Hwyneeds: Methodology, Analysis and Evaluation: TR-433, March 2001

The quadrennial need study was developed to assist in identifying county highway financial needs (construction, rehabilitation, maintenance, and administration) and in the distribution of the road use tax fund (RUTF) among the counties in the state. During the period since the need study was first conducted using HWYNEEDS software, between 1982 and 1998, there have been large fluctuations in the level of funds distributed to individual counties. A recent study performed by Jim Cable (HR-363, 1993), found that one of the major factors affecting the volatility in the level of fluctuations is the quality of the pavement condition data collected and the accuracy of these data. In 1998, the Center for Transportation Research and Education researchers (Maze and Smadi) completed a project to study the feasibility of using automated pavement condition data collected for the Iowa Pavement Management Program (IPMP) for the paved county roads to be used in the HWYNEEDS software (TR-418). The automated condition data are objective and also more current since they are collected in a two year cycle compared to the 10-year cycle used by HWYNEEDS right now. The study proved the use of the automated condition data in HWYNEEDS would be feasible and beneficial in educing fluctuations when applied to a pilot study area. In another recommendation from TR-418, the researchers recommended a full analysis and investigation of HWYNEEDS methodology and parameters (for more information on the project, please review the TR-418 project report). The study reported in this document builds on the previous study on using the automated condition data in HWYNEEDS and covers the analysis and investigation of the HWYNEEDS computer program methodology and parameters. The underlying hypothesis for this study is thatalong with the IPMP automated condition data, some changes need to be made to HWYNEEDS parameters to accommodate the use of the new data, which will stabilize the process of allocating resources and reduce fluctuations from one quadrennial need study to another. Another objective of this research is to investigate the gravel roads needs and study the feasibility of developing a more objective approach to determining needs on the counties gravel road network. This study identifies new procedures by which the HWYNEEDS computer program is used to conduct the quadrennial needs study on paved roads. Also, a new procedure will be developed to determine gravel roads needs outside of the HWYNEED program. Recommendations are identified for the new procedures and also in terms of making changes to the current quadrennial need study. Future research areas are also identified

Cautious Weight Tuning for Link State Routing Protocols

Link state routing protocols are widely used for intradomain routing in the Internet. These protocols are simple to administer and automatically update paths between sources and destinations when the topology changes. However, finding link weights that optimize network performance for a given traffic scenario is computationally hard. The situation is even more complex when the traffic is uncertain or time-varying. We present an efficient heuristic for finding link settings that give uniformly good performance also under large changes in the traffic. The heuristic combines efficient search techniques with a novel objective function. The objective function combines network performance with a cost of deviating from desirable features of robust link weight settings. Furthermore, we discuss why link weight optimization is insensitive to errors in estimated traffic data from link load measurements. We assess performance of our method using traffic data from an operational IP backbone

Feasibility study of an Integrated Program for Aerospace vehicle Design (IPAD). Volume 2: The design process

The extent to which IPAD is to support the design process is identified. Case studies of representative aerospace products were developed as models to characterize the design process and to provide design requirements for the IPAD computing system

Satellite-based precipitation estimation using watershed segmentation and growing hierarchical self-organizing map

This paper outlines the development of a multi-satellite precipitation estimation methodology that draws on techniques from machine learning and morphology to produce high-resolution, short-duration rainfall estimates in an automated fashion. First, cloud systems are identified from geostationary infrared imagery using morphology based watershed segmentation algorithm. Second, a novel pattern recognition technique, growing hierarchical self-organizing map (GHSOM), is used to classify clouds into a number of clusters with hierarchical architecture. Finally, each cloud cluster is associated with co-registered passive microwave rainfall observations through a cumulative histogram matching approach. The network was initially trained using remotely sensed geostationary infrared satellite imagery and hourly ground-radar data in lieu of a dense constellation of polar-orbiting spacecraft such as the proposed global precipitation measurement (GPM) mission. Ground-radar and gauge rainfall measurements were used to evaluate this technique for both warm (June 2004) and cold seasons (December 2004-February 2005) at various temporal (daily and monthly) and spatial (0.04 and 0.25) scales. Significant improvements of estimation accuracy are found classifying the clouds into hierarchical sub-layers rather than a single layer. Furthermore, 2-year (2003-2004) satellite rainfall estimates generated by the current algorithm were compared with gauge-corrected Stage IV radar rainfall at various time scales over continental United States. This study demonstrates the usefulness of the watershed segmentation and the GHSOM in satellite-based rainfall estimations