Art Modeling Studios Liliana 146: A Unique and Stylish Model

BENDIB, Ahmed, CHOUDER, Aissa, KARA, Kamel, KHERBACHI, Abdelhammid, BARKAT, Said and ISSA, Walid (2019). New modeling approach of secondary control layer for autonomous single-phase microgrids. Journal of the Franklin Institute, 356 (13), 6842-6874.

Art Modeling Studios Liliana 146

Download: https://tweeat.com/2vKTIC

Feier, Christina; Polleres, Axel; Dumitru, Roman; Domingue, John; Stollberg, Michael and Fensel, Dieter (2005). Towards intelligent web services: the web service modeling ontology (WSMO). In: 2005 International Conference on Intelligent Computing (ICIC'05), 23-26 Aug 2005, Hefei, China.

Recent thermomechanical modeling to calculate the stress field in industrially direct-chill (DC) cast-aluminum slabs has been successful, but lack of material data limits the accuracy of these calculations. Therefore, the constitutive behavior of three aluminum alloys (AA1050, AA3104, and AA5182) was determined in the as-cast condition using tensile tests at low strain rates and from room temperature to solidus temperature. The parameters of two constitutive equations, the extended Ludwik equation and a combination of the Sellars-Tegart equation with a hardening law, were determined. In order to study the effect of recovery, the constitutive behavior after prestraining at higher temperatures was also investigated. To evaluate the quantified constitutive equations, tensile tests were performed simulating the deformation and cooling history experienced by the material during casting. It is concluded that both constitutive equations perform well, but the combined hardening-Sellars-Tegart (HST) equation has temperature-independent parameters, which makes it easier to implement in a DC casting model. Further, the deformation history of the ingot should be taken into account for accurate stress calculations.

An improved general understanding of riverbed heterogeneity is of importance for all groundwater modeling studies that include river-aquifer interaction processes. Riverbed hydraulic conductivity (K) is one of the main factors controlling river-aquifer exchange fluxes. However, the meter-scale spatial variability of riverbed K has not been adequately mapped as of yet. This study aims to fill this void by combining an extensive field measurement campaign focusing on both horizontal and vertical riverbed K with a detailed geostatistical analysis of the meter-scale spatial variability of riverbed K . In total, 220 slug tests and 45 standpipe tests were performed at two test sites along the Belgian Aa River. Omnidirectional and directional variograms (along and across the river) were calculated. Both horizontal and vertical riverbed K vary over several orders of magnitude and show significant meter-scale spatial variation. Horizontal K shows a bimodal distribution. Elongated zones of high horizontal K along the river course are observed at both sections, indicating a link between riverbed structures, depositional environment and flow regime. Vertical K is lognormally distributed and its spatial variability is mainly governed by the presence and thickness of a low permeable organic layer at the top of the riverbed. The absence of this layer in the center of the river leads to high vertical K and is related to scouring of the riverbed by high discharge events. Variograms of both horizontal and vertical K show a clear directional anisotropy with ranges along the river being twice as large as those across the river.

Objective: Anger and other indices of negative affect have been implicated in a stress-induced pathway to relapse. The Alcoholics Anonymous (AA) literature states that reduction of anger is critical to recovery, yet this proposed mechanism has rarely been investigated. Using lagged, controlled hierarchical linear modeling analyses, this study investigated whether AA attendance mobilized changes in anger and whether such changes explained AA-related benefit. Method: Alcohol-dependent adults (N = 1,706) receiving treatment as part of a clinical trial were assessed at intake and at 3, 6, 9, 12, and 15 months. Results: Findings revealed substantially elevated levels of anger compared with the general population (98th percentile) that decreased over 15-month follow-up but remained high (89th percentile). AA attendance was associated with better drinking outcomes, and higher levels of anger were associated with heavier drinking. However, AA attendance was unrelated to changes in anger. Conclusions: Although support was not found for anger as a mediator, there was strong convergence between AA's explicit emphasis on anger and the present findings: Anger appears to be a serious, enduring problem related to relapse and heavy alcohol consumption. Methodological factors may have contributed to the lack of association between AA and anger, but results suggest that AA attendance alone may be insufficient to alleviate the suffering and alcohol-related risks specifically associated with anger. PMID:20409438

Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. Aims: (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data

Aerosol Modeling System (AMS) that is consisted of the Asian Dust Aerosol Model2 (ADAM2) and the Community Multi-scale Air Quality (CMAQ) modeling system has been employed to document the spatial distributions of the monthly and the annual averaged concentration of both the Asian dust (AD) aerosol and the anthropogenic aerosol (AA), and their total depositions in the Asian region for the year 2010. It is found that the annual mean surface aerosol (PM10) concentrations in the Asian region affect in a wide region as a complex mixture of AA and AD aerosols; they are predominated by the AD aerosol in the AD source region of northern China and Mongolia with a maximum concentration exceeding 300 μg m(-3); AAs are predominated in the high pollutant emission regions of southern and eastern China and northern India with a maximum concentration exceeding 110 μg m(-3); while the mixture of AA and AD aerosols is dominated in the downwind regions extending from the Yellow Sea to the Northwest Pacific Ocean. It is also found that the annual total deposition of aerosols in the model domain is found to be 485 Tg (372 Tg by AD aerosol and 113 Tg by AA), of which 66% (319 Tg) is contributed by the dry deposition (305 Tg by AD aerosol and 14 Tg by AA) and 34% (166 Tg) by the wet deposition (66 Tg by AD aerosol and 100 Tg by AA), suggesting about 77% of the annual total deposition being contributed by the AD aerosol mainly through the dry deposition process and 24% of it by AA through the wet deposition process. The monthly mean aerosol concentration and the monthly total deposition show a significant seasonal variation with high in winter and spring, and low in summer. Copyright 2015 Elsevier B.V. All rights reserved.

Australian coal mines have been facing a major challenge of increasing risk of flooding caused by intensive rainfall events in recent years. In light of growing climate change concerns and the predicted escalation of flooding, estimating flood inundation risk becomes essential for understanding sustainable mine water management in the Australian mining sector. This research develops a spatial multi-criteria decision making prototype for the evaluation of flooding risk at a regional scale using the Bowen Basin and its surroundings in Queensland as a case study. Spatial gridded data, including climate, hydrology, topography, vegetation and soils, were collected and processed in ArcGIS. Several indices were derived based on time series of observations and spatial modeling taking account of extreme rainfall, evapotranspiration, stream flow, potential soil water retention, elevation and slope generated from a digital elevation model (DEM), as well as drainage density and proximity extracted from a river network. These spatial indices were weighted using the analytical hierarchy process (AHP) and integrated in an AHP-based suitability assessment (AHP-SA) model under the spatial risk evaluation framework. A regional flooding risk map was delineated to represent likely impacts of criterion indices at different risk levels, which was verified using the maximum inundation extent detectable by a time series of remote sensing imagery. The result provides baseline information to help Bowen Basin coal mines identify and assess flooding risk when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in this research offers the Australian mining industry, and social and environmental studies around the world, an effective way to produce reliable assessment on flood risk for managing uncertainty in water availability under climate change. Copyright 2015. Published by Elsevier B.V. 2ff7e9595c