Siting park-and-ride facilities using a multi-objective spatial optimization model

Park-and-ride services are an important component of many public transportation systems in the United States. Locating park-and-ride facilities is an essential step when planning for these services. In this research we focus on three major siting/modeling concerns that need to be addressed when siting park-and-ride facilities: covering as much potential demand as possible, locating park-and-ride facilities as close as possible to major roadways, and siting such facilities in the context of an existing system. Unfortunately, existing models do not enable each of these concerns to be simultaneously addressed. This paper presents a multi-objective spatial optimization model for integrating these considerations. This model is applied for siting park-and-ride facilities in Columbus, Ohio. Application results show the usefulness of the developed model in supporting transit planning in an urban region.     

Characterization of Nicalon fibres with varying diameters: Part II Modified Weibull distribution

Diameters vary significantly in a tow of commercial NicalonTM fibres, which is one of the most attractive ceramic reinforcements for structural composites. It was found that the strength distribution of Nicalon fibres could not be adequately characterized using either single- or bi-modal Weibull distribution. A recently proposed modified Weibull distribution can account for the effect of varying diameter in the characterization of fibre strength. To verify the validity of the modified Weibull distribution, comprehensive mechanical testing and fractographic studies have been conducted on Nicalon SiC fibres with diameters varying from 8 to 22 m. The experimental results have been reported in Part I. Part II of this paper further modifies the derivation of the modified Weibull distribution to yield a relationship which is similar in form, but soundly based on experimental findings. Factors considered in the modified Weibull distribution include the dependence of fracture toughness and flaw density on fibre diameter, both of which may vary with fibre diameter, as reported in Part I. Comparison with experimental data shows that the current modified Weibull distribution works very well, while both single-modal and bi-modal Weibull distributions are inadequate for describing Nicalon fibres with varying diameters. © 1998 Chapman & Hall     

Hardware/software co-design of a real-time kernel based tracking system

The probabilistic visual tracking methods using color histograms have been proven to be robust to target model variations and background illumination changes as shown by the recent research. However, the required computational cost is high due to intensive image data processing. The embedded solution of such algorithms become challenging due to high computational power demand and algorithm complexity. This paper presents a hardware/software co-design architecture for implementation of the well-known kernel based mean shift tracking algorithm. The design uses color histogram of the target as tracking feature. The target is searched in the consecutive images by maximizing the statistical match of the color distributions. The target localization is based on gradient based iterative search instead of exhaustive search which makes the system capable of achieving frame rate up to hundreds of frames per second while tracking multiple targets. The design, which is fully standalone, is implemented on a low-cost medium-size field programmable gate array (FPGA) device. The hardware cost of the design is compared with some other tracking systems. The performance of the system in terms of speed is evaluated and compared with the software based implementation. It is expected that the proposed solution will find its utility in applications like embedded automatic video surveillance systems.     

Dynamic Compensation for Control of a Rotary wing UAV Using Positive Position Feedback

This paper presents a novel compensation method for the coupled fuselage-rotor mode of a Rotary wing Unmanned Aerial Vehicle (RUAV). The presence of stabilizer bar limits the performance of attitude control of an RUAV. In this paper, a Positive Position Feedback (PPF) is introduced to increase the stability margins and allow higher control bandwidth. The identified model is used to design a PPF controller to mitigate the presence of stabilizer bar. Parameters for the linear RUAV model are obtained by performing linear system identification about a few selected points. This identification process gives complete RUAV dynamics and is suitable for designing a Stability Augmentation System (SAS) of an RUAV. The identified parameters of an RUAV model are verified using experimental flight data and can be used to obtain the nonlinear model of an RUAV. The performance of the proposed algorithm is tested using a high-fidelity RUAV simulation model, which is validated through experimental flight data. The closed-loop response of the rotorcraft indicates that the desired attitude performance is achieved while ensuring that the coupled fuselage-rotor mode is effectively compensated without penalizing the phase response.     

Multi-objective rule mining using a chaotic particle swarm optimization algorithm

In this paper, classification rule mining which is one of the most studied tasks in data mining community has been modeled as a multi-objective optimization problem with predictive accuracy and comprehensibility objectives. A multi-objective chaotic particle swarm optimization (PSO) method has been introduced as a search strategy to mine classification rules within datasets. The used extension to PSO uses similarity measure for neighborhood and far-neighborhood search to store the global best particles found in multi-objective manner. For the bi-objective problem of rule mining of high accuracy/comprehensibility, the multi-objective approach is intended to allow the PSO algorithm to return an approximation to the upper accuracy/comprehensibility border, containing solutions that are spread across the border. The experimental results show the efficiency of the algorithm.     

An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows

Binary image representation is essential format for document analysis. In general, different available binarization techniques are implemented for different types of binarization problems. The majority of binarization techniques are complex and are compounded from filters and existing operations. However, the few simple thresholding methods available cannot be applied to many binarization problems. In this paper, we propose a local binarization method based on a simple, novel thresholding method with dynamic and flexible windows. The proposed method is tested on selected samples called the DIBCO 2009 benchmark dataset using specialized evaluation techniques for binarization processes. To evaluate the performance of our proposed method, we compared it with the Niblack, Sauvola and NICK methods. The results of the experiments show that the proposed method adapts well to all types of binarization challenges, can deal with higher numbers of binarization problems and boosts the overall performance of the binarization.     

Kosha: A Peer-to-Peer Enhancement for the Network File System

The storage needs of modern scientific applications are growing exponentially, and designing economical storage solutions for such applications – especially in Grid environments – is an important research topic. This work presents Kosha, a system that aims to harvest redundant storage space on cluster nodes and user desktops to provide a reliable, shared file system that acts as a large distributed storage. Kosha utilizes peer-to-peer (p2p) mechanisms to enhance the widely-used Network File System (NFS). P2P storage systems provide location transparency, mobility transparency, load balancing, and file replication – features that are not available in NFS. On the other hand, NFS provides hierarchical file organization, directory listings, and file permissions, which are missing from p2p storage systems. By blending the strengths of NFS and p2p storage systems, Kosha provides a low overhead storage solution. Our experiments show that compared to unmodified NFS, Kosha introduces a 3.3% fixed overhead and 4.5% additional overhead as nodes are increased from two to sixteen. For larger number of nodes, the additional overhead increases slowly. Kosha achieves load balancing in distributed directories, and guarantees or better file availability.*This work was supported in part by an NSF CAREER award (ACI-0238379).Troy A. Johnson was supported by a U.S. Department of Education GAANN doctoral fellowship.     

基于制造资源能力的装夹工艺分层设计技术

为发展创成式的计算机辅助工艺设计,研究了计算机辅助工艺设计系统中工件装夹规划的自动生成算法.基于扩展有向图,建立了零件的公差信息和基准-加工特征关系的数学表示模型,基于公差分析和制造资源能力模型,建立了从单件层到多件层的工件装夹工艺生产算法.该数学模型和算法可自动识别工件的加工特征、装夹基准,并根据制造资源能力和公差分析对装夹进行优化分组,实现装夹分组对工件加工精度的影响最小化,进而生成装夹规程.最后以实例证明了该方法的可行性.