5795561
An in-depth analysis of information markets with aggregate uncertainty
The novel idea of setting up Internet-based virtual markets, information markets, to aggregate dispersed information and predict outcomes of uncertain future events has empirically found its way into many domains. But the theoretical examination of information markets has lagged relative to their implementation and use. This paper proposes a simple theoretical model of information markets to understand their information dynamics. We investigate and provide initial answers to a series of research questions that are important to understanding how information markets work, which are: (1) Does an information market converge to a consensus equilibrium? (2) If yes, how fast is the convergence process? (3) What is the best possible equilibrium of an information market? and (4) Is an information market guaranteed to converge to the best possible equilibrium?
41639900
An Evolutionary Fuzzy Multi-objective Approach to Cell Formation
Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applications because it can only be used to solve small-size problems. In this paper, we propose a heuristic genetic algorithm (HGA) as a viable solution for solving large-scale fuzzy multi-objective CF problems. Heuristic crossover and mutation operators are developed to improve computational efficiency. Our results show that the HGA outperforms the FMP and goal programming (GP) models in terms of clustering results, computational time, and user friendliness.
5646511
KTR: an efficient key management scheme for air access control
To provide secure access to data in wireless broadcast services, symmetric key-based encryption is used to ensure that only users who own the valid keys can decrypt the data. In this paper, we propose an efficient key management scheme (namely KTR) to handle key distribution with regarding to complex subscription options and user activities. KTR has the following advantages. First, it supports all subscription activities in wireless broadcast services. Second, in KTR, a user only needs to hold one set of keys for all subscribed programs, instead of separate sets of keys for each program. Third, KTR identifies the minimum set of keys that must be changed to ensure broadcast security and minimize the rekey cost. Our simulations show that KTR can save about 45% of communication overhead in the broadcast channel and about 50% of decryption cost for each user, compared with conventional approaches based on logical key hierarchy.
27561759
Splice site prediction using support vector machines with a Bayes kernel
One of the most important tasks in correctly annotating genes in higher organisms is to accurately locate the DNA splice sites. Although relatively high accuracy has been achieved by existing methods, most of these prediction methods are computationally extensive. Due to the enormous amount of DNA sequences to be processed, the computational speed is an important issue to consider. In this paper, we present a new machine learning method for predicting DNA splice sites, which first applies a Bayes feature mapping (kernel) to project the data into a new feature space and then uses a linear Support Vector Machine (SVM) as a classifier to recognize the true splice sites. The computation time is linear to the number of sequences tested, while the performance is notably improved compared with the Naive Bayes classifier in terms of classification accuracy, precision, and recall. Our classification results are also comparable to the solution quality obtained by the SVMs with polynomial kernels, while the speed of our proposed method is significantly faster. This is a notable improvement in computational modeling considering the huge amount of DNA sequences to be processed.
17686405
A time-series biclustering algorithm for revealing co-regulated genes
Although existing bicluster algorithms claimed to be able to discover co-regulated genes under a subset of given experiment conditions, they ignore the inherent sequential relationship between crucial time points and thus are not applicable to analyze time-series gene expression data. A simple and effective deletion-based algorithm, using the mean squared residue score as a measure, was developed to bicluster time-series gene expression data. While enforcing a threshold value for the score, the algorithm alternately eliminates genes and time points according to their correlation to the bicluster. To ensure the time locality, only the starting and ending points in the time interval are eligible for deletion. As a result, the number of genes and the length of time interval are simultaneously maximized. Our experimental results shown that the proposed method is capable of identifying co-regulated genes characterized by partial time-course data that previous methods failed to discover.
7900750
A Web-service oriented framework for building SCORM compatible learning management systems
Managing the large amount of learning content involved in the development of an expandable learning management system (LMS) is a critical task for most educational organizations. In designing such a system, consideration must be given not only to the requirement of instructors and students, but also to the adaptive qualities of the system itself, because of the rapidly changing software environment. Unlike most enterprises, educational organization can't afford high system maintenance. Development of a flexible, expandable and reliable learning management system is, therefore, imperative. This paper proposes a Web service oriented framework in building a sharable content object reference model (SCORM) compatible LMS. We integrated the SCORM concept with distributed computing technologies to build the components of the LMS and demonstrate how these services can be configured to create a complete system. This framework increases reusability and reduces the maintenance requirements of the LMS. It provides a way for small educational organizations, with limited resources, to build a complete SCORM compatible LMS. In such an ideal situation, the content provider not only provides the content, but also the service for the consumers of that content.
41181041
A matrix synthesis approach to thermal placement
In this paper, we consider the thermal placement problem for gate arrays. We introduce a new combinatorial optimization problem, matrix synthesis problem (MSP), to model the thermal placement problem. Given a list of mn nonnegative real numbers and an integer t, MSP constructs a m/spl times/n matrix out of the given numbers such that the maximum sum among all t/spl times/t submatrices is minimized. We show that MSP is NP-complete and present several provably good approximation algorithms for the problem. We also demonstrate that our thermal placement strategy is flexible enough to allow simultaneous consideration of other objectives such as wiring.
12805154
Efficient rectilinear Steiner tree construction with rectilinear blockages
Given n points on a plane, a rectilinear Steiner minimal tree (RSMT) connects these points through some extra points called Steiner points to achieve a tree with minimal total wire length. Taking blockages into account dramatically increases the problem complexity. It is extremely unlikely that an efficient optimal algorithm exists for rectilinear Steiner minimal tree construction with rectilinear blockages (RSMTRB). Although there exist some heuristic algorithms for this problem, they have either poor quality or expensive running time. In this paper, we propose an efficient and effective approach to solve RSMTRB. The connection graph we used in this approach is called spanning graph which only contains O(n) edges and vertices. An O(n log n) time algorithm is proposed to construct spanning graph for RSMTRB. The experimental results show that this approach can achieve a solution with significantly reduced wire length. The total run time increased is negligible in the whole design flow.
79941
Floorplan area minimization using Lagrangian relaxation
ABSTRACT Floorplan area minimization is an important problem because many modules have shape exibilities during the oorplanning stage. Area minimization in general non-slicing oorplan is a complicated problem. Many previous works have attempted to tackle this problem [9; 6; 5; 1] using heuristics or numerical methods but none of them can solve it optimally and e ciently. In this paper, we show how this problem can be solved optimally by a geometric programming using Lagrangian relaxation. The resulting Lagrangian relaxation subproblem is so simple that the size of each module can be found in constant time. We implemented our idea in a simulated annealing framework based on the sequence pair representation. The area minimization procedure is invoked in every iteration of the annealing process but the total execution time is still very much faster than that of the most updated previous work [4]. For a benchmark data with 49 modules, we take 19.5 hours using a 270 MHz Sun Ultra 5 while the convex programming approach in [4] takes seven days using a 250 MHz DEC Alpha. This area minimization method will be applicable to any other oorplanning algorithm which uses constraint graphs to nd module positions in the nal packing.
2004729
Dependable Handling of Uncertainty
Uncertainty quantification is an important approach to modeling in the presence of limited information about uncertain quantities. As a result recent years have witnessed a burgeoning body of work in this field. The present paper gives some background, highlights some recent work, and presents some problems and challenges.