In recent years, with the development of the economy and the advancement of the national income, personal healthcare has been becoming an important issue. Since the health examination can help people understand their ...
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In recent years, with the development of the economy and the advancement of the national income, personal healthcare has been becoming an important issue. Since the health examination can help people understand their own health conditions clearly, many people make regularly health examinations to avoid missing the best treatment time. So the health examination is an important role for people's health statuses. However, people only get aware of the result of health examination report but they are not clear whether their health trends are high-risk or not. In this paper, we proposed a novel framework for discovering health risk patterns and the relationships between the patterns and a target disease by mining historic health examination data. Moreover, a prediction model for the target disease can be constructed effectively by the discovered information. Through the framework, the physicians can early provide health alerts and medical treatments for people to effectively increase the quality of disease prevention.
Using a proton beam based lithography process, we fabricate and study high aspect ratio metamaterials, revealing distinct 3-dimensional resonances. Increased aspect ratio also leads to enhanced tunability and sensitiv...
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The use of the endovascular prostheses in Abdominal Aortic Aneurysm (EVAR) has proven to be an effective technique to reduce the pressure and rupture risk of aneurysm. Nevertheless, in a long term perspective differen...
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Genetic algorithms (GAs) are increasingly being applied to large scale problems. The traditional MPI-based parallel GAs require detailed knowledge about machine architecture. On the other hand, MapReduce is a powerful...
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Genetic algorithms (GAs) are increasingly being applied to large scale problems. The traditional MPI-based parallel GAs require detailed knowledge about machine architecture. On the other hand, MapReduce is a powerful abstraction proposed by Google for making scalable and fault tolerant applications. In this paper, we show how genetic algorithms can be modeled into the MapReduce model. We describe the algorithm design and implementation of GAs on Hadoop, an open source implementation of MapReduce. Our experiments demonstrate the convergence and scalability up to 10 5 variable problems. Adding more resources would enable us to solve even larger problems without any changes in the algorithms and implementation since we do not introduce any performance bottlenecks.
We use a point-matching approach to numerically compute the Casimir interaction energy for a two perfect-conductor waveguide of arbitrary section. We present the method and describe the procedure used to obtain the nu...
We use a point-matching approach to numerically compute the Casimir interaction energy for a two perfect-conductor waveguide of arbitrary section. We present the method and describe the procedure used to obtain the numerical results. At first, our technique is tested for geometries with known solutions, such as concentric and eccentric cylinders. Then, we apply the point-matching technique to compute the Casimir interaction energy for new geometries such as concentric corrugated cylinders and cylinders inside conductors with focal lines.
Backscatter signatures of multiyear sea ice (MYI) during the late summer and early fall season before the fall freeze-up in the Canadian Arctic Archipelago (CAA) have been obtained through the use of a ship-based pola...
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Backscatter signatures of multiyear sea ice (MYI) during the late summer and early fall season before the fall freeze-up in the Canadian Arctic Archipelago (CAA) have been obtained through the use of a ship-based polarimetric scatterom-eter. The device operates in C-band, and measurements were conducted in swaths from incidence angles of 20-60. Three characteristic sites on MYI floes were investigated in the high Arctic and the central Arctic regions. In situ snow and sea-ice thermophysical data were collected at each site in conjunction with local scatterometer measurements. The thermophysical data were subsequently analyzed using dielectric modeling techniques and coupled with the backscattering measurements (
The system-level modeling and simulation framework Sesame/Artemis aims to efficiently explore the design space of heterogeneous embedded multimedia architectures. The Sesame environment provides several methods and to...
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The system-level modeling and simulation framework Sesame/Artemis aims to efficiently explore the design space of heterogeneous embedded multimedia architectures. The Sesame environment provides several methods and tools to quickly and separately build the application process network model, the target architecture model, and the mapping model of the application onto the architecture. In addition, this tool is designed to allow the refining simulation models smoothly across different abstraction levels and to include support for refining only parts of an architecture model, creating a mixed-level simulation model. In this paper, the Sesame software framework is selected to implement at the black-box architecture model level a parallel H.264/AVC video encoding application targeting multiprocessors platforms.
We present an overview of the validity of the Proximity Force Approximation (PFA) in the calculation of Casimir forces between perfect conductors for different geometries, with particular emphasis for the configuratio...
This paper reports the development of an optimal neural network model for stress-strain behaviour of steel fibre reinforced concrete in direct compression. For this, an algorithm which combines the Akaike's inform...
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This paper reports the development of an optimal neural network model for stress-strain behaviour of steel fibre reinforced concrete in direct compression. For this, an algorithm which combines the Akaike's information criterion (AIC) with the golden-section optimisation technique has been implemented. The extensive computational experiments have been successful in finding a network topology with excellent generalisation capabilities. The model was developed using the experimental results of doctoral research work of the second author. The parameters for modeling included the reinforcing index, the material parameter, and peak stress corresponding to peak strain and normalised strain. The output of the model is the normalised stress. The computational experiments used to implement the method are carried out by employing the three-layer back propagation neural network. The application of the combined algorithm resulted in an optimal topology of 4-26-1. The results of the model were excellent. However, a deviation of 0-15% was noticed in the post peak strain region when compared with experimental results.
Using a proton beam based lithography process, we fabricate and study high aspect ratio metamaterials, revealing distinct 3-dimensional resonances. Increased aspect ratio also leads to enhanced tunability and sensitiv...
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Using a proton beam based lithography process, we fabricate and study high aspect ratio metamaterials, revealing distinct 3-dimensional resonances. Increased aspect ratio also leads to enhanced tunability and sensitivity for practical applications.
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