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Search results for: CLOUD LOAD PREDICTION
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Wpływ azotowania jarzeniowego na niszczenie wodorowe stali przy stałym obciążeniu = Influence of plasma nitriding on steelhydrogen degradation under constant load
PublicationPrzedstawiono wyniki badań wpływu warstwy azotowanej jarzeniowo na podatność stali stopowej 34CrAlNi7-10 na niszczenie wodorowe, wyznaczoną w próbie stałego obciążenia w środowisku kwaśnym przy polaryzacji katodowej o gęstości prądu 1 mA/cm2.Określano odporność na pękanie w czasie 200 godz. dla obciążeń równych 0,88-0,96 siły zrywającej.
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Modelowanie przepływu wód podziemnych w strefie brzegowej morza - możliwości prognozowania = Groundwater flow modeling in the coastline area - prediction possibilities
PublicationSpecyficzne warunki występowania wód podziemnych w strefie brzegowej morza sprawiają, że ich eksploatacja jest sprawą złożoną i powinna być weryfikowana na modelu numerycznym. Zasadniczym zagrożeniem jest ingresja słonych wód morskich, która może być wzbudzona eksploatacją. Innym czynnikiem, który może przyczynić się do ingresji wód słonych do warstwy wodonośnej może być podniesienie się poziomu morza. W pracy przedstawiono wyniki...
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Trends in In Silico Approaches to the Prediction of Biologically Active Peptides in Meat and Meat Products as an Important Factor for Preventing Food-Related Chronic Diseases
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Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information
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Validation study on a new semi-empirical method for the prediction of added resistance in waves of arbitrary heading in analyzing ship speed trial results
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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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Błażej Prusak dr hab.
PeopleBłażej Prusak is Head of the Department of Finance at the Faculty of Management and Economics, Gdansk University of Technology and Editor-in-Chief of the journal Research on Enterprise in Modern Economy - theory and practice (REME), as well as a member of editorial boards of such journals as Intellectual Economics; Space. Economics. Society; Academy of Management. He is the author or co-author of several scientific monographs including:...
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Paweł Lubomski dr inż.
PeoplePaweł Lubomski is the director of the IT Services Centre at the Gdańsk University of Technology. He is responsible for developing and maintaining the central information systems of the university. He is also in charge of the R&D team and works on new approaches to IT systems’ protection. He also acts as the project manager of two big innovative IT projects co-financed by the European Funds. He received a PhD degree in computer...
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Potential of Serum Proteome Patterns Analysis by MALDI-TOF Mass Spectrometry for Prediction of Acute Radiation Injury Response in Head and Neck Cancers Patients
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Parametrization of Backbone−Electrostatic and Multibody Contributions to the UNRES Force Field for Protein-Structure Prediction from Ab Initio Energy Surfaces of Model Systems
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_v_2
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_v_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_h_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_v_5
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_h_5
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_h_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_h_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_v_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_h_5
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_v_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 009_v_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_v_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_v_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_h_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_h_5
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 019_h_4
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_v_2
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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3D printed ABS thermoplastic vs. steel. Dry sliding wear test in constant load & velocity ring on flat configuration. Test parameters: print layer thickness and orientation. Test symbol: 039_h_3
Open Research DataData gathered in sliding ring-on-block (flat contact) tribological experiment. Materials: alloy steel (heat treated) vs. ABS plastic.
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SESNED: Dataset for Event-Based Non-Intrusive Load Monitoring Research
Open Research DataSescom NILM Energy Dataset (SESNED ) description
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Wyznaczanie współczynnika przejmowania ciepła podczas wrzenia w przepływie dwutlenku węgla (Prediction of flow boling heat transfer coefficient for carbon dioxide in minichannels)
PublicationW pracy przedstawiono wyniki obliczeń uzyskane za pomocą własnego modelu półemirycznego dla wybranych danych eksperymentalnych dla wrzenia w przepływie dwutlenku węgla. Metoda obliczeniowa została zweryfikowana z danymi eksperymentalnymi Docoulombiera i innych (2011) oraz Mastrullo i innych (2009). Badania eksperymentalne dotyczą pełnego zakresu zmienności stopnia suchości oraz zakresu prędkości masowej G=200-1200 kg/m2s. rozwijany...
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A Hierarchical Multiscale Approach to Protein Structure Prediction: Production of Low‐Resolution Packing Arrangements of Helices and Refinement of the Best Models with a United‐Residue Force Field
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Polybrominated diphenyl ether (PBDE) concentrations in dust from various indoor environments in Gdańsk, Poland: Prediction of concentrations in indoor air and assessment of exposure of adults
PublicationMonitoring of polybrominated diphenyl ethers (PBDEs) in indoor environments involves the determination of their concentrations in air, airborne particles, and settled dust. Each of these is a source of human exposure to PBDEs. In this study, we attempted to model PBDEs concentrations in various typical indoor environments on the basis of real PBDEs measurements in dust collected from them. The analytical procedure for determining...
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Krzysztof Gierłowski dr inż.
PeopleKrzysztof Gierłowski received his Ph.D. degree in telecommunications from the Faculty of Electronics, Gdańsk University of Technology (GUT), Poland, in 2018. He is author or co-author of more than 80 scientific papers and reviewer for a number of conferences and journals. Krzysztof Gierłowski took part in major IT-oriented projects, including: EU-funded Polish Future Internet Engineering initiative, PL-LAB2020 Infrastructural...
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Wojciech Litwin dr hab. inż.
People1992÷1996 - study on Mechanical Department at Gdansk University of Technology1996 – employed in the Faculty of Ocean Engineering and Ship Technology at the Gdansk University of Technology2004 – PhD2014 – habilitation2016 - vice dean for science at Faculty of Ocean Engineering2020 - dean of the Faculty of Ocean Engineering2021 - head of Institute of Naval Architecture He participated in a number of designing and research programs...
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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...
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Jacek Stefański prof. dr hab. inż.
PeopleJJacek Stefański received M.Sc., Ph.D. and D.Sc. degrees in telecommunications engineering from Gdansk University of Technology (GUT), Poland, in 1993, 2000 and 2012, respectively. Awarded title of Professor by the President of Poland in 2020. Currently, he works as a professor at the Department of Radio Communication Systems and Networks (DRCSN) in GUT. From 2005 to 2009, he worked as an assistant professor in the National Institute...
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Piotr Orzechowski dr inż.
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Comparative Study of Pavement Rehabilitation Using Hot in-Place Recycling and Hot-Mix Asphalt: Performance Evaluation, Pavement Life Prediction, and Life Cycle Cost Analysis
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Analiza porównawcza metod predykcji chwili zgodności fazowejw automatycznym synchronizatorze prądnic = Comparison of the methods of prediction time phase coincidence in automatic synchronizer of power generators
PublicationW artykule porównano dokładność wybranych metod realizacji warunku fazowego podczas synchronizacji obiektów elektroenergetycznych. Do porównania wybrano trzy metody: liniową, wielomianową oraz metodę adaptacyjnej synchronizacji prądnic z ekstrapolacją funkcją wymierną. Badania przeprowadzono dla różnych warunków pracy. Przyjęto stałą różnicę częstotliwości napięć synchronizowanych obiektów, różnicę częstotliwości zmieniającą się...
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Validation of EORTC, CUETO, and EAU risk stratification in prediction of recurrence, progression, and death of patients with initially non–muscle‐invasive bladder cancer (NMIBC): A cohort analysis
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Theoretical designing of selenium heterocyclic non-fullerene acceptors with enhanced power conversion efficiency for organic solar cells: a DFT/TD-DFT-based prediction and understanding
PublicationIn this study, we have designed and explored a new series of non-fullerene acceptors for possible applications in organic solar cells. We have designed four molecules named as APH1 to APH4 after end-capped modification of recently synthesized Y6-Se-4Cl molecule. Density functional theory and time dependent-density functional theory have been employed for computing geometric and photovoltaic parameters of the designed molecules....
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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries (prezentacja na konferencji TWENTY-SIXTH ANNUAL CONFERENCE MULTINATIONAL FINANCE SOCIETY)
PublicationUlotka konferencyjna: http://www.mfsociety.org/modules/modMainContent/uploadFiles/miscFiles/1562848077-MFC2019-Booklet-for-Distribution_2019-06-25.pdf
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Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
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Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)
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AOP173 key event associated pathway predictor – online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis
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IEEE International Conference on Cloud Computing
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Piotr Figura dr inż.
PeoplePiotr Figura is employed as an assistant professor at the Department of Finance at the Faculty of Management and Economics, Gdansk University of Technology. He is a member of Commission for the Verification of Learning Outcomes, as well as an academic reviewer of the Central Exemination Booard. He is the author or co-author of several scientific monographs including: Standard financial indicators for stock enterprises; Classical...
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Validation of EORTC, CUETO and EAU risk stratification in prediction of recurrence, progression and death of patients with initially non-muscle invasive bladder cancer (NMIBC): a cohort analysis with systematic review.
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FEM modelling of screw displacement pile interaction with subsoil
PublicationPredicting the-settlement characteristics of piles is an important element in the designing of pile foundations. The most reliable method in evaluating pile-soil interaction is the static load test, preferably performed with instrumentation for measuring shaft and pile base resistances. This, however, is a mostly post-implementation test. In the design phase, prediction methods are needed, in which numerical simulations play an...