水电站水工闸门运行事故及对策

水电站水工闸门曾因疏于管理、操作失误、重大缺陷没有及时消除,以及闸门启闭电源不可靠等原因,而发生多次运行事故,不仅影响发电等效益的发挥,有的甚至对大坝和下游人民生命财产造成危害.为了防止水工闸门运行事故的发生,应规范闸门操作运行,杜绝人为操作失误,及时消除重大隐患,设置柴油发电应急备用电源,若采用远方操控闸门的运行方式,必须严格实行大坝现场监护人制度.     

Gravity filtration performances of the bio-diatomite dynamic membrane reactor for slightly polluted surface water purification

A bio-diatomite dynamic membrane (BDDM) reactor for surface water treatment under a water head of 30, 40, 50, 60 and 70 cm, respectively, was investigated, which was very effective for pollutants removal. The water head exerted strong influences on filtration flux of BDDM during the precoating process, as well as on the formation of BDDM and turbidity variations. A high filtration flux (approximately 200-300 L/m2 h) could be achieved in the long filtration times of BDDM with a stable effluent turbidity of approximately 0.11-0.25 NTU. The BDDM could remove particles larger than 25 μm completely. The adopted sintered diatomite mainly consisted of macro pores, which were beneficial for improving the filtration flux of BDDM. During the backwash stage, the BDDM could be removed completely by the air backwash.     

一种新颖的CDMA系统下多目标无线定位方法

利用Marginalized粒子滤波算法,处理CDMA(Code Division Multiple Access)系统中多目标无线定位及跟踪问题。在CDMA系统中,由于数据的非线性导致了过大的计算复杂度,并影响到定位的精度。论文主要从CDMA系统中多目标联合检测和建立基于边缘化粒子滤波器的数据融合模型两方面进行研究和分析,解决CDMA中多用户的辨别、定位精度和计算复杂度之间的矛盾。仿真结果证明其方法能够保证多目标定位的精度,并极大地减少计算复杂度。     

Aggregate keyword search on large relational databases

Keyword search has been recently extended to relational databases to retrieve information from text-rich attributes. However, all the existing methods focus on finding individual tuples matching a set of query keywords from one table or the join of multiple tables. In this paper, we motivate a novel problem of aggregate keyword search: finding minimal group-bys covering a set of query keywords well, which is useful in many applications. We develop two interesting approaches to tackle the problem. We further extend our methods to allow partial matches and matches using a keyword ontology. An extensive empirical evaluation using both real data sets and synthetic data sets is reported to verify the effectiveness of aggregate keyword search and the efficiency of our methods.     

Optimal cyclic single crane scheduling for two parallel train oilcan repairing lines

Crane is widely used to move a heavy object from one place to another not only in manufacturing industry but also service industry. As an important resource in the train oilcan repairing, crane scheduling affects directly the productivity of the systems. In this paper, we study cyclic single crane scheduling problem with two parallel train oilcan repairing lines, where jobs are loaded into the line at one end and unloaded at the other end. The processing time at each workstation must be within a given range. There is no buffer between these stations. A crane is used to move jobs between the workstations in two parallel lines. The objective is to schedule the moves to minimize the production cycle. We proposed a time way diagram for two parallel lines and developed a mixed integer linear programming model. Then we extended the model to the scheduling problem with multi-station to eliminate the bottleneck in lines. Examples are given to demonstrate the effectiveness of the model.     

Tree-turn routing: an efficient deadlock-free routing algorithm for irregular networks

In this paper, we propose a general turn model, called a Tree-turn model, for tree-based routing algorithms on irregular topologies. In the Tree-turn model, links are classified as either a tree link or a cross link and six directions are associated with the channels of links. Then we can prohibit some of the turns formed by these six directions such that an efficient deadlock-free routing algorithm, Tree-turn routing, can be derived. There are three phases to develop the Tree-turn routing. First, a coordinated tree for a given topology is created. Second, a communication graph is constructed based on the topology and the corresponding coordinated tree. Third, the forwarding table is set up by using all-pairs shortest path algorithm according to the prohibited turns in the Tree-turn model and the directions of the channels in the communication graph. To evaluate the performance of the proposed Tree-turn routing, we develop a simulator and implement Tree-turn routing along with up*/down* routing, L-turn routing, and up*/down* routing with DFS methodology. The simulation results show that Tree-turn routing outperforms other routing algorithms for all the test cases.     

Contextual correlation based thread detection in short text message streams

Short text message streams are produced by Instant Messaging and Short Message Service which are wildly used nowadays. Each stream contains more than one thread usually. Detecting threads in the streams is helpful to various applications, such as business intelligence, investigation of crime and public opinion analysis. Existing works which are mainly based on text similarity encounter many challenges including the sparse eigenvector and anomaly of short text message. This paper introduces a novel concept of contextual correlation instead of the traditional text similarity into single-pass clustering algorithm to cover the challenges of thread detection. We firstly analyze the contextually correlative nature of conversations in short text message streams, and then propose an unsupervised method to compute the correlative degree. As a reference, a single-pass algorithm employing the contextual correlation is developed to detect threads in massive short text stream. Experiments on large real-life online chat logs show that our approach improves the performance by 11% when compared with the best similarity-based algorithm in terms of F1 measure.     

Relevance feature mapping for content-based multimedia information retrieval

This paper presents a novel ranking framework for content-based multimedia information retrieval (CBMIR). The framework introduces relevance features and a new ranking scheme. Each relevance feature measures the relevance of an instance with respect to a profile of the targeted multimedia database. We show that the task of CBMIR can be done more effectively using the relevance features than the original features. Furthermore, additional performance gain is achieved by incorporating our new ranking scheme which modifies instance rankings based on the weighted average of relevance feature values. Experiments on image and music databases validate the efficacy and efficiency of the proposed framework.     

Robust and efficient ridge-based palmprint matching

During the past decade, many efforts have been made to use palmprints as a biometric modality. However, most of the existing palmprint recognition systems are based on encoding and matching creases, which are not as reliable as ridges. This affects the use of palmprints in large-scale person identification applications where the biometric modality needs to be distinctive as well as insensitive to changes in age and skin conditions. Recently, several ridge-based palmprint matching algorithms have been proposed to fill the gap. Major contributions of these systems include reliable orientation field estimation in the presence of creases and the use of multiple features in matching, while the matching algorithms adopted in these systems simply follow the matching algorithms for fingerprints. However, palmprints differ from fingerprints in several aspects: 1) Palmprints are much larger and thus contain a large number of minutiae, 2) palms are more deformable than fingertips, and 3) the quality and discrimination power of different regions in palmprints vary significantly. As a result, these matchers are unable to appropriately handle the distortion and noise, despite heavy computational cost. Motivated by the matching strategies of human palmprint experts, we developed a novel palmprint recognition system. The main contributions are as follows: 1) Statistics of major features in palmprints are quantitatively studied, 2) a segment-based matching and fusion algorithm is proposed to deal with the skin distortion and the varying discrimination power of different palmprint regions, and 3) to reduce the computational complexity, an orientation field-based registration algorithm is designed for registering the palmprints into the same coordinate system before matching and a cascade filter is built to reject the nonmated gallery palmprints in early stage. The proposed matcher is tested by matching 840 query palmprints against a gallery set of 13,736 palmprints. Experimental results show that the proposed matcher outperforms the existing matchers a lot both in matching accuracy and speed.     

Reference price effect and its implications for decision making in online auctions: An empirical study

Simultaneous supplies of an item by multiple online auction vendors greatly reduce the burden of arduous search that a consumer has to conduct in a brick-and-mortar market. The enriched information set endows all auction participants with added decision flexibility and complexity. One of such flexibilities or complications is the potential of information cross-referencing. In this study, we empirically tested if and how bidders interacted with each other through cross-referencing. Our results strongly supported the existence of cross-referencing. We also identified new strategies and tactical moves as best responses for sellers and bidders under the online simultaneous condition. This research provided another support for the path-dependent nature of online auctions as bidders were found to actively adjust their behavior in avoidance of winner's curse.