印度大停电及其对我国电网发展的借鉴作用

2012年7月30日和31日,印度接连发生2次大停电事故,其中第一次事故影响了14个邦,而第二次事故则影响了多达22个邦。此次停电事故波及地区广、涉及人口多,对各国电力发展再次敲响警钟。分析了此次大停电事故的主要原因,结合我国电网发展面临的内外部因素,分析了我国电网发展需要从中汲取的经验教训,并提出相关建议。     

A module‐integrated isolated solar micro‐inverter without electrolytic capacitors

This paper presents a module‐integrated isolated solar micro‐inverter. The studied grid‐tied micro‐inverters can individually extract the maximum solar power from each photovoltaic (PV) panel and transfer to the AC utility system. A harmonic suppression technique is used to reduce the DC‐bus capacitance. Electrolytic capacitors are not needed in the studied solar micro‐inverter. High conversion efficiency, high maximum power point tracking accuracy and long lifespan can be achieved. The operation principles and design considerations of the studied PV inverter are analyzed and discussed. A laboratory prototype is implemented and tested to verify its feasibility. Copyright © 2012 John Wiley & Sons, Ltd.     

Design and implementation of a high‐efficiency LiFePO4 battery charger for electric vehicle applications

This letter studies and implements a high‐efficiency LiFePO₄ battery charger. The modular design can satisfy the requirements of series/parallel charging for electric vehicle applications. A CC‐CC‐CV charging scheme is also realized to meet the characteristics of LiFePO₄ battery stacks. A 2 kW laboratory prototype is built and tested. The experimental results are shown to verify the feasibility of the proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

802.11无线网状网中基于时频信道的准动态信道分配算法

该文首次在多天线多信道802.11无线网状网中提出了时频信道的概念。时频信道是通过在时间和频率两个维度划分无线资源取得的。这种划分方法增加了信道数量,使信道划分更加精细,为提高系统的信道利用率做了准备。在时频信道的基础上,提出了准动态信道分配算法。该算法可以和现有的固定信道分配算法结合,实现准动态信道分配,根据链路上负载变化,取得最大的吞吐量。该算法先根据固定信道分配算法为各链路分配相同数量的时频信道,剩余部分当作公共信道。在通信过程中,各链路首先使用分配给自己的信道和空闲的公共信道。如果分配给一个链路的信道不够,且别的链路上的信道有空闲,该链路还可以暂时使用这些空闲信道。理论分析和仿真结果证明该算法可以有效提高系统的吞吐量。     

MINING SURPRISING PATTERNS AND THEIR EXPLANATIONS IN CLINICAL DATA

□ We present a new technique for interactively mining patterns and generating explanations by harnessing the expertise of domain experts. Key to the approach is the distinction between what is unexpected from the perspective of the computational data mining process and what is surprising to the domain experts and interesting relative to their needs. We demonstrate the potential of the approach for discovering patterns and generating rich explanations in a clinical domain. Discovering interesting facts in clinical data is a grand challenge, because medical practitioners and clinicians generally have exceptional knowledge in the problem domain in which they work, however, this knowledge is typically difficult to isolate computationally. To identify the desired surprising patterns, we formally record user knowledge and use that knowledge to filter and constrain the output from an objective data mining technique, with the user making the final judgement about whether a rule is surprising. Specifically, we introduce an unexpectedness algorithm based on association rule mining and Bayesian Networks and a ?-explanations technique for explanation generation to identify unexpected patterns. An implemented prototype is successfully demonstrated using a large clinical database recording incidence, prevalance, and outcome of dialysis and kidney transplant patients.     

Integration of Artificial Immune System and K-Means Algorithm for Customer Clustering

This study proposes a novel artificial immune system (AIS)-based clustering algorithm, which integrates with a K-means (AISK) algorithm for a customer clustering problem. Computational results using Iris, Glass, Wine, and Breast Cancer benchmark datasets indicate that the proposed AIS-based clustering algorithm is more accurate than some particle swarm optimization (PSO)-based clustering algorithms. In addition, the model evaluation results using a daily transaction database provided by a cyberstore also show that the proposed AISK algorithm is superior to PSO-based clustering algorithms.     

A hybrid approach for identification of concurrent control chart patterns

Control chart patterns (CCPs) are widely used to identify the potential process problems in modern manufacturing industries. The earliest statistical techniques, including chart and R chart, are respectively used for monitoring process mean and process variance. Recently, pattern recognition techniques based on artificial neural network (ANN) are very popular to be applied to recognize unnatural CCPs. However, most of them are limited to recognize simple CCPs arising from single type of unnatural variation. In other words, they are incapable to handle the problem of concurrent CCPs where two types of unnatural variation exist together within the manufacturing process. To facilitate the research gap, this paper presents a hybrid approach based on independent component analysis (ICA) and decision tree (DT) to identify concurrent CCPs. Without loss of generality, six types of concurrent CCPs are used to validate the proposed method. Experimental results show that the proposed approach is very successful to handle most of the concurrent CCPs. The proposed method has two limitations in real application: it needs at least two concurrent CCPs to reconstruct their source patterns and it may be incapable to handle the concurrent pattern incurred by two correlated process (“upward trend” and “upward shift”).     

A rugged display: Recent results of flexible cholesteric liquid‐crystal displays

Abstract— A 3‐m‐long rugged flexible display having a novel single‐plastic‐substrate structure has been demonstrated with a coated cholesteric liquid‐crystal mixture. The display is designed to be fabricated by a roll‐to‐roll process to increase productivity at a competitive cost. It has the advantage of having almost no limitation in display length. The high‐resolution (300‐dpi) monochrome cholesteric liquid‐crystal display (ChLCD) can be achieved by using a photo‐addressing method. A single‐layered 10.4‐in. color ChLCD also has been developed with good color and contrast.     

Multisensor based security robot system for intelligent building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man–machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.     

Content-based query processing for video databases

This paper presents a query processing strategy for the content-based video query language named CVQL. By CVQL, users can flexibly specify query predicates by the spatial and temporal relationships of the content objects. The query processing strategy evaluates the predicates and returns qualified videos or frames as results. Before the evaluation of the predicates, a preprocessing is performed to avoid unnecessary accessing of videos which are impossible to be the answers. The preprocessing checks the existence of the content objects specified in the predicates to eliminate unqualified videos. For the evaluation of the predicates, an M-index is designed based on the analysis of the behaviors of the content objects. The M-index is employed to avoid frame-by-frame evaluation of the predicates. Experimental results are presented to illustrate the performance of this approach