviour of hydrogenated titania nanotubes modified with conducting polymer infiltrated by redox active network” [Electrochim. Acta 222 (20 December) (2016) 1281–1292]
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2,7-Dihydro-3H-pyridazino[5,4,3-kl]acridin-3-one derivatives, novel type of cytotoxic agents active on multidrug-resistant cell lines. Synthesis and biological evaluation.
PublicationOtrzymano serię pirydazyno akrydyn-3-onów w reakcji 9-okso-9,10-dihydroakrydyno-1-karboksylanu etylu z POCl3, następnie dodanie odpowiedniej alkiloaminoalkilohydrazyny. Badane związki wykazują w porównaniu z referencyjnymi cytostatykami DX, MIT niższe wartości indeksu RI, a także niższe aktywności cytotoksyczne.
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Effects of Post-Harvest Elicitor Treatments with Ultrasound, UV- and Photosynthetic Active Radiation on Polyphenols, Glucosinolates and Antioxidant Activity in a Waste Fraction of White Cabbage (Brassica oleracea var. capitata)
PublicationBiosynthesis of phytochemicals in leaves of Brassica can be initiated by abiotic factors. The aim of the study was to investigate elicitor treatments to add value to waste of cabbage. A leaf waste fraction from industrial trimming of head cabbage was exposed to UV radiation (250–400 nm, 59 and 99 kJ m-2, respectively), photosynthetic active radiation (PAR, 400–700 nm, 497 kJ m-2), and ultrasound in water bath (35 kHz, at 15, 30...
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СИЛОВОЙ ПРЕОБРАЗОВАТЕЛЬ С АКТИВНЫМ ПОДАВЛЕНИЕМ ВЫСШИХ ГАРМОНИК ДЛЯ СИСТЕМ ЭЛЕКТРОСНАБЖЕНИЯ ЛЕТАТЕЛЬНЫХ АППАРАТОВ (Power converter with active suppression of higher harmonics for aircraft power supply systems)
PublicationПредставлены два алгоритма активной фильтрации для силового преобразователя с активным подавлением высших гармоник. Первый алгоритм основан на дискретном преобразовании Фурье: посредством синтезированной системы управления инвертированные измеренные высшие гармоники напряжения поступают на вход инвертора. Второй метод управления основан на алгоритме с использованием принципов самообучения, что значительно снижает потребность в...
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Evaluation of the significance of the effect of the active cross-sectional area of the inlet air channel on the specific enthalpy of the exhaust gas of a diesel engine using statistics F of the Fisher-Snedecor distribution
PublicationThis paper presents the application of Fisher-Snedecor distribution F statistics to assess the significance of the influence of changes in the active cross-sectional area of the inlet air channel (Adol) flow in a diesel engine on the observed diagnostic parameter determined on the basis of measurements of the quick changing exhaust gas temperature in the outlet channel, which is the specific enthalpy of the exhaust gas stream within...
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Experimental economics in business education: Using simple games to achieve multifaceted effects
PublicationEconomics differs from other sciences not only because of its normative part, but also because of very limited use of experiments. In this way, economics is often perceived as being methodologically more similar to astronomy or meteorology rather than physics or chemistry. Over last decades, however, experimental economics has been significantly developed. This chapter presents some of the possibilities for academic teachers to...
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublicationIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublicationThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
PublicationThe paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Knowledge sharing in manufacturing subsidiaries: proactive and reactive perspective in knowledge exploitation context
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Effect of native air-formed oxidation on the corrosion behavior of AA7075 aluminum alloys
PublicationThe microstructure of aluminum alloys plays a key role in their corrosion resistance. In particular, the presence of intermetallic precipitates differing in the potential from the alloy matrix induces local corrosion. The study presents the effect of native air-formed oxidation on the corrosion behavior of AA 7075 aluminum alloy. Various microscopic and spectroscopic techniques were used to examine the changes occurring in the...
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Action of an Antiserum to a-Tocoquinone on Photosystem II-Particle Preparations of N icotiana tabacum
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The effect of electromagnetic field on reactive oxygen species production in human neutrophilsin vitro
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Isothiocyanates as effective agents against enterohemorrhagic Escherichia coli: insight to the mode of action
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Various modes of action of dietary phytochemicals, sulforaphane and phenethyl isothiocyanate, on pathogenic bacteria
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Evaluation of Analytes Characterized with Potential Protective Action after Rat Exposure to Lead
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Starch-grafted-N-vinylformamide copolymers manufactured by reactive extrusion: synthesis and characterization
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Unsteady aerodynamic forces acting on the rotor blades in the turbine stagewith steam extraction.
PublicationPrzeprowadzono analizę niestacjonarnych wymuszeń działających na łopatki wirnikowe w stopniu z upustem turbiny 13UC100. Niestacjonarne siły zostały wyznaczone dla 4 punktów pracy upustu. Wskazano na możliwą przyczynę zaistniałego zniszczenia łopatek wirnikowych turbiny.