An integrated energy planning model for Illinois

An integrated energy supply and demand model for the state of Illinois is described. This equilibrium model is an important tool for integrating information from a variety of planning studies and data bases. A wide range of energy issues affecting diverse areas of the energy system, such as Illinois coal production under alternate oil price assumptions, renewable energy resource potential, and conservation options, can be analyzed by using the model.     

Quantity,controls and functions of large woody debris in Midwestern USA streams

Large woody debris (LWD) can increase stream habitat heterogeneity by providing structure, altering flow patterns, enhancing sediment deposition, forming pools and retaining organic matter. In North America, the role of LWD has been studied extensively in streams of mature forests (e.g. Pacific Northwest), but few studies have assessed LWD in streams of younger forests (e.g. Midwestern USA). Our objectives were to: (1) quantify the volume and abundance of LWD in a set of Midwestern streams; (2) evaluate possible factors influencing LWD quantity; (3) identify the functional roles of LWD; and (4) compare LWD levels in the upper Midwest to those elsewhere in North America. In 2002 and 2003, we measured LWD and geomorphological variables in 15 low‐gradient streams draining previously logged watersheds in the Upper Peninsula of Michigan. Mean (±SE) LWD volume (0.77 ± 0.12 m³ 100 m⁻²) and abundance (33 ± 3 pieces 100 m⁻¹) were 71% and 10% lesser, respectively, than in streams of similar gradient elsewhere in North America. Channel shape (width:depth ratio) explained 30% of the variation in LWD volume (multiple stepwise regression, P = 0.015) while LWD length and length:channel width combined, explained 72% of the variation in LWD density (multiple stepwise regression, P < 0.0001). About 50% of the LWD either stored sediment or stabilized banks and 14% of the LWD formed pools, although pool density was not significantly related to LWD volume or density. LWD levels, overall, were low in upper Midwestern streams, but the relative importance of that LWD to ecosystem function may be magnified in these wood‐poor systems. Copyright © 2006 John Wiley & Sons, Ltd.     

Expert Systems for Construction Project Monitoring

Potential applications of knowledge based expert systems in the area of construction project monitoring and control are described. Originally developed from research in artificial intelligence, these systems are computer programs that can undertake intelligent tasks currently performed by highly skilled people. While some project monitoring can be accomplished by algorithmic procedures, the capability of knowledge based expert systems to deal with illstructured problems and to be extensively modified over time make them desirable for application in this area. Sample applications and heuristic rules in scheduling and inventory control are provided.     

是天使？是魔鬼？——IE7正式版体验

10月19日,历经5年的等待,姗姗来迟的InternetExplorer7正式版终于出现在世人面前。有别于以往渐近式的改进,本次的IE7不管是外观,还是内涵,都发生了翻天覆地的变化。不过,资源占用情况依然不容乐观,本文将带你了解这一切。     

The infrared infiltration and joining of advanced material

JOM - Infrared processing is a newly developed technique for materials processing. Key features include rapid processing, simplicity, and low cost. Because of the rapid processing, very little...     

Estimation of failure intensity for the Weibull process

A Weibull process/non-homogeneous Poisson process is commonly used to analyze the failure behavior of repairable systems. The object of the present study is to obtain exact estimates of the failure intensity of this model at the time of n failures. The resulting MLE estimate is biased and the corrected version for biasedness along with some approximate estimates is given. An analytical and numerical comparison of the relative efficiencies of the MLE of the exact biased, approximated biased, exact unbiased and approximated unbiased of the intensity function is presented. It will be shown that for small n (n < 30) there is quite a large relative difference between the mean squared errors of the exact and approximate estimates of the intensity function. Real failure data are used to illustrate the difference between the exact and approximate estimates of the intensity function.