Search results for "Cni"

Historia de una restauración: la Puerta de Serranos

1994

Sobre la decoración esgrafiada en el barroco español

2000

Focused Ultrasound Effects on Osteosarcoma Cell Lines

2019

MRI guided Focused Ultrasound (MRgFUS) has shown to be effective therapeutic modality for non-invasive clinical interventions in ablating of uterine fibroids, in bone metastasis palliative treatments, and in breast, liver, and prostate cancer ablation. MRgFUS combines high intensity focused ultrasound (HIFU) with MRI images for treatment planning and real time thermometry monitoring, thus enabling non-invasive ablation of tumor tissue. Although in the literature there are several studies on the Ultrasound (US) effects on cell in culture, there is no systematic evidence of the biological effect of Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS) treatment on osteosarcoma cells, …

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

2019

A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approac…

Comparison of approaches for generation of fully non-stationary artificial accelerograms

2019

The modelling of the seismic input is a critical aspect when non-linear time-history analyses (NLTHAs) are carried out. As a matter of fact, seismic response of structures is very sensitive to the input excitation time history. The present work aims to highlight the differences in the input modelling and the assessment of seismic response of three r.c. structures employing four generation methods of fully non-stationary artificial accelerogram sets at a given construction site. For each method, seven accelerograms are generated and employed to perform NLTHAs on three r.c. structures having irregular mass and stiffness distributions. The original contribution of the paper relies in the crite…

Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices

2022

We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphoc…

Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks

2019

Abstract The power curve of a wind turbine describes the generated power versus instantaneous wind speed. Assessing wind turbine performance under laboratory ideal conditions will always tend to be optimistic and rarely reflects how the turbine actually behaves in a real situation. Occasionally, some aerogenerators produce significantly different from nominal power curve, causing economic losses to the promoters of the investment. Our research aims to model actual wind turbine power curve and its variation from nominal power curve. The study was carried out in three different phases starting from wind speed and related power production data of a Senvion MM92 aero-generator with a rated powe…

Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level

2019

Abstract A reliable preliminary forecast of heating energy demand of a building by using a detailed dynamic simulation software typically requires an in-depth knowledge of the thermal balance, several input data and a very skilled user. The authors will describe how to use Artificial Neural Networks to predict the demand for thermal energy linked to the winter climatization of non-residential buildings. To train the neural network it was necessary to develop an accurate energy database that represents the basis of the training of a specific Artificial Neural Networks. Data came from detailed dynamic simulations performed in the TRNSYS environment. The models were built according to the stan…

A web-based autonomous weather monitoring system of the town of Palermo and its utilization for temperature nowcasting

2008

Weather data are crucial to correctly design buildings and their heating and cooling systems and to assess their energy performances. In the intensely urbanized towns the effect of climatic parameters is further emphasized by the "urban heat island" phenomenon, known as the increase in the air temperature of urban areas, compared to the conditions measured in the extra-urban areas. The analysis of the heat island needs detailed local climate data which can be collected only by a dedicated weather monitoring system. The Department of Energy and Environmental Researches of the University of Palermo has built up a weather monitoring system that works 24 hours per day and makes data available i…

Short term wind speed prediction using Multi Layer Perceptron

2012

Among renewable energy sources wind energy is having an increasing influence on the supply of energy power. However wind energy is not a stationary power, depending on the fluctuations of the wind, so that is necessary to cope with these fluctuations that may cause problems the electricity grid stability. The ability to predict short-term wind speed and consequent production patterns becomes critical for the all the operators of wind energy. This paper studies several configurations of Artificial Neural Networks (ANN), a well-known tool able to estimate wind speed starting from measured data. The presented ANNs, t have been tested through data gathered in the area of Trapani (Sicily). Diffe…