Supporting early pruning in top-k query processing on massive data

This paper analyzes the execution behavior of “No Random Accesses” (NRA) and determines the depths to which each sorted file is scanned in growing phase and shrinking phase of NRA respectively. The analysis shows that NRA needs to maintain a large quantity of candidate tuples in growing phase on massive data. Based on the analysis, this paper proposes a novel top-k algorithm Top-K with Early Pruning (TKEP) which performs early pruning in growing phase. General rule and mathematical analysis for early pruning are presented in this paper. The theoretical analysis shows that early pruning can prune most of the candidate tuples. Although TKEP is an approximate method to obtain the top-k result, the probability for correctness is extremely high. Extensive experiments show that TKEP has a significant advantage over NRA.     

BSPNN: boosted subspace probabilistic neural network for email security

In the modern age of Internet connectivity, advanced information systems have accumulated huge volumes of data. Such fast growing, tremendous amount of data, collected and stored in large databases has far exceeded our human ability to comprehend without proper tools. There has been a great deal of research conducted to explore the potential applications of Machine Learning technologies in Security Informatics. This article studies the Network Security Detection problems in which predictive models are constructed to detect network security breaches such as spamming. Due to overwhelming volume of data, complexity and dynamics of computer networks and evolving cyber threats, current security systems suffer limited performance with low detection accuracy and high number of false alarms. To address such performance issues, a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), has been proposed which combines a Radial Basis Function Neural Network with an innovative diversity-based ensemble learning framework. Extensive empirical analyses suggested that BSPNN achieved high detection accuracy with relatively small computational complexity compared with other conventional detection methods.     

Relative importance,specific investment and ownership in interorganizational systems

Implementation and maintenance of interorganizational systems (IOS) require investments by all the participating firms. Compared with intraorganizational systems, however, there are additional uncertainties and risks. This is because the benefits of IOS investment depend not only on a firm’s own decisions, but also on those of its business partners. Without appropriate levels of investment by all the firms participating in an IOS, they cannot reap the full benefits. Drawing upon the literature in institutional economics, we examine IOS ownership as a means to induce value-maximizing noncontractible investments. We model the impact of two factors derived from the theory of incomplete contracts and transaction cost economics: relative importance of investments and specificity of investments. We apply the model to a vendor-managed inventory system (VMI) in a supply chain setting. We show that when the specificity of investments is high, this is a more critical determinant of optimal ownership structure than the relative importance of investments. As technologies used in IOS become increasingly redeployable and reusable, and less specific, the relative importance of investments becomes a dominant factor. We also show that the bargaining mechanism—or the agreed upon approach to splitting the incremental payoffs—that is used affects the relationship between these factors in determining the optimal ownership structure of an IOS.

Physiological and psychophysical responses in handling maximum acceptable weights under different footwear--floor friction conditions

A study on combined manual materials-handling tasks performed on floors under three friction levels was conducted. Eight male subjects participated in the study. The maximum acceptable weight of handling, including lifting, carrying for 3m, lowering, and walking 3m back at twice per minute was determined. The subject then performed the same tasks for 10 min. Heart rate, Vo2, energy efficiency, perceived sense of slip, and rating of perceived exertion for whole body strain were measured. The results showed that the effects of friction level on the maximum acceptable weights of handling, perceived sense of slip, Vo2, and energy efficiency were statistically significant (p相似文献   

The election problem in asynchronous distributed systems with bounded faulty processes

Determining the “weakest” failure detectors is a central topic in solving many agreement problems such as Consensus, Non-Blocking Atomic Commit and Election in asynchronous distributed systems. So far, this has been studied extensively for several such fundamental problems. It is stated that Perfect Failure Detector P is the weakest failure detector to solve the Election problem with any number of faulty processes. In this paper, we introduce Modal failure detector M and show that to solve Election, M is the weakest failure detector to solve election when the number of faulty processes is less than ⌈n/2⌉. We also show that it is strictly weaker than P.

WWW上路径模式发掘的研究

本文从互连网发展的趋势入手,对路径模式发掘进行了研究。先简要介绍数据库发掘的概况及网上数据发掘的特点,后结合关联法和组合概率法,并以算法和实例详细对之进行分析。     

Scalable parallel data mining for association rules

The authors propose two new parallel formulations of the Apriori algorithm (R. Agrawal and R. Srikant, 1994) that is used for computing association rules. These new formulations, IDD and HD, address the shortcomings of two previously proposed parallel formulations CD and DD. Unlike the CD algorithm, the IDD algorithm partitions the candidate set intelligently among processors to efficiently parallelize the step of building the hash tree. The IDD algorithm also eliminates the redundant work inherent in DD, and requires substantially smaller communication overhead than DD. But IDD suffers from the added cost due to communication of transactions among processors. HD is a hybrid algorithm that combines the advantages of CD and DD. Experimental results on a 128-processor Cray T3E show that HD scales just as well as the CD algorithm with respect to the number of transactions, and scales as well as IDD with respect to increasing candidate set size     

纳米SiO2材料的应用

本文根据纳米的奇异特性,简要综述纳米ＳｉＯ２在各个领域中的应用。     

移动台车栏板辅助浇筑系统的设计与应用

蒲石河工程下水库大坝顶部混凝土护栏位于坝顶临空边沿,钢筋绑扎和模板支立作业难度大,施工时存在安全隐患。为此,蒲石河工程设计了移动台车栏板辅助浇筑系统并成功应用。实践表明,作业台车设计可靠、安全稳定、操作简便、定位准确、移动方便,保障了施工人员人身安全,节约了成本,加快了工期,提高了模板支立质量,值得类似工程借鉴并推广使用。