15989563
On the usefulness of infeasible solutions in evolutionary search: A theoretical study
Evolutionary algorithms (EAs) have been widely used in optimization, where infeasible solutions are often encountered. Some EAs regard infeasible solutions as useless individuals while some utilize infeasible solutions based on heuristic ideas. It is not clear yet that whether infeasible solutions are helpful or not in the evolutionary search. This paper theoretically analyzes that under what conditions in- feasible solutions are beneficial. A sufficient condition and a necessary condition are derived and discussed. Then, the paper theoretically shows that the use of infeasible solutions could change the hardness of the task. For example, an EA-hard problem can be transformed to EA-easy by exploiting infeasible solutions. While, the conditions derived in the paper can be used to judge whether to use infeasible solutions or not.
15348979
Cocktail Ensemble for Regression
This paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. Based on an error-ambiguity decomposition, we formally analyze the optimal linear combination of two base ensembles, which is then extended to multiple individual ensembles via pairwise combinations. The Cocktail ensemble approach is proposed based on this analysis. Experiments over a broad range of data sets show that the proposed approach outperforms the individual ensembles, two other methods of ensemble combination, and two state-of-the-art regression approaches.
15248817
TEFE: A Time-Efficient Approach to Feature Extraction
With the rapid evolution of Internet applications, people all over the world are sharing pictures, videos and audios online, and thus, content-based analysis is often demanded. Test efficiency is crucial to the success of online information processing. One obstacle to high-speed testing is the time cost of feature extraction for test objects, particularly for objects with complex representation such as images, videos and audios. In this paper, we study the problem of reducing test time cost by extracting cheap but sufficient features. We propose the TEFE (time-efficient feature extraction) approach, which balances between the test accuracy and test time cost by extracting a proper subset of features for each test object. In the implementation, TEFE trains a sequence of support vector machines and classifies each test object cascadingly. Empirical study shows that TEFE is time efficient while holding a classification accuracy close to that of using all features. It also shows that the test time is linearly adjustable in TEFE.
14236359
Semi-naive Exploitation of One-Dependence Estimators
It is well known that the key of Bayesian classifier learning is to balance the two important issues, that is, the exploration of attribute dependencies in high orders for ensuring a sufficient flexibility in approximating the ground-truth dependencies, and the exploration of low orders for ensuring a stable probability estimate from limited training samples. By allowing one-order attribute dependencies, one-dependence estimators (ODEs) have been shown to be able to approximate the ground-truth attribute dependencies whilst keeping the effectiveness of probability estimation, and therefore leading to excellent performance. In previous studies, however, ODEs were exploited in simple ways, such as by averaging, for classification. In this paper, we propose a semi-naive exploitation of ODEs that fits a function of ODEs to pursue higher-order attribute dependencies. Extensive experiments show that the proposed SNODE approach can achieve better performance than many state-of-the-art Bayesian classifiers.
33025668
The Permanent Rank of a Matrix
Define the perrank of a matrixAto be the size of the largest square submatrix ofAwith nonzero permanent. Motivated in part by the Alon?Jaeger?Tarsi Conjecture [3], we prove several results on perranks..
5420099
A new approach to estimating the expected first hitting time of evolutionary algorithms
The expected first hitting time is an important issue in theoretical analyses of evolutionary algorithms since it implies the average computational time complexity. In this paper, by exploiting the relationship between the convergence rate and the expected first hitting time, a new approach to estimating the expected first hitting time is proposed. This approach is then applied to four evolutionary algorithms which involve operators of mutation, mutation with population, mutation with recombination, and time-variant mutation, respectively. The results show that the proposed approach is helpful for analyzing a broad range of evolutionary algorithms.
33694964
Workflow scheduling in grids: an ant colony optimization approach
Grid applications in virtue of open service grid architecture (OGSA) are promising next-generation computation techniques. One of the most important and challenging problems about grid application is the workflow scheduling problem to achieve the users' QoS (quality of service) requirements as well as to minimize the cost. This paper proposes an ant colony optimization (ACO) algorithm to tackle this problem. Several new features are introduced to the algorithm. First, we define two kinds of pheromone and three kinds of heuristic information to guide the search direction of ants for this bi-criteria problem. Each ant uses either one from these heuristic types and pheromone types in each iteration based on the probabilities controlled by two parameters. These two parameters are adaptively adjusted in the process of the algorithm. Second, we use the information of partial solutions to modify the bias of ants so that inferior choices will be ignored. Moreover, the experimental results in 3 workflow applications under different deadline constraints show that the performance of our algorithm is very promising, for it outperforms the Deadline-MDP algorithm in most cases.
14448098
Research on Dynamic Task Assignment in Grid Workflow System
Task assignment in grid workflow system should be designed to adapt well with the grid which allow people from different organizations to work together in the same workflow process. To ensure grid workflow systems could assign the task to the most suitable person, a novel solution is proposed firstly. Then two description languages GHRSL and HRRL are defined. GHRSL (grid human resource specification language) describes people as grid resources. HRRL (human resources requirement language) describes human resources requirement of workflow tasks. Finally, the evaluation method and the algorithm of dynamic task assignment are also proposed. Based on these, the grid workflow system could assign tasks dynamically to the correct person(s)
9006284
A workflow model based on fuzzy-timing Petri nets
Time information management in workflow has been recognized as one of the most significant tasks in workflow management. The uncertainties in time and time-related constraints in workflow models should be taken into consideration. Based on introducing time constraints on elements in fuzzy-timing Petri nets, this paper propose a new workflow model named fuzzy temporal workflow nets (FTWF-nets). The calculation of temporal elements in FTWF-nets is given. Then time modeling and time possibility analysis of temporal phenomena in FTWF-nets are investigated. Finally an example is given to illustrate how to use these methods. Research results show that FTWF-nets can be used to model time information in those workflows, which have time uncertainty and have time constraints on resources and activities, and analyze the time possibility on some constraints.
17624107
3D Simulation of Real-Time Infrared Scene Based on DSP
Nowadays 3D simulation of Infrared scene is quite popular. Most of these simulations were realized on PC and under the help of many free or commercial 3D APIs or libraries. We carried out our simulation by a rendering engine written by ourselves, and implement this engine on a DSP board, which gave us much convenience to directly inject the digital result into the IR tracking and alarming systems which use the result as their data source. We also used some techniques such as look-up table, culling, etc, to accelerate the IR radiance calculation and rendering speed. The result shows that itpsilas a valuable attempt, which can make the IR scene generator smaller and more portable, and gain advantage in the hardware acceleration as well as convenience in future system connection.
1810758
Display-only file server: a solution against information theft due to insider attack
Insider attack is one of the most serious cybersecurity threats to corporate America. Among all insider threats, information theft is considered the most damaging in terms of potential financial loss. Moreover, it is also especially difficult to detect and prevent, because in many cases the attacker has the proper authority to access the stolen information. According to the 2003 CSI/FBI Computer Crime and Security Survey, theft of proprietary information was the single largest category of losses in the 2003 survey totaling $70.1 million or 35% of the total financial loss reported in that survey. In this paper, we describe the design, implementation and evaluation of an industrial-strength solution called <i>Display-Only File Server</i> (DOFS), which can transparently and effectively stop information theft by insiders in most cases, even if the insiders have proper authorities to read/write the protected information. The DOFS architecture ensures that bits of a protected file never leave a DOFS server after the file is checked in and users can still interact with the protected files in the same way as if it is stored locally. Essentially, DOFS decouples "display access" from other types of accesses to a protected file by providing users only the "display image" rather than the bits of the files, and applies the thin-client computing model on existing client-server applications.