Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (653)
  • Open Access

    ARTICLE

    Using Pharmacokinetic Modeling and Electronic Health Record Data to Predict Clinical and Safety Outcomes after Methylprednisolone Exposure during Cardiopulmonary Bypass in Neonates

    Henry P. Foote1, Huali Wu2, Stephen J. Balevic1,2, Elizabeth J. Thompson1,2, Kevin D. Hill1,2, Eric M. Graham3, Christoph P. Hornik1,2, Karan R. Kumar1,2,*

    Congenital Heart Disease, Vol.18, No.3, pp. 295-313, 2023, DOI:10.32604/chd.2023.026262

    Abstract Background: Infants undergoing cardiac surgery with cardiopulmonary bypass (CPB) frequently receive intra-operative methylprednisolone (MP) to suppress CPB-related inflammation; however, the optimal dosing strategy and efficacy of MP remain unclear. Methods: We retrospectively analyzed all infants under 90 days-old who received intra-operative MP for cardiac surgery with CPB from 2014–2017 at our institution. We combined real-world dosing data from the electronic health record (EHR) and two previously developed population pharmacokinetic/pharmacodynamic models to simulate peak concentration (Cmax) and area under the concentration-time curve for 24 h (AUC24) for MP and the inflammatory cytokines interleukin-6 (IL-6) and interleukin-10 (IL-10). We evaluated the relationships… More > Graphic Abstract

    Using Pharmacokinetic Modeling and Electronic Health Record Data to Predict Clinical and Safety Outcomes after Methylprednisolone Exposure during Cardiopulmonary Bypass in Neonates

  • Open Access

    ARTICLE

    Modeling Price-Aware Session-Based Recommendation Based on Graph Neural Network

    Jian Feng*, Yuwen Wang, Shaojian Chen

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 397-413, 2023, DOI:10.32604/cmc.2023.038741

    Abstract Session-based Recommendation (SBR) aims to accurately recommend a list of items to users based on anonymous historical session sequences. Existing methods for SBR suffer from several limitations: SBR based on Graph Neural Network often has information loss when constructing session graphs; Inadequate consideration is given to influencing factors, such as item price, and users’ dynamic interest evolution is not taken into account. A new session recommendation model called Price-aware Session-based Recommendation (PASBR) is proposed to address these limitations. PASBR constructs session graphs by information lossless approaches to fully encode the original session information, then introduces item price as a new… More >

  • Open Access

    ARTICLE

    CONVECTIVE HOT AIR DRYING KINETICS OF RED BEETROOT IN THIN LAYERS

    Abhishek Dasorea,* , Tarun Polavarapub , Ramakrishna Konijetic , Naveen Puppalad ,

    Frontiers in Heat and Mass Transfer, Vol.14, No.1, pp. 1-8, 2020, DOI:10.5098/hmt.14.23

    Abstract The effect of air temperature on drying kinetics of red beetroot slices was investigated experimentally in a cabinet tray dryer. Drying was carried out at 70, 75, 80, and 85 ° More >

  • Open Access

    ARTICLE

    MODELING OF THE FLOW AND HEAT TRANSFER OF SUPERCRITICAL CO2 FLOWING IN SERPENTINE TUBES

    Teng Huanga,* , Xuefang Li a,† , Lin Chengb,‡

    Frontiers in Heat and Mass Transfer, Vol.15, No.1, pp. 1-8, 2020, DOI:10.5098/hmt.15.15

    Abstract As a non-flammable, non-toxic refrigerant, supercritical CO2 (ScCO2) has been increasingly used for heat transfer applications. In this study, the ScCO2 flow and heat transfer in a set of full-size three-dimensional serpentine tubes were modeled with different inner diameters and tube pitches. The standard k-epsilon model was used for the turbulence modeling. The results show the effect of the different tube inner diameters and tube pitches on the flow and heat transfer of ScCO2 for a given flow flux or inlet Reynolds number. The heat transfer coefficient decreases as both the tube pitch and the inner diameter increase for a… More >

  • Open Access

    ARTICLE

    Modeling & Evaluating the Performance of Convolutional Neural Networks for Classifying Steel Surface Defects

    Nadeem Jabbar Chaudhry1,*, M. Bilal Khan2, M. Javaid Iqbal1, Siddiqui Muhammad Yasir3

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 245-259, 2022, DOI:10.32604/jai.2022.038875

    Abstract Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured with an RGB camera. Defects must be detected early to take timely corrective action due to production concerns. For image classification up till now, a model-based method has been utilized, which indicated the predicted reflection characteristics of surface defects in comparison to flaw-free surfaces. The problem of detecting steel surface defects has grown in importance as a result of the vast range of steel applications in end-product… More >

  • Open Access

    ARTICLE

    Étude de la vulnérabilité à la pollution du système phréatique du sahel de Sfax par les outils SIG

    Nadia Trabelsi, Imen Hentati, Ibtissem Triki, Moncef Zairi

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 317-338, 2019, DOI:10.3166/rig.2019.00087

    Abstract The Sfax phreatic system is an important source of water supply. The latter is constantly threatened by nitric pollution. In order to protect this aquifer, a study of the intrinsic vulnerability has been carried out using the SI (Susceptibility Index) method. The model takes into consideration the various vulnerability criteria governing the process of contaminant transfer. These are geological, hydrogeological, land use, topography, and meteorological factors. In this study, a method derived from the SI model is presented (modified SI). The model is based on an approach that integrates hydrological modeling under Agriflux and GIS. Indeed, the use of GIS… More >

  • Open Access

    ARTICLE

    Modeling for application data with 3D spatiale feature in MADS

    Chamseddine Zaki1 , Mohamed Ayet1,2, Allah Bilel Soussi2

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 255-262, 2019, DOI:10.3166/rig.2019.00086

    Abstract A conceptual spatiotemporal data model must be able to offer users a semantic richness of expression to meet their diverse needs concerning the modeling of spatio-temporal data. The conceptual spatiotemporal data model must be able to represent the objects, relationships and events that can occur in a field of study, track data history, support the multirepresentation of these data, and represent temporal and spatial data with two and three dimensions features. The model must also allow the assignment of different types of constraints to relations and provide a complete orthogonality between dimensions and concepts. The MADS model meets several requirements… More >

  • Open Access

    ARTICLE

    Modélisation sémantique et programmation générative pour une simulation multi-agent dans le contexte de gestion de catastrophe

    Claire Prudhomme1 , Ana Roxin2 , Christophe Cruz2 , Frank Boochs1

    Revue Internationale de Géomatique, Vol.30, No.1, pp. 37-65, 2020, DOI:10.3166/rig.2020.00102

    Abstract Disaster management requires collaborative preparedness among the various stakeholders. Collaborative exercises aim to train stakeholders to apply the plans prepared and to identify potential problems and areas for improvement. As these exercises are costly, computer simulation is an interesting tool to optimize preparation through a wider variety of contexts. However, research on simulation and disaster management focuses on a particular problem rather than on the overall optimization of the plans prepared. This limitation is explained by the challenge of creating a simulation model that can represent and adapt to a wide variety of plans from various disciplines. The work presented… More >

  • Open Access

    ARTICLE

    La genèse systémique d’empreinte pour une maîtrise de l’observation de la Terre

    Mireille Fargette1 , Maud Loireau2, Najet Raouani3 , Thérèse Libourel4

    Revue Internationale de Géomatique, Vol.31, No.1, pp. 135-197, 2022, DOI:10.3166/RIG.31.135-197

    Abstract This work is interested in observation, in scientific knowledge acquired from what is perceived (Link making Sense) from a complex systemic world. The approach leads to proposing the concept of imprint within the interdisciplinary framework “System – Reality – World as perceived – Model” and testing it against data, then to proposing systemic ontology as an approach. This makes it possible to deploy the Link making Shape from the systemic domain to the world as perceived, to analyze and describe the relevant part in the data and to show how the whole of this mostly symbolic work can contribute, with… More >

  • Open Access

    ARTICLE

    Explorer les processus de mobilité passée
    Raisonnement ontologique fondé sur la connaissance des pratiques socioculturelles et des vestiges archéologiques

    Laure Nuninger1 , Thérèse Libourel2, Xavier Rodier3, Rachel Opitz4, Philip Verhagen5, Catherine Fruchart1, Clément Laplaige3, Samuel Leturcq3, Nathanael Levoguer3

    Revue Internationale de Géomatique, Vol.31, No.1, pp. 81-110, 2022, DOI:10.3166/RIG.31.81-110

    Abstract In this article we propose an original approach designed by archaeologists and a computer scientist for knowledge creation in studies of movement. Using case studies, we analyze how researchers have identified, conceptualized, and linked the material traces describing various movement processes in a given region. Then, we explain how we construct ontologies that enable us to explicitly relate material elements, identified in the observed landscape, to the knowledge or theory that explains their role and relationships within the movement process. Combining formal pathway systems, so-called « Path framework systems » and informal movement systems, so-called « Pathway systems », through… More >

Displaying 1-10 on page 1 of 653. Per Page  

Share Link