16907116
Enhancing the Fuzzy Set Model with Positively Compensatory Operators
The conventional fuzzy set model uses the MIN and MAX operators for the evaluation of boolean operators AND and OR, respectively. It has been criticized to generate incorrect ranked output in many cases. This is because the MIN and MAX operators do not well correspond with human behavior for document ranking. There are a variety of fuzzy operators to replace the MIN and MAX operators. In this paper we first investigate the behavioral aspects of the fuzzy operators and address important issues to affect retrieval effectiveness. We then present the enhanced fuzzy set model based on positively compensatory operators, which are suitable for achieving high retrieval effectiveness. It is also shown through experiments that the enhanced fuzzy set model provides similar retrieval effectiveness and higher retrieval efficiency in comparison with the extended boolean model.
8831551
A per-object based hybrid concurrency control
Existing concurrency control algorithms do not conform well to various environments in the performance perspective. Each algorithm has some assumption on the conflict characteristic of its execution environment, and its performance degrades when the assumption fails. A per-object hybrid scheme integrating a two phase locking algorithm with a parallel validation technique is presented to solve this problem. Read and write accesses on each database object are controlled by one algorithm at a time. This controlling algorithm can alter while transactions are running, in order to enhance the overall system performance. In the simulation study, the proposed scheme with the proposed algorithm alteration strategy is shown to conform well to various execution environments, better than both the two phase locking algorithm and the parallel validation technique.
38239153
Qualitative Behavior Modeling of Information Processing Components
This paper presents qualitative behavior modeling of Information Processing Components(IPCs), which are domain-specific software components for modeling reusable functions in database management systems(DBMSs). After introducing a detailed formal syntax of IPCs, we propose their modular, qualitative behavior generation mechanism. The proposed mechanism is based on qualitative modeling and simulation, thus produces a sequence of temporal state transitions of modeled IPCs. The proposed modeling mechanism aims to facilitate the scientific measurement of
14456420
A replica control method for improving availability for read-only transactions
Data replication is often considered in distributed database systems to enhance availability and performance. The benefit of data replication, however can only be realized at the cost of maintaining the consistency of data. In particular, network partition failures make it more difficult to achieve high data availability while ensuring strong correctness criteria such as l-copy serializability. We propose a replica control method to improve the availability of data in the presence of network partition failures. Our method extends the traditional primary copy method by using the relaxed correctness criterion called insular consistency for large-scale distributed systems, where partition failures frequently occur. We focus on increasing the availability of data for read-only transactions. We introduce a version vector as a tool for guaranteeing insular consistency and present a mechanism that allows read-only transactions to be executed at any partition as long as the insular consistency is satisfied. An asynchronous update propagation mechanism is also employed to improve the performance of update operations. We also show that the proposed method is correct and give some performance considerations.
13362734
FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting
Abstract The aim of this paper is to present a novel subspace clustering method named FINDIT. Clustering is the process of finding interesting patterns residing in the dataset by grouping similar data objects from dissimilar ones based on their dimensional values. Subspace clustering is a new area of clustering which achieves the clustering goal in high dimension by allowing clusters to be formed with their own correlated dimensions. In subspace clustering, selecting correct dimensions is very important because the distance between points is easily changed according to the selected dimensions. However, to select dimensions correctly is difficult, because data grouping and dimension selecting should be performed simultaneously. FINDIT determines the correlated dimensions for each cluster based on two key ideas: dimension-oriented distance measure which fully utilizes dimensional difference information, and dimension voting policy which determines important dimensions in a probabilistic way based on V nearest neighbors' information. Through various experiments on synthetic data, FINDIT is shown to be very successful in the high dimensional clustering problem. FINDIT satisfies most requirements for good clustering methods such as accuracy of results, robustness to the noise and the cluster density, and scalability to the dataset size and the dimensionality. Moreover, it is gracefully scalable to full dimension without any modification to algorithm.
591216
The HS File: A New Dynamic Signature File Method for Efficient Information Retrieval
Many works on the signature file methods have been made in the past, but they are mainly for static environments. However, many recent applications in practice require a dynamic information storage structure that effectively supports insertions, deletions and updates. Though there are a few signature file techiniques for dynamic environments, they suffer from serious performance degradation when query signature weights are light. In this paper, we propose a new dynamic signature file organization, called the hierarchical signature(HS) file, that solves the problem of light query signature weights. We perform simulation experiments by using wide range of parameter values. We show through performance comparison based on experiments that the HS file improves performance significantly in both the retrieval time and the storage over-head over the other dynamic signature file methods proposed earlier.
6621245
Application of Machine Shop Data Model in Manufacturing Simulation
Simulation technology holds tremendous promise for the manufacturing industry. A machine shop data model has been developed at the National Institute of Standards and Technology (NIST) to represent neutral machine shop data for supporting machine shop manufacturing simulation [1]. This paper discusses the data model and its application in manufacturing simulation. The paper also proposes an application framework that integrates the simulation model, machine shop database, and machine shop XML (Extensible Markup Language) data document. A prototype system is developed to present the application of machine shop data model using the proposed framework.
12566781
Web-Based Simulation with Server Application Approach under Distributed Environment
14475818
Data exchange for machine shop simulation
Manufacturing simulation systems normally provide interfaces for data import and export using proprietary formats. Dependent data interfaces limit simulation applications in the manufacturing industry. This paper describes a mechanism for transferring data between a traditional database and XML files, which represent a machine shop data model developed at the National Institute of Standards and Technology (NIST). The data model is described by XML (eXtensible Markup Language) and UML (Unified Modeling Language). The data transfer mechanism is based on document object model (DOM), XML path language (XPath), and open database connectivity (ODBC) database engines. A prototype implementation is also described in this paper
30123293
Key Management in Wireless Sensor Networks
Wireless sensor networks hold the promise of facilitating large-scale, real-time data processing in complex environments. As sensor networks edge closer towards widespread deployment, security issues become a central concern. Key management in wireless sensor networks is a challenging problem. Computationally complex asymmetric crypto techniques are unsuitable for use in resource-constrained sensor nodes and use of symmetric cryptography makes the entire network vulnerable in the event of node compromise. This paper presents a key management scheme that satisfies both operational and security requirements of distributed wireless sensor networks. The proposed scheme accommodates other techniques like data aggregation for energy efficiency and watchdog mechanism for intrusion monitoring. Also, the proposed scheme is generic enough so that it can be applied to variety of sensor network protocols.
45657020
Partial convexification cuts for 0-1 mixed-integer programs
Abstract In this research, we propose a new cut generation scheme based on constructing a partial convex hull representation for a given 0–1 mixed-integer programming problem by using the reformulation–linearization technique (RLT). We derive a separation problem that projects the extended space of the RLT formulation into the original space, in order to generate a cut that deletes a current fractional solution. Naturally, the success of such a partial convexification based cutting plane scheme depends on the process used to tradeoff the strength of the cut derived and the effort expended. Accordingly, we investigate several variable selection rules for performing this convexification, along with restricted versions of the accompanying separation problems, so as to be able to derive strong cuts within a reasonable effort. We also develop a strengthening procedure that enhances the generated cut by considering the binariness of the remaining unselected 0–1 variables. Finally, we present some promising computational results that provide insights into implementing the proposed cutting plane methodology.