以奥林匹克精神为纲——中国运动鞋品牌运行之我见

2008年29届奥运会在北京举行，使得有关奥运的话题成为热门中的热门，与运动有关或无关的众多品牌、厂商对北京奥运年均寄予厚望，为赢取更大的收获和提升品牌知名度作最大的努力。其实早在几年前，国内外运动鞋品牌企业就已经大张旗鼓，在产品研发与广告宣传等多方面投入重金，为在这次北京奥运年带来的难得契机中处于市场制高点或明或隐地博杀着。     

含V、N无缝钢管表面外折缺陷产生原因的分析

通过对鞍钢生产的部分批号V、N微合金强化无缝钢管及生产该钢管的原料连铸坯和连轧管坯的表面缺陷进行研究，分析了含V、N钢管表面外折缺陷的成因，提出了改善钢管表面质量的方法。采用改进后工艺生产的无缝管，其表面外折废品量大幅度降低。     

Performance of hashed cache data migration schemes on multicomputers

Many researchers approach the problem of programming distributed memory machines by assuming a global shared name space. Thus the user views the distributed memory of the machine as though it were shared. A major issue that arises at this point is how to manage the memory. When a processor accesses data stored on another processor's memory, data must be moved between the two processors. Once these data are retrieved from another processor's memory, several interesting issues are raised. Where should these data be stored locally? What transformations must be performed to the code to guarantee that the nonlocal accesses reference the correct memory location? What optimizations can be performed to reduce the time spent in accessing the nonlocal data? In this paper we examine various data migration mechanisms that allow an explicit and controlled mapping of data to memory. We describe, experimentally evaluate, and model a set of schemes for storing and retrieving off-processor array elements. The schemes are all based on using hash tables for efficient access of nonlocal data. The three different techniques evaluated are the basic hashed cache, partial enumeration, and full enumeration, the details of which are described in the paper. In all three schemes, nonlocal data are stored in hash tables—the difference is in the amount of memory used by the schemes and the retrieval mechanisms for nonlocal data.     

A result on the hyperstability of a class of hybrid dynamic systems

This paper presents a hyperstability theorem for a class of hybrid dynamic systems composed of coupled differential and difference equations subject to (possibly) time-varying nonlinearities satisfying a Popov-type inequality. The nonlinear controller generates the plant input at all times from its sampled values by defining an extended discrete system. The hyperstability results are obtained from this discrete system of special type whose state consists of the sampled continuous substate and the digital substate of the given hybrid system. Some corollaries and related physical interpretations are also given     

Effectiveness of spatial representation in the formation of network communities: experimental study on community organizer

In this paper, we present and discuss Community Organizer, a system designed to support network communities. The main characteristic of Community Organizer is the use of spatial representations for the relationships among community members including the communications exchanged among these members. These spatial representations reflect the degree of closeness of interests and concerns among the members, and are intended to provide users with clues on how to form network communities. In order to investigate the effectiveness of the proposed spatial representations, we conducted experiments with two different versions of the software. One version offered meaningful spatial representations while the other version did not. The subjects who used the former software version felt a greater sense of ‘community’, enjoyed using the software more, and actively used it longer than the subjects using the latter software version (control condition). These results indicated that the proposed spatial representations are effective in supporting network community formation.     

Time dispersion in large plastic scintillation neutron detectors

Time dispersion (TD) is computed for large neutron detectors using plastic scintillators. It is shown that TD seen by the photomultiplier (PM) tube does not necessarily increase with incident neutron energy, which is a result not fully in agreement with the usual finding     

Learning spreadsheets: human instruction vs. computer-based instruction

The increasing need to instruct students in the use of personal computer software, especially electronic spreadsheets, is placing greater demands on the already full university curriculum. A potential help in meeting these demands is the readily available computer-based software tutorials. In order to explore the feasibility of computer-based instruction as an alternative to human instruction, this research compares two modes of instruction, computer-based and human. An experiment was conducted with groups of business student subjects. The research results indicate no difference in students' attitude towards computer-based instruction and human instruction of spreadsheets. Students' short-term recall of the software syntax being taught is as strong with computer-based instruction as with human instruction. These results were not affected by the level of personal computer experience that students had prior to the experiment. However, the ability to comprehend and immediately apply the software to a task is greater with human instruction than with computer-aided instruction. This advantage holds true for students instructed by experienced and inexperienced instructors.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.