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.
11987571
Predicting Future Customers via Ensembling Gradually Expanded Trees
Our LAMDAer team has won the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2006 Data Mining Competition (open category) grand champion. This report presents our solution to the PAKDD 2006 Data Mining Competition. Following a brief description of the task, we discuss the difficulties of the task and explain the motivation of our solution. Then, we propose the Gradually Expanded Tree Ensemble (GetEnsemble) method, which handles the difficulties via ensembling expanded trees. We evaluated the proposed method and several other methods using AUC, and found the proposed method beats others in this task. Besides, we show how to obtain cues on which kind of second generation (2G) customers are likely to become third generation (3G) users with the proposed method.
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.
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.
16271421
Weak Evolvability Equals Strong Evolvability
A process for the purification of caffeine which comprises carrying out the following steps in any order; (a) recrystallization of caffeine from an aqueous alkaline solution of caffeine containing a reducing agent and (b) extraction of the caffeine from an aqueous alkaline solution of caffeine with a substantially water-immiscible solvent which is liquid under the conditions of the process.
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.
2683390
A RDT-based interconnection network for scalable network-on-chip designs
The interconnection network plays an important role in the performance and energy consumption of a network-on-chip (NoC) system. In this paper, we propose a RDT(2,2,1)//spl alpha/-based interconnection network for NoC designs. RDT(2,2,1)//spl alpha/ is constructed by recursively overlaying 2D diagonal meshes (torus). The number of layers needed for routing the links in RDT(2,2,1)//spl alpha/ is shown to be bounded at 6, which is feasible to be implemented with current and future VLSI technologies. With the innovative diagonal structure and its simple rank assignment, RDT(2,2,1)//spl alpha/ possesses the following features: recursive structure, smaller diameter and average distance, embedded mesh/torus topology, a constant node degree of 8, and robust routing schemes. These features make RDT(2,2,1)//spl alpha/ a promising solution for the interconnection network of NoC designs satisfying the requirements for scalability, energy-efficiency, customizability, and fault-tolerance.
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.
15504838
Utilization-based heuristics for statically mapping real-time applications onto the HiPer-D heterogeneous computing system
Real-time applications continue to increase in importance as they are employed in various critical areas, such as command and control systems. These applications have traditionally required custom-made systems to execute them. Recently, with the widespread use of increasingly powerful commercial off-the-shelf (COTS) products, some real-time system designers have started a shift from custom development to COTS-based systems to achieve lower costs and more flexible systems. This research investigates the problem of allocating real-time applications to a set of COTS heterogeneous machines connected together by a COTS high-speed network. The heuristics were implemented on the High Performance Distributed Computing Program's (HiPer-D) Naval Surface Warfare Center (NSWC) testbed. At the specification of NSWC, the goal of this study is to design static resource allocation heuristics that balance the utilization of the computation and network resources in the HiPer-D system based on the system information provided. The broader goal is to maximize the time before dynamic reallocation is required for managing an increased workload at runtime.
52872567
A Clustering Approach to Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-Hop Relay Networks
In this paper, a clustering approach to solve a network planning problem for 802.16J relay networks is considered. Our clustering approach consists of three basic steps: (1) divide the nodes into k distinct clusters, (2) solve the planning problem separately for each cluster, and (3) perform a final optimization to reduce issues arising at cluster boundaries. Simulation results show that our approach is more efficient than existing approaches: solutions of equivalent quality can be found in 40% of the time. Thus our technique can be used to solve larger problems with similar hardware, or similar size problems in less time.