Numerical analysis of coronary artery bypass grafts: An over view

Arterial bypass grafts tend to fail after some years due to the development of intimal thickening (restenosis). Non-uniform hemodynamics following a bypass operation contributes to restenosis and bypass failure can occur due to the focal development of anastomotic intimal hyperplasia. Additionally, surgical injury aggravated by compliance mismatch between the graft and artery has been suggested as an initiating factor for progress of wall thickening along the suture line Vascular grafts that are small in diameter tend to occlude rapidly. Computational fluid dynamics (CFD) methods have been effectively used to simulate the physical and geometrical parameters characterizing the hemodynamics of various arteries and bypass configurations. The effects of such changes on the pressure and flow characteristics as well as the wall shear stress during a cardiac cycle can be simulated. Recently, utilization of fluid and structure interactions have been used to determine fluid flow parameters and structure forces including stress and strains relationships under steady and transient conditions. In parallel to this, experimental diagnostics techniques such as Laser Doppler Anemometry, Particle Image Velocimetry, Doppler Guide wire and Magnetic Resonance Imaging have been used to provide essential information and to validate the numerical results. Moreover, clinical imaging techniques such as magnetic resonance or computed tomography have assisted considerably in gaining a detailed patient-specific picture of the blood flow and structure dynamics. This paper gives a review of recent numerical investigations of various configurations of coronary artery bypass grafts (CABG). In addition, the paper ends with a summary of the findings and the future directions.     

The partial solutions consideration based self-adaptive evolutionary algorithm: A learning structure of neuro-fuzzy networks

Evolutionary computation has become a popular research field due to its global searching ability. Therefore, it raises a challenge to develop an efficient and robustness evolutionary algorithm to not only reduce the evolution process but also increase the chances to meet the global solution. To this end, this study aims to provide a novel evolutionary algorithm named the partial solutions consideration based self-adaptive evolutionary algorithm (PSC-SEA) to address this issue; the proposed algorithm is applied to adjust the parameters of the neuro-fuzzy networks. More specifically, different from the existing evolution algorithms, the partial solutions consideration (PSC) tends to consider both the specializations and complementary relationships of the partial solutions from the complete solution to prevent converging to suboptimal solution. Moreover, a self-adaptive evolutionary algorithm (SEA) is proposed to dynamically adjust the searching space according to the performance. By doing so, the proposed evolutionary algorithm can consider the influence of partial solutions and provide a suitable searching space to increase the chances to meet the global solution. As shown in the results, the proposed evolutionary algorithm obtains better performance and smoother learning curves than other existing evolutionary algorithms. In other words, the proposed evolutionary algorithm can efficient tune the parameters of the neuro-fuzzy networks to meet the global solution. Base on the results, a framework is proposed to build a benchmark for developing the evolutionary algorithms that can not only consider the influence of partial solutions but also provide a suitable searching space.     

Metal-defined polymeric variable optical attenuator

A variable optical attenuator (VOA) based on a metal-defined polymeric optical waveguide has been demonstrated for the first time. The metal film stressor deposited on top of the upper cladding layer not only produces the refractive index change within the core layer, but also acts as a thin-film heater allowing thermal tuning of the optical power within a metal-defined optical waveguide. Fabricated devices exhibit greater than 25 dB of optical attenuation with an applied electrical current of /spl sim/40 mA at 1550-nm wavelength. The switching speed of the VOA exhibits 800 /spl mu/s of rising and 720 /spl mu/s of falling time.     

Comprehensive Study of Emitter-Ledge Thickness of InGaP/GaAs HBTs

A comprehensive study of emitter-ledge thickness of InGaP/GaAs heterojunction bipolar transistors (HBTs) has been undertaken. It is shown that the recombination rate and electron densities are drastically increased near the exposed base surface between the base contact and the emitter ledge. In contrast, the corresponding hole densities are decreased. If the emitter ledge is too thick, current will flow through the undepleted ledge, which increases the emitter-size effect. In contrast, if the emitter ledge is too thin, it may not effectively passivate the surface. Therefore, the thickness of the emitter ledge is a crucial issue and should be carefully considered. It is shown that, from simulated and experimental results, the optimum emitter-ledge thickness of InGaP/GaAs HBT is 100-200 Aring     

赣州市五大产业生产方程与组合预测

依据数学和经济学的理论方法，利用赣州市的历史统计数据，对赣州市的农业、工业、建筑业、运输业、商业分别建立生产方程，进而开展组合预测。     

Multipass hierarchical stereo matching for generation of digital terrain models from aerial images

This paper presents a new multi-pass hierarchical stereo-matching approach for generation of digital terrain models (DTMs) from two overlapping aerial images. Our method consists of multiple passes which compute stereo matches with a coarse-to-fine and sparse-to-dense paradigm. An image pyramid is generated and used in the hierarchical stereo matching. Within each pass, the DTM is refined by using the image pyramid from the coarse to the fine level. At the coarsest level of the first pass, a global stereo-matching technique, the intra-/inter-scanline matching method, is used to generate a good initial DTM for the subsequent stereo matching. Thereafter, hierarchical block matching is applied to image locations where features are detected to refine the DTM incrementally. In the first pass, only the feature points near salient edge segments are considered in block matching. In the second pass, all the feature points are considered, and the DTM obtained from the first pass is used as the initial condition for local searching. For the passes after the second pass, 3D interactive manual editing can be incorporated into the automatic DTM refinement process whenever necessary. Experimental results have shown that our method can successfully provide accurate DTM from aerial images. The success of our approach and system has also been demonstrated with a flight simulation software. Received: 4 November 1996 / Accepted: 20 October 1997     

采用现场总线等技术的综合网络建设

首先对当前企业综合自动化的发展方向和具代表性的过程控制系统进行了简要的介绍，而后着重讨论了工业控制计算机技术、数据通信及网络技术的应用情况．最后提出了当前构建企业综合信息网的可行解决方案。     

Hybrid neural document clustering using guided self-organization and WordNet

Document clustering is text processing that groups documents with similar concepts. It's usually considered an unsupervised learning approach because there's no teacher to guide the training process, and topical information is often assumed to be unavailable. A guided approach to document clustering that integrates linguistic top-down knowledge from WordNet into text vector representations based on the extended significance vector weighting technique improves both classification accuracy and average quantization error. In our guided self-organization approach we integrate topical and semantic information from WordNet. Because a document-training set with preclassified information implies relationships between a word and its preference class, we propose a novel document vector representation approach to extract these relationships for document clustering. Furthermore, merging statistical methods, competitive neural models, and semantic relationships from symbolic Word-Net, our hybrid learning approach is robust and scales up to a real-world task of clustering 100,000 news documents.     

Anatomy of a portable digital mediaprocessor

Portable devices equipped with imaging, video, and audio functionality are proliferating rapidly, and manufacturers are shipping hundreds of millions of such devices. A general-purpose processor (GPP) typically consumes tens of watts to nearly a hundred watts, while a high-performance digital still cameras main processor consumes only hundreds of milliwatts to nearly half a watt. Designing a mediaprocessor with performance comparable to that of a GPP at a power budget two orders of magnitude lower and a cost more than an order of magnitude lower poses quite a challenge. To meet requirements and reduce overall system cost, mediaprocessor designers must integrate the device with an extensive set of peripherals. For performance, cost, and power reasons, application-specific integrated circuits have traditionally been the most popular choice for portable media systems. We discuss the architecture of the DM310, a highly integrated portable digital mediaprocessor, manufactured in a 0.13-micron process.