Application of regional earthquake mitigation optimization

A linear program was developed to help seismically active communities decide: (1) how much to spend on pre-earthquake mitigation that aims to reduce future losses versus waiting until after an event and paying for reconstruction, and (2) which of the many possible mitigation activities to fund so as to minimize overall risk. The mitigation alternatives considered are structural upgrading policies for groups of buildings. Benefits of mitigation are losses avoided in future earthquakes, including structural, non-structural, contents, and time-related losses, and casualties. The model is intended to be used as a tool to support the public regional mitigation planning process. In realistic applications, the model includes millions of variables, thus requiring a special solution method. This paper focuses on two efficient solution algorithms to solve the model—a Dantzig–Wolfe decomposition algorithm and a greedy heuristic algorithm. A comprehensive numerical study compares the two algorithms in terms of solution quality and solution time. The study shows that, compared to the Dantzig–Wolfe algorithm, the heuristic algorithm is much faster as expected, and provides comparable solution quality.     

胖笔记本(替代台式PC)将上市

谈到笔记本电脑大家都希望薄而轻.但是有些笔记本电脑加强了其计算能力.事实上,全功能的,或全一型(All-in-one)的便携式PC占有一般消费和企业市场的很大份额.Mobile Insight Inc.估计,未来的1～1.5年时段内笔记本电脑的销量中全功能的将占有70%.在未来的若干年内追求笔记本的轻薄但要外附模块的便携式PC系统也会加速发展,但是市场的渗透力估计不会很大.     

Optimization of Investments in Natural Gas Distribution Networks

This paper presents an optimization model and solution procedure for planning investments in gas distribution networks for residential customers. The situation can be considered a capital budgeting problem under uncertainty. There is uncertainty about whether a potential customer will convert to gas service if a distribution main is built, the revenue generated if the household does convert, and the cost of constructing the main. A fixed annual budget is allocated to a set of discrete, competing projects over time. The allocation is done by maximizing the expected net present value (NPV) given the decision-maker’s risk preferences. The probability distribution of the NPV for each competing project is created from two statistical models. A binary probit model is used to estimate the probability of conversion for a potential customer. A random effects regression model is used to estimate the revenue generated should a particular potential customer switch to gas. A rollout value greedy heuristic was devised to solve the resulting optimization formulation. Two case studies based on data from a large gas company illustrate the analysis.     

FusionMLS: Highly dynamic 3D reconstruction with consumer-grade RGB-D cameras

Computational Visual Media - Multi-view dynamic three-dimensional reconstruction has typically required the use of custom shutter-synchronized camera rigs in order to capture scenes containing...     

Logistics planning under uncertainty for disposition of radioactive wastes

The US Department of Energy (DOE) faces an enormous environmental remediation challenge involving highly radioactive wastes at former weapons production facilities. The purpose of this analysis is to focus on equipment acquisition and fleet sizing issues related to transportation of wastes from remediation sites to disposal sites. Planning for the transportation of these wastes must be done with recognition of important uncertainties related to overall quantities of waste to be moved, the rate at which the wastes will be prepared for transport, and the certification of suitable transportation containers for use in the effort. However, deadlines for completion of the effort have already been set by the political process, without much regard for these uncertainties. To address this fleet sizing problem, we have created a robust optimization model that focuses on equipment investment decisions. Through this robust optimization, we illustrate how modeling can be used to explore the effects of uncertainty on the equipment acquisition strategy. The disposition of radioactive wastes from DOE sites is an important illustration of a category of problems where equipment investments must be made under conditions of considerable uncertainty. The methodology illustrated in this paper can be applied to this general class of problems.     

Augmenting priority rule heuristics with justification and rollout to solve the resource-constrained project scheduling problem

The key question addressed by the resource-constrained project scheduling problem (RCPSP) is to determine the start times for each activity such that precedence and resource constraints are satisfied while achieving some objective. Priority rule-based heuristics are widely used for large problems. Rollout and justification can be integrated with priority rule heuristics to solve the RCPSP. We develop several such procedures and examine the resulting solution quality and computational cost. We present empirical evidence that these procedures are competitive with the best solution procedures described in the literature.     

Modeling supplier selection and the use of option contracts for global supply chain design

As supply chains become more and more dependent on the efficient movement of materials among facilities that are geographically dispersed there is more opportunity for disruption. One of the common disruptions is the loss of production capability at supplier sites. We formulate a two-stage stochastic program and a solution procedure to optimize supplier selection to hedge against these disruptions. This model allows for the effective quantitative exploration of the trade-off between cost and risks to support improved decision-making in global supply chain design. A realistic case study is explored.     

On-line Free-viewpoint Video： From Single to Multiple View Rendering

In recent years, many image-based rendering techniques have advanced from static to dynamic scenes and thus become video-based rendering （VBR） methods. But actually, only a few of them can render new views on-line. We present a new VBR system that creates new views of a live dynamic scene. This system provides high quality images and does not require any background subtraction. Our method follows a plane-sweep approach and reaches real-time rendering using consumer graphic hardware, graphics processing unit （GPU）. Only one computer is used for both acquisition and rendering. The video stream acquisition is performed by at least 3 webcams. We propose an additional video stream management that extends the number of webcams to 10 or more. These considerations make our system low-cost and hence accessible for everyone. We also present an adaptation of our plane-sweep method to create simultaneously multiple views of the scene in real-time. Our system is especially designed for stereovision using autostereoscopic displays. The new views are computed from 4 webcams connected to a computer and are compressed in order to be transfered to a mobile phone. Using GPU programming, our method provides up to 16 images of the scene in real-time. The use of both GPU and CPU makes this method work on only one consumer grade computer.     

Real-time video-based rendering from uncalibrated cameras using plane-sweep algorithm

In this paper, we present a new online video-based rendering (VBR) method that creates new views of a scene from uncalibrated cameras. Our method does not require information about the cameras intrinsic parameters. For obtaining a geometrical relation among the cameras, we use projective grid space (PGS) which is 3D space defined by epipolar geometry between two basis cameras. The other cameras are registered to the same 3D space by trifocal tensors between these basis cameras. We simultaneously reconstruct and render novel view using our proposed plane-sweep algorithm in PGS. To achieve real-time performance, we implemented the proposed algorithm in graphics processing unit (GPU). We succeed to create novel view images in real-time from uncalibrated cameras and the results show the efficiency of our proposed method.     

Camera array image rectification and calibration for stereoscopic and autostereoscopic displays

This paper presents an image rectification method for an arbitrary number of views with aligned camera center. This paper also describes how to extend this method to easily perform a robust camera calibration. These two techniques can be used for stereoscopic rendering to enhance the perception comfort or for depth from stereo. In this paper, we first expose why epipolar geometry is not suited to solve this problem. Second, we propose a nonlinear method that includes all the images in the rectification process. Then, we detail how to extract the rectification parameters to provide a quasi-Euclidean camera calibration. Our method only requires point correspondences between the views and can handle images with different resolutions. The tests show that it is robust to noise and to sparse point correspondences among the views.