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.
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.
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.
776801
Optimizing SOC Test Resources using Dual Sequences
In this paper, we propose a new data structure called dual sequences to represent SOC test schedules. Dual sequences are used together with a simulated annealing based procedure to optimize the SOC test application time and tester resources. The problems we consider are generation of optimal test schedules for SOCs and minimizing tester memory and test channels. Results of experiments conducted on ITC’02 benchmark SOCs show the effectiveness of the proposed method.
41515379
The I+ Test
The I test is an efficient and precise data dependence method to ascertain whether integer solutions exist for one-dimensional arrays with constant bounds. For one-dimensional arrays with variable limits, the I test assumes that there may exist integer solutions. In this paper, we propose the I+ test|an extended version of the I test. The I+ test can be applied towards determining whether integer solutions exist for onedimensional arrays with either variable or constant limits, improving the applicable range of the I test. Experiments with benchmark cited from EISPACK, LINPACK, Parallel loops, Livermore loops and Vector loops showed that among 1189 pairs of one-dimensional arrays tested, 183 had their data dependence analysis amended by the I+ test. That is, the I+ test increases the success rate of the I test by approximately 15:4 percent. Comparing with the Power test and the Omega test, the I+ test has higher accuracy than the Power test and shares the same accuracy with the Omega test when determining integer solutions for these 1189 pairs of one-dimensional arrays, but has much better efficiency over them.
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.
18525423
An efficient and optimal algorithm for simultaneous buffer and wire sizing
In this paper, we consider the problem of interconnect delay minimization by simultaneous buffer and wire sizing under the Elmore delay model. We first present a polynomial time algorithm SBWS to minimize the delay of an interconnect wire. Previously, no polynomial time algorithm for the problem has been reported in the literature. SBWS is an iterative algorithm with guaranteed convergence to the optimal solution. It runs in quadratic time and uses constant memory for computation. Experimental results show that SBWS is extremely efficient in practice. For example, for an interconnect of 10000 segments and buffers, the CPU time is only 0.255 s. We then extend our result to handle interconnect trees. We present an algorithm SBWS-T which always gives the optimal solution. Experimental results show that SBWS-T is faster than the greedy wire sizing algorithm in practice.