Mining Co-Location Patterns with Rare Events from Spatial Data Sets

A co-location pattern is a group of spatial features/events that are frequently co-located in the same region. For example, human cases of West Nile Virus often occur in regions with poor mosquito control and the presence of birds. For co-location pattern mining, previous studies often emphasize the equal participation of every spatial feature. As a result, interesting patterns involving events with substantially different frequency cannot be captured. In this paper, we address the problem of mining co-location patterns with rare spatial features. Specifically, we first propose a new measure called the maximal participation ratio (maxPR) and show that a co-location pattern with a relatively high maxPR value corresponds to a co-location pattern containing rare spatial events. Furthermore, we identify a weak monotonicity property of the maxPR measure. This property can help to develop an efficient algorithm to mine patterns with high maxPR values. As demonstrated by our experiments, our approach is effective in identifying co-location patterns with rare events, and is efficient and scalable for large-scale data sets.

A base62 transformation format of ISO 10646 for multilingual identifiers

ISO 10646 Universal Character Set (UCS) is a 31‐bit coding architecture that covers symbols in most of the world's written languages. Identifiers in programming languages are usually defined by using alphanumeric characters of ASCII, which represent mainly English words. An approach for working around this deficiency is to encode multilingual identifiers into the alphanumeric range of ASCII. For case‐sensitive languages, an encoding that utilizes [0–9][A–Z][a–z] can be more space‐efficient for multilingual identifiers. This paper proposes a base62 transformation format of ISO 10646 called UTF‐62. The resulting string of UTF‐62 is within a [0–9][A–Z][a–z] range, a total of 62 base characters. UTF‐62 also preserves the lexicographic sorting order of UCS‐4. Copyright © 2001 John Wiley & Sons, Ltd.     

多媒体实时传输协议RTP

文章分析了现有网络协议支持多媒体通信存在的问题,介绍了实时传输协议ＲＴＰ的概念和功能,对多媒体传输的支持以及实现等技术。     

Internet综合服务模型和分类服务模型

文章介绍了未来Ｉｎｔｅｒｎｅｔ中存在的两种服务模型,综合服务（Ｉｎｔ－Ｓｅｒｖ）和分类服务（Ｄｉｆｆ—Ｓｅｒｖ）,并对它们进行了评价。     

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.     

Probabilistic skylines on uncertain data: model and bounding-pruning-refining methods

Uncertain data are inherent in some important applications. Although a considerable amount of research has been dedicated to modeling uncertain data and answering some types of queries on uncertain data, how to conduct advanced analysis on uncertain data remains an open problem at large. In this paper, we tackle the problem of skyline analysis on uncertain data. We propose a novel probabilistic skyline model where an uncertain object may take a probability to be in the skyline, and a p-skyline contains all objects whose skyline probabilities are at least p (0 < p ≤ 1). Computing probabilistic skylines on large uncertain data sets is challenging. We develop a bounding-pruning-refining framework and three algorithms systematically. The bottom-up algorithm computes the skyline probabilities of some selected instances of uncertain objects, and uses those instances to prune other instances and uncertain objects effectively. The top-down algorithm recursively partitions the instances of uncertain objects into subsets, and prunes subsets and objects aggressively. Combining the advantages of the bottom-up algorithm and the top-down algorithm, we develop a hybrid algorithm to further improve the performance. Our experimental results on both the real NBA player data set and the benchmark synthetic data sets show that probabilistic skylines are interesting and useful, and our algorithms are efficient on large data sets.     

Modeling NOx emissions from coal-fired utility boilers using support vector regression with ant colony optimization

Modeling NO_x emissions from coal fired utility boiler is critical to develop a predictive emissions monitoring system (PEMS) and to implement combustion optimization software package for low NO_x combustion. This paper presents an efficient NO_x emissions model based on support vector regression (SVR), and compares its performance with traditional modeling techniques, i.e., back propagation (BPNN) and generalized regression (GRNN) neural networks. A large number of NO_x emissions data from an actual power plant, was employed to train and validate the SVR model as well as two neural networks models. Moreover, an ant colony optimization (ACO) based technique was proposed to select the generalization parameter C and Gaussian kernel parameter γ. The focus is on the predictive accuracy and time response characteristics of the SVR model. Results show that ACO optimization algorithm can automatically obtain the optimal parameters, C and γ, of the SVR model with very high predictive accuracy. The predicted NO_x emissions from the SVR model, by comparing with the BPNN model, were in good agreement with those measured, and were comparable to those estimated from the GRNN model. Time response of establishing the optimum SVR model was in scale of minutes, which is suitable for on-line and real-time modeling NO_x emissions from coal-fired utility boilers.     

板坯传热二冷动态控制模型的有限体积法

阐述了时空有限体积法的基本思想，应用其方法，以钢水的凝固过程为多元系相变的实际为出发点，建立了连铸板坯凝固传热的二冷动态控制模型，求得表面温度的分布，表面温度、二冷区各段水量随拉速的变化关系。模型的模拟数据和现场实测数据吻合良好。算法对连铸过程中拉速的变化具有良好的适应能力，拉速引起的表面温度波动很小，能可靠地反映浇注条件频繁发生变化的实际连铸坯的凝固传热过程。     

金属基复合透明导电膜的研究

透明导电薄膜作为一种新型的光电材料显示出多种优异的光电性能和具有广泛的应用背景。综述了金属基复合透明导电膜的发展历程与研究现状，重点讨论了电介质，金属，电介质（D/M/D）和透明导电氧化物，金属，透明导电氧化物（TCO/M/TCO）这两种类型的多层复合膜，分析了其设计原理和存在问题，并指出了控制金属层的厚度和界面扩散是制备高性能光电薄膜的重要方面，最后介绍了金属基复合膜应用，并对其研究进行了展望。     

宝钢5m宽厚板热矫直机新工艺

厚板在生产的各个工序中都会产生各种浪形缺陷，为了满足市场和用户对钢板质量的要求，宝钢5m宽厚板轧机在加速冷却装置之后设置了一台热矫直机，主要用于轧后及加速冷却后钢板的矫直，以尽量减小钢板的不平直度。