开发有线电视收费管理系统需注意的问题

分析有线电视业务及用户管理中出现的问题与解决办法，为系统的开发建立数据模型，以确保有线电视网络公司和用户的利益。     

Information-Based Evaluation Criterion for Classifier's Performance

In the past few years many systems for learning decision rules from examples were developed. As different systems allow different types of answers when classifying new instances, it is difficult to appropriately evaluate the systems' classification power in comparison with other classification systems or in comparison with human experts. Classification accuracy is usually used as a measure of classification performance. This measure is, however, known to have several defects. A fair evaluation criterion should exclude the influence of the class probabilities which may enable a completely uninformed classifier to trivially achieve high classification accuracy. In this paper a method for evaluating the information score of a classifier's answers is proposed. It excludes the influence of prior probabilities, deals with various types of imperfect or probabilistic answers and can be used also for comparing the performance in different domains.     

Consolidation of Long-Term Memory: Evidence and Alternatives.

Memory loss in retrograde amnesia has long been held to be larger for recent periods than for remote periods, a pattern usually referred to as the Ribot gradient. One explanation for this gradient is consolidation of long-term memories. Several computational models of such a process have shown how consolidation can explain characteristics of amnesia, but they have not elucidated how consolidation must be envisaged. Here findings are reviewed that shed light on how consolidation may be implemented in the brain. Moreover, consolidation is contrasted with alternative theories of the Ribot gradient. Consolidation theory, multiple trace theory, and semantization can all handle some findings well but not others. Conclusive evidence for or against consolidation thus remains to be found. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Interval Fuzzy Multiobjective Watershed Management Model for the Lake Qionghai Watershed, China

Integrated watershed management is required to ensure the reasonable use of resources and reconcile interactions among natural and human systems. In the present study, an interval fuzzy multiobjective programming (IFMOP) method was used to solve an integrated watershed management problem. Based on system analysis, an IFMOP model suitable for a lake watershed system {IFMOPLWS} was developed and applied to the Lake Qionghai watershed in China. Scenario analysis and an interactive approach were used in the solution process. In this manner, various system components were incorporated into one framework for holistic consideration and optimization. Integrality and uncertainty, as well as the multiobjective and dynamic characteristics of the watershed system, were well addressed. Using two scenarios, two planning schemes were generated. Agriculture, tourism, macroeconomics, cropland use, water supply, forest coverage, soil erosion, and water pollution were fully interpreted and compared to identify a preferable planning alternative for local agencies. This study showed that the IFMOPLWS is a powerful tool for integrated watershed management planning and can provide a solid base for sustainable watershed management.     

一种增强型冲突分解算法

冲突分解算法是一种能有效改善无线信道多址接入协议的方式。本文对传统的冲突分解算法——树形冲突分解算法和先到先服务冲突分解算法进行了深入研究和仿真，探讨了这两种算法的优点和不足之处，提出了一种增强型的冲突分解算法（Enhanced Splitting Algorithm，ESA）。该算法继承了树形冲突分解算法和先到先服务算法的优点，不仅考虑了碰撞分组产生的时间，还考虑了分组的产生间隔，从而有效地提高了冲突分解算法的性能。仿真结果显示ESA算法是一种可行的算法。     

Dynamique motivationnelle de l'epuisement et du bien-etre chez des enseignants africains.

This study examines the links between antecedents and consequences of Gabonese teachers' (N= 152) work motivation. The theoretical underpinnings are based on the Motivational Model of Job Burnout (MMJB) which is grounded in Self-Determination Theory (SDT) and states that the more supervisors satisfy an employee's need for self-determination, competence, and relatedness, the more self-determined is the latter's work motivation. The level of self-determined motivation has an impact on job satisfaction, which in turn determines life satisfaction. Higher levels of self-determined motivation also buffer emotional exhaustion and psychological distress. The model was confirmed via structural equation modeling and provides support for the validity and generalizability of the MMJB and SDT. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dynamic stiffness vibration analysis using a high‐order beam model

This work presents the derivation of the exact dynamic stiffness matrix for a high‐order beam element. The terms are found directly from the solutions of the differential equations that describe the deformations of the cross‐section according to the high‐order theory, which include cubic variation of the axial displacements over the cross‐section of the beam. The model has six degrees of freedom at the two ends, one transverse displacement and two rotations, and the end forces are a shear force and two end moments. Using the dynamic stiffness matrix exact vibration frequencies for beams with various combinations of boundary conditions are tabulated and compared with results from the Bernoulli–Euler and Timoshenko beam models. Copyright © 2003 John Wiley & Sons, Ltd.     

Many-Body Terms in van der Waals Cohesion Energy of Nanotubes

We have developed a model for the calculation of van der Waals force for layered systems with axial symmetry. Our result can be applied to compute the cohesion of a carbon nanotube to a substrate, the cohesion between nanotubes, and between shells of multiwall nanotubes. We have obtained unusal power laws for the distance dependence of the many-body van der Waals potential.     

Web-based systems design: a study of contemporary practices and an explanatory framework based on “method-in-action”

This paper reports the findings of a detailed study of Web-based systems design (WBSD) practices in Ireland based on data collected over a 3-year period (2002–2005), the objectives of which were to (1) contribute towards a richer understanding of the current “real-world” context of WBSD by characterising the profile of a typical project (team size, timeframe, nature of requirements, etc.) and identifying the key challenges, constraints, and imperatives (i.e. “mediating factors”) faced by Web-based system designers, and (2) understand how those contextual parameters and mediating factors influence the activity of WBSD as regards the selection and enactment of whatever design practices are therefore engaged (i.e. the use of methods, procedures, etc.). Data was gathered through a survey which yielded 165 usable responses, and later through a series of semi-structured qualitative interviews. Using grounded theory, an explanatory conceptual framework is derived, based on an extension of the “method-in-action” model, the application of which to WBSD has not been previously investigated in depth. It is proposed that this framework of WBSD issues is valuable in a number of ways to educators, researchers, practitioners, and method engineers.     

Multiagent learning using a variable learning rate

Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on the policies of the other agents. This creates a situation of learning a moving target. Previous learning algorithms have one of two shortcomings depending on their approach. They either converge to a policy that may not be optimal against the specific opponents' policies, or they may not converge at all. In this article we examine this learning problem in the framework of stochastic games. We look at a number of previous learning algorithms showing how they fail at one of the above criteria. We then contribute a new reinforcement learning technique using a variable learning rate to overcome these shortcomings. Specifically, we introduce the WoLF principle, “Win or Learn Fast”, for varying the learning rate. We examine this technique theoretically, proving convergence in self-play on a restricted class of iterated matrix games. We also present empirical results on a variety of more general stochastic games, in situations of self-play and otherwise, demonstrating the wide applicability of this method.