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Search results for: trust in vaccine
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Steady-State Vibration Level Measurement of the Five-Phase Induction Machine during Third Harmonic Injection or Open-Phase Faults
PublicationMultiphase electric machines are increasingly used in various industries and for electromobility. Complex systems have been developed for the control and powering of multiphase machines, which require verification. The quality of control and the power supply of electric machines is usually evaluated by analyzing various electrical parameters. On the other hand, taking into account the fact that a motor is an electrical-mechanical...
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublicationDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublicationCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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Finite State Machine Based Modelling of Discrete Control Algorithm in LAD Diagram Language With Use of New Generation Engineering Software
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Non-linear circuit model of a single doubly-fed induction machine formulated in natural axes for drive systems simulation purposes
PublicationMathematical modelling and a circuit model formulated in natural axes of a single doubly-fed induction machine, with the account of magnetic circuit nonlinearity are presented in the paper. Derivation of the model differential equations was based on Lagrange's energy method. State functions of magnetic elements in the model are non-linear and depend on all currents flowing in the machine windings and on the angle of rotor position....
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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JOURNAL OF MACHINE LEARNING RESEARCH
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The effect of full-cell impregnation of pine wood (Pinus Sylvestris L.) on the fine dust content during sawing on a frame sawing machine
PublicationIn this paper the results of the analysis of the effect of the impregnation treatment of pine wood on the granularity of sawdust from the sawing process on the frame sawing machine PRW 15M are presented. Granulometric analyses of chips from impregnated and unimpregnated pine wood implies that the impregnation of pine wood does not affect the size and structure of the sawdust produced. A major ≈ 95% share of the formed chips is...
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Wykorzystanie modelu silnika indukcyjnego klatkowego do prądowej diagnostyki jego łożysk. Application of induction machine model for current diagnostics of bearings
PublicationW pracy podano widmo prądu stojana dla silnika normalnego oraz wprawianego w drgania o nastawianej częstotliwości. Drgania korpusu wirnika skutkują uginaniem się wirnika, co symuluje bicie wirnika od uszkodzenia łożysk. Podano też model matematyczny silnika, dopuszczający niecentryczność wirnika. Podano widmo prądu stojana przy pracy z wibracjami wirnika odwzorowującymi w pewnym przybliżeniu wibracje od uszkodzonych łożysk.
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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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
PublicationPlain 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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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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David Duenas Cid dr hab.
PeopleHe is an Associate Professor at Kozminski University and the director of the Pub-Tech (Public Sector Data-Driven Technologies) Research Center. Previously, he served as an H2020 Marie Skłodowska-Curie Widening Fellow at Gdansk University of Technology, as a Researcher at the Johan Skytte Institute of Political Studies of the University of Tartu, as a Postdoctoral Researcher at the Ragnar Nurkse Department of Innovation and Governance...
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Defending against Fake VIP in Scant-Transparency Information Systems with QoS Differentiation
PublicationIn client-server information systems with quality of service (QoS) differentiation, Client may deplete Server’s resources by demanding unduly high QoS level. Such QoS abuse has eluded systematic treatment; known defenses using Client authorization, payments, or service request inspection prior to QoS assignment, are heuristic and environment-specific. We offer a game-theoretic approach on the premise that a service request is occasionally...
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Jerzy Konorski dr hab. inż.
PeopleJerzy Konorski received his M. Sc. degree in telecommunications from Gdansk University of Technology, Poland, and his Ph. D. degree in computer science from the Polish Academy of Sciences, Warsaw, Poland. In 2007, he defended his D. Sc. thesis at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology. He has authored over 150 papers, led scientific projects funded by the European Union,...
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Zaufanie do siebie jako jeden z aspektów zaufania w aktywności przedsiębiorczej
PublicationArtykuł prezentuje znaczenie zaufania do samego siebie na tle zaufania w relacjach budowanych przez przedsiębiorcę w jego otoczeniu społecznym i biznesowym. Wyjaśniono koncepcję zaufania do samego siebie, odnosząc się do zróżnicowanych typów zaufania, na przykład: kalkulacyjnego, opartego na wiedzy i identyfikacyjnego. Wskazano jego potencjalne źródła i konsekwencje w kontekście budowania własnego wizerunku, podejmowania decyzji...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Revisiting the estimation of cutting power with different energetic methods while sawing soft and hard woods on the circular sawing machine: a Central European case
PublicationIn the classical approaches, used in Central Europe in practice, cutting forces and cutting power in sawing processes of timber are commonly computed by means of the specific cutting resistance kc. It needs to be highlighted that accessible sources in handbooks and the scientific literature do not provide any data about wood provenance, nor about cutting conditions, in which cutting resistance has been empirically determined. In...
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Supporting Assurance by Evidence-based Argument Services
PublicationStructured arguments based on evidence are used in many domains, including systems engineering, quality assurance and standards conformance. Development, maintenance and assessment of such arguments is addressed by TRUST-IT methodology outlined in this paper. The effective usage of TRUST-IT requires an adequate tool support. We present a platform of software services, called NOR-STA, available in the Internet, supporting key activities...
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Zaufanie w zespołach pracowniczych – czy polskie zespoły są gotowe na empowerment?
PublicationZaufanie jest istotnym elementem klimatu pracy zespołowej i warunkiem budowania efektywnych zespołów, korzystających z potencjału zaangażowanych w realizację celu pracowników. Zaufanie jest też podstawą wdrażania w zespołach zasad empowermentu, rozumianego nie tylko jako przekazanie władzy członkom zespołu, ale również jako zdolność zespołu do przejmowania odpowiedzialności za realizację wybranego celu. W artykule przedstawiono...
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Finger Vein Presentation Attack Detection Method Using a Hybridized Gray-Level Co-Occurrence Matrix Feature with Light-Gradient Boosting Machine Model
PublicationPresentation Attack Detection (PAD) is crucial in biometric finger vein recognition. The susceptibility of these systems to forged finger vein images is a significant challenge. Existing approaches to mitigate presentation attacks have computational complexity limitations and limited data availability. This study proposed a novel method for identifying presentation attacks in finger vein biometric systems. We have used optimal...
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Wykorzystanie metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn = application of the FMEA method for skills development of machine parts technology desing
PublicationPrzedstawiono sposób wykorzystania metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn. Podano wytyczne ogólne i etapy analizy procesu i konstrukcji. Zamieszczono przykład analizy technologii dwustronnej dźwigni spawanej w produkcji małoseryjnej.
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The Immunogenic and Immunoprotective Activities of Recombinant Chimeric T. gondii Proteins Containing AMA1 Antigen Fragments
PublicationToxoplasmosis, one of the most common parasitoses worldwide, is potentially dangerous for individuals with a weakened immune system, but specific immunoprophylaxis intended for humans is still lacking. Thus, efforts have been made to create an efficient universal vaccine for both animals and humans to overcome the shortcomings of currently used treatment methods and protect all hosts against toxoplasmosis. The current work represents...
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The Fear of SARS-CoV-2 Infection versus the Perception of COVID-19 Vaccination amongst Older Adults in Urban Areas (CoV-VAC-PL Study): A Polish Community-Based Study
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Attitudes toward Receiving COVID-19 Booster Dose in the Middle East and North Africa (MENA) Region: A Cross-Sectional Study of 3041 Fully Vaccinated Participants
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Attitudes toward Receiving COVID-19 Booster Dose in the Middle East and North Africa (MENA) Region: A Cross-Sectional Study of 3041 Fully Vaccinated Participants
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Coalition Shaping the Vaccination Landscape
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Investigating beliefs in anti-vax conspiracy theories among medical students
PublicationAbstract: While the doctors’ role in immunization is essential, their lack of knowledge or vaccine hesitancy may affect their ability to communicate effectively and educate patients about vaccination, vaccine hesitancy, and vaccine conspiracy theories. This, in turn, may hinder health policy aimed at fighting infectious diseases. Vaccine hesitancy is prevalent not only among the general population but also among healthcare...
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The Impact of the Antigenic Composition of Chimeric Proteins on Their Immunoprotective Activity against Chronic Toxoplasmosis in Mice
PublicationToxoplasmosis may pose a serious threat for individuals with weakened or undeveloped immune systems. However, to date, there is no specific immunoprophylaxis for humans. Thus, the aim of this study was to evaluate the immunogenicity of three trivalent—SAG2-GRA1-ROP1L (SGR), SAG1L-MIC1-MAG1 (SMM), and GRA1-GRA2-GRA6 (GGG)—and two tetravalent—SAG2-GRA1-ROP1-GRA2 (SGRG) and SAG1-MIC1-MAG1-GRA2 (SMMG)—chimeric T. gondii proteins, as...
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IEEE Transactions on Human-Machine Systems
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Machine Translation Summit
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Machine Vision Applications
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Electrust Electrust: Dynamics of Trust and Distrust Creation in Internet Voting
ProjectsProject realized in Gdasnk university of technology according to 101038055 agreement from 2021-04-22
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Practical Evaluation of Internet Systems' Security Mechanisms
PublicationA proposed Internet systems security layer with context-oriented security mechanisms reduces the risk associated with possible vulnerabilities. A metric of the system trust level is proposed, and then evaluated according to a university Internet system.
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Zaufanie w zespole badawczym – studium przypadku (projekt CD NIWA realizowany na Politechnice Gdańskiej)
PublicationArtykuł dotyczy tematyki klimatu pracy zespołowej, ze szczególnym uwzględnieniem zaufania w zespole jako czynnika warunkującego zaangażowanie, efektywność i innowacyjność zespołu. Przeanalizowano znaczenie oraz wymiary zaufania w zespole badawczym na podstawie koncepcji International Team Trust Indicator, czyli dziesięciowymiarowego modelu zaufania. Celem artykułu jest analiza klimatu współpracy i poziomu zaufania w interdyscyplinarnym...
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Zaufanie do marek jako mediator pomiędzy postrzeganym ryzykiem i skłonnością do elektronicznego word-of-mouth
PublicationRozwój Internetu oraz dostęp konsumentów do mediów społecznościowych wpływają na ich zaangażowanie on-line. Odzwierciedla to również sposób, w jaki konsumenci wyrażają opinie o markach i produktach w Sieci. Celem ankiety było zbadanie wpływu postrzeganego ryzyka i zaufania do marki na skłonność konsumentów do electronic word-of-mouth (eWOM). Ponadto, autorzy zbadali rolę zaufania do marki jako mediatora w relacji między postrzeganym...
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Analiza numeryczna i badania doświadczalne wpływu usytuowania stężeń na nośność wyboczeniową modelu kratownicy
PublicationIn the present research the results of experimental test and numerical analyses of a model of a typical truss are presented. The truss linear buckling analysis and non linear static analyses with respect to material and geometrical nonlinearity are conducted. For different stiffnesses and location of braces, the critical load and limit load for the truss are calculated and the threshold bracing stiffness is found. The results of...
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Koncepcja poprawy jakości docierania elementów cienkościennych na docierarce jednotarczowej = Conception of quality improvement of thin-walled elements lapping done on single-disk lapping machine
PublicationPrzedstawiono problem zapewnienia prawidłowych warunków współpracy przedmiotu obrabianego i narzędzia tarczowego w czasie docierania płaskich elementów cienkościennych. Omówiono sposób dociążania elementów podczas obróbki oraz wytrzymałościowy model układu.
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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...