广域电力系统整体建模的并行计算技术

在分析广域电力系统整体建模需求的基础上,提出广域电力系统整体建模并行化的方案,设计基于粒子群算法的并行优化算法,开发相关软硬件系统.通过算例系统进行测试,结果证明了广域电力系统整体建模的可行性与有效性,显示了并行化方法在整体建模计算时间上的优越性.表明该电力整体建模的并行计算技术具有较强的工程实用价值.     

山地城市小流域暴雨径流模型的研发及应用

采用ArcEngine二次开发包结合水力学基础算法,建立山地城市暴雨径流模型,以模拟山地城市降雨径流,分析山地城市排水系统的排放能力。应用该模型对重庆市北部新区盘溪河流域排水系统进行了预测和评估,结果表明,模拟结果与实测数据的效率系数Nash-Suttcliffe系数Ens为0.56～0.76,相对误差8.82%～11.8%。模型关键参数率定及敏感性分析表明,最敏感参数为径流宽度、坡度、曼宁系数和不透水面积率。针对排水管道内流量、充满度和溢流检查井个数等方面进行了排水系统排放能力的评估,结果表明,一年一遇暴雨下有0.52%的排水管道长时间处于满流状态,五十年和百年一遇的超载排水管道占排水管道总数5.86%和8.20%;百年一遇暴雨下有0.72%的检查井发生溢流,一年一遇暴雨下有0.31%的检查井发生溢流。该模型实现了对山地城市暴雨径流的产汇过程模拟以及内涝点位置和数量的识别,为城市雨水管网管理提供决策支持。     

基于 GPU 和 Kinect 的快速物体重建

便宜的物体快速三维建模技术是当前计算机视觉领域重要的研究课题.给出了一种基于Kinect传感器的快速物体重建方法,以及基于该方法的一种图形处理器 (Graphic processing unit, GPU)原型系统实现.本文方法主要分为两步: 1)系统的初始标定; 2)全自动的物体重建.对于系统初始标定,提出了一种简单易用的粗标定方法;对于物体重建,提出一种全自动的快速物体重建方法.本文方法鲁棒性高,在出现点云配准错误时仍然能够稳定地得到较理想的重建模型.针对环闭合(Loop-closure)问题,提出了一种全局的点云配准方法.对几类物体的重建实验结果表明,本文方法方便实用,且能得到较好的重建效果.此外,本文还探索了有遮挡物体的重建问题.将本文方法应用于有遮挡物体的重建,也取得了较好的重建效果.     

基于电阻抗扫描成像的乳腺癌自动诊断及参数提取

电阻抗扫描成像作为一种无损功能成像方法, 在乳腺癌诊断方面已经成为X射线乳腺成像的辅助诊断工具. 基于电阻抗扫描成像(Electrical impedance scanning, EIS )的人工诊断方法主观性强、诊断性能差异性较大. 本文提出了一种新的乳腺癌参数提取算法—全参数提取算法(Complete parameters extraction algorithm, CPEA), 并在此基础上设计了一个乳腺癌诊断算子—异常能量指数(Abnormal energy indicator, AEI), 可将乳腺癌诊断及癌灶参数提取合二为一.临床实验表明, 新方法可用于乳腺癌的实时诊断,具有较高的灵敏度和特异度, 同时能够给出癌灶的完整参数信息.     

Reshaping 3D facial scans for facial appearance modeling and 3D facial expression analysis

3D face scans have been widely used for face modeling and analysis. Due to the fact that face scans provide variable point clouds across frames, they may not capture complete facial data or miss point-to-point correspondences across various facial scans, thus causing difficulties to use such data for analysis. This paper presents an efficient approach to representing facial shapes from face scans through the reconstruction of face models based on regional information and a generic model. A new approach for 3D feature detection and a hybrid approach using two vertex mapping algorithms, displacement mapping and point-to-surface mapping, and a regional blending algorithm are proposed to reconstruct the facial surface detail. The resulting models can represent individual facial shapes consistently and adaptively, establishing facial point correspondences across individual models. The accuracy of the generated models is evaluated quantitatively. The applicability of the models is validated through the application of 3D facial expression recognition using the static 3DFE and dynamic 4DFE databases. A comparison with the state of the art has also been reported.     

Optimization of machining processes from the perspective of energy consumption: A case study

One of the primary objectives of sustainable manufacturing is to minimize energy consumption in its manufacturing processes. A strategy of energy saving is to adapt new materials or new processes; but its implementation requires radical changes of the manufacturing system and usually a heavy initial investment. The other strategy is to optimize existing manufacturing processes from the perspective of energy saving. However, an explicit relational model between machining parameters and energy cost is required; while most of the works in this field treat the manufacturing processes as black or gray boxes. In this paper, analytical energy modeling for the explicit relations of machining parameters and energy consumption is investigated, and the modeling method is based on the kinematic and dynamic behaviors of chosen machine tools. The developed model is applied to optimize the machine setup for energy saving. A new parallel kinematic machine Exechon is used to demonstrate the procedure of energy modeling. The simulation results indicate that the optimization can result in 67% energy saving for the specific drilling operation of the given machine tool. This approach can be extended and applied to other machines to establish their energy models for sustainable manufacturing.     

Solving school bus routing using the multiple vehicle traveling purchaser problem: A branch-and-cut approach

School bus routing problems, combining bus stop selection and bus route generation, look simultaneously for a set of bus stops to pick up students from among a group of potential locations, and for bus routes to visit the selected stops and carry the students to their school. These problems, classified as Location-Routing problems, are of interest in densely populated urban areas.This article introduces a generalization of the vehicle routing problem called the multi-vehicle traveling purchaser problem, modeling a family of routing problems combining stop selection and bus route generation. It discusses a Mixed Integer Programming formulation extending previous studies on the classical single vehicle traveling purchaser problem. The proposed model is based on a single commodity flow formulation combining continuous variables with binary variables by means of coupling constraints. Additional valid inequalities are proposed with the purpose of strengthening its Linear Programming relaxation. These valid inequalities are obtained by projecting out the flow variables.We develop a branch-and-cut algorithm that makes use of the proposed model and valid inequalities. This cutting plane algorithm is implemented and tested on a large family of symmetric and asymmetric instances derived from randomly generated problems, showing the usefulness of the proposed valid inequalities.     

An empirical analysis of the determinants of 3G adoption in China

The main aim of this study is to examine the factors that affect Chinese consumers’ intention to adopt 3G. This study has extended the Technology Acceptance Model (TAM) by incorporating the determinants of perceived usefulness, cost, trust, and demographic profiles of Chinese consumers. Data is collected from Chinese consumers via self-administered questionnaire. Structural equation modeling was applied to examine the research model proposed. Our result showed that social influence, service quality and perceived ease of use have a direct and significant relationship with perceived usefulness of 3G, and this in turn affects the consumers’ decision to adopt 3G. Contrary to existing TAM research, perceived ease of use was not found to have a direct and significant influence with Chinese consumers’ intention to adopt 3G. Our study also revealed that those with higher educational level are more likely to adopt 3G. Based on the findings, this research is able to propose several practical recommendations to 3G providers in China, such as enhancing the variety of services provided through collaborations with mobile software and content developers. Furthermore, 3G providers can focus on promoting 3G through services such as “Friends and Family” packages as Chinese consumers’ 3G adoption decisions is influenced by their social network. In terms of theoretical contributions, this study has answered many calls from past researchers to investigate the determinants of perceived usefulness. This research was also conducted in China, which is one of the largest telecommunication markets in the world.     

Robust joint modeling of mean and dispersion through trimming

The Maximum Likelihood Estimator (MLE) and Extended Quasi-Likelihood (EQL) estimator have commonly been used to estimate the unknown parameters within the joint modeling of mean and dispersion framework. However, these estimators can be very sensitive to outliers in the data. In order to overcome this disadvantage, the usage of the maximum Trimmed Likelihood Estimator (TLE) and the maximum Extended Trimmed Quasi-Likelihood (ETQL) estimator is recommended to estimate the unknown parameters in a robust way. The superiority of these approaches in comparison with the MLE and EQL estimator is illustrated by an example and a simulation study. As a prominent measure of robustness, the finite sample Breakdown Point (BDP) of these estimators is characterized in this setting.     

Cost-benefit analysis of an SLA mapping approach for defining standardized Cloud computing goods

Due to the large variety in computing resources and, consequently, the large number of different types of service level agreements (SLAs), computing resource markets face the problem of a low market liquidity. Restricting the number of different resource types to a small set of standardized computing resources seems to be the appropriate solution to counteract this problem. Standardized computing resources are defined through an SLA template. An SLA template defines the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing research results have only introduced static SLA templates so far, the SLA templates cannot reflect changes in user needs and market structures. To address this shortcoming, we present a novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings of users. It allows Cloud users to define mappings between a public SLA template, which is available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates are adapted to the demand of Cloud users, we also analyze the costs and benefits of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, we investigate how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics within adaptation methods allows balancing the costs and benefits of the SLA mapping approach.