广播电视发射台技术指标集中自动测试系统

本文介绍了利用计算机技术、网络技术、三遥技术对广播电视发射技术指标进行实时自动测试的系统，以便进一步为安全优质播出提供技术保证。     

Series resonant ZCS‐PFM DC‐DC power converter with high‐frequency high‐voltage transformer link for high‐power magnetron drive

This paper presents a single lossless inductive snubber‐assisted ZCS‐PFM series resonant DC‐DC power converter with a high‐frequency high‐voltage transformer link for industrial‐use high‐power magnetron drive. The current flowing through the active power switches rises gradually at a turned‐on transient state with the aid of a single lossless snubber inductor, and ZCS turn‐on commutation based on overlapping current can be achieved via the wide range pulse frequency modulation control scheme. The high‐frequency high‐voltage transformer primary side resonant current always becomes continuous operation mode, by electromagnetic loose coupling design of the high‐frequency high‐voltage transformer and the magnetizing inductance of the high‐frequency high‐voltage transformer. As a result, this high‐voltage power converter circuit for the magnetron can achieve a complete zero current soft switching under the condition of broad width gate voltage signals. Furthermore, this high‐voltage DC‐DC power converter circuit can regulate the output power from zero to full over audible frequency range via the two resonant frequency circuit design. Its operating performances are evaluated and discussed on the basis of the power loss analysis simulation and the experimental results from a practical point of view. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 153(3): 79–87, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20126     

CAL delivery selection criteria and authoring systems

Abstract  In the past, authoring systems have been used to generate computer-assisted learning materials that have often followed the rather restrictive programmed learning format. A number of innovative ways of using recently developed systems to develop CAL packages that include a wider range of learning activities (access to data bases, simulations, interactive video, etc.) are described. Analogous to the concept of a media selection model, a computer delivery mode selection model is presented as an aid to decision making for designers. This increase in flexibility should broaden the applicability of computerassisted learning (CAL) to a wider range of educational objectives and raise the level of the cognitive emphasis in learning packages, as well as facilitate the implementation of visually appealing materials. The paper also implies a standard of acceptability for authoring systems.     

A simplified cascade current‐source inverter interconnected to a single‐phase three‐wire distribution system and its application to electric energy storage systems with batteries

A novel current source inverter system interconnected to the single‐phase grid is proposed. It has the same construction as the conventional three‐phase current source inverter that is interconnected to the single‐phase three‐wire distribution system. Though the proposed circuit has no output transformer, it can be equivalently performed as the single‐phase double cascade inverter by diverting the pole transformer in the utility system. By controlling the appropriate scheme, the output currents can be obtained as the five‐level waveforms and their distortions can be decreased sufficiently. It is applied to the interactive electric energy storage system with batteries and the basic discharging characteristics are discussed experimentally. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(2): 50–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10380     

KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS

Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.
This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.     

Authority updating: An expert authority evaluation algorithm considering post‐evaluation and power indices in social networks

In group assessment, the focus is on finding high‐authority experts to improve the reliability of assessment results. In this study, we propose an authority updating algorithm while considering the power and judgement reliability of an expert on the basis of social networks and post‐evaluations. A network power index is established and used to reflect the power of an expert while considering social networks. The measurement of the judgement reliability of an expert considers the post‐evaluation of the objects selected by experts, thereby more scientifically reflecting the reliability of experts. The analysis shows the following: although the social‐network structure influences the authority of experts, the influence weakens when the assessment group is a highly or even fully connected group; the network effect may increase the authority of some experts and reduce that of others, and it will weaken as the network connectivity increases; moreover, the judgement reliability and authority of an expert while considering post‐evaluation can encourage him/her to make fair assessments and strive to reduce his/her motivation and cognitive biases.     

A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems

Scheduling semiconductor wafer manufacturing systems has been viewed as one of the most challenging optimization problems owing to the complicated constraints, and dynamic system environment. This paper proposes a fuzzy hierarchical reinforcement learning (FHRL) approach to schedule a SWFS, which controls the cycle time (CT) of each wafer lot to improve on-time delivery by adjusting the priority of each wafer lot. To cope with the layer correlation and wafer correlation of CT due to the re-entrant process constraint, a hierarchical model is presented with a recurrent reinforcement learning (RL) unit in each layer to control the corresponding sub-CT of each integrated circuit layer. In each RL unit, a fuzzy reward calculator is designed to reduce the impact of uncertainty of expected finishing time caused by the rematching of a lot to a delivery batch. The results demonstrate that the mean deviation (MD) between the actual and expected completion time of wafer lots under the scheduling of the FHRL approach is only about 30 % of the compared methods in the whole SWFS.     

Positive state‐bounding observer for positive interval continuous‐time systems with time delay

This paper is concerned with the problem of positive observer synthesis for positive systems with both interval parameter uncertainties and time delay. Conventional observers may no longer be applicable for such kind of systems due to the positivity constraint on the observers, and they only provide an estimate of the system state in an asymptotic way. A pair of positive observers with state‐bounding feature is proposed to estimate the state of positive systems at all times in this paper. A necessary and sufficient condition for the existence of desired observers is first established, and the observer matrices can be obtained easily through the solutions of a set of linear matrix inequalities (LMIs). Then, to reduce the error signal between the system state and its estimates, an iterative LMI algorithm is developed to compute the optimized state‐bounding observer matrices. Finally, a numerical example is presented to show the effectiveness and applicability of the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Site occupations and ordering behaviour of O phase in Ti2AlNb—based intermetallics

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赋权学生:混合式学习模式的应有之意——以通识类课程社会学的教学实践为例

工业化时代的传统教学模式已滞后于后福特主义生产模式对劳动者的需要。混合式学习模式在最近二十年发展起来,具有知识载体的多元化、知识获取的易得性,以及知识形式的丰富性等显著特征。在社会学的课程实践中,运用混合式学习模式,将赋权学生的教学理念融入课前、课中和课后三个阶段,精心的教学设计激发学生的主体意识,取得较好的教学效果。