• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.516-523
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• 2008

Recently, the Web has been constructed based on collective intel1igence and growing up quickly. User created contents have been made the mainstream in this environments. So it's required to make an efficient technique of searching for the contents. The current searching technique mainly is achieved by key words. Semantic Web based on similarity and relationship of a language and using user tags in web2.0 also have been researched with activity. Generally, the web of the participation architecture has a lot of user created contents, various forms and classification. Therefore, it is necessary to classify and to efficiently search for a lot of user created contents. In this paper, we propose a depth searching technique considering the relationship among the tags that descript user contents. It is expected that the proposed depth searching techniques can reduce the time taken to search for the unwanted contents and the increase the efficiency of the contents searching using a service of suggestion words in tags groups.

• Journal of Korea Water Resources Association
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• v.38 no.9 s.158
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• pp.761-770
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• 2005

This study applied the fuzzy logic control for the construction of the reservoir operation model which can consider uncertainty of the predicted inflow in determining reservoir release during flood period. The control rule is usually constructed based on the opinion of experts which is a general technique. To improve the drawback of general technique, this study constructed the Fuzzy-Tabu search model automatically established by the fuzzy rule using Tabu search which is a global optimization technique. As the results, the peak release is decreased and the flood control efficiency is improved. The total release is also decreased and this represents the benefit in water use. Consequently, it is confirmed that the effect of flood control can be increased through the constructed model. It also shows that the available water resources after the flood is more increased. So, the proposed Fuzzy-Tabu search model could be better than the actual reservoir operation methodology in the aspect of water use.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.91-97
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• 2002

This paper describes a heuristic search technique carrying out collision avoidance for Autonomous Underwater Vehicles(AUVs). Fuzzy relational products are used as the mathematical implement for the analysis and synthesis of relations between obstacles that are met in the navigation environment and available candidate nodes. In this paper, we propose a more effective evaluation function that reflects the heuristic information of domain experts on obstacle clearance, and an advanced heuristic search method performing collision avoidance for AUVs. The search technique adopts fuzzy relational products to conduct path-planning of intelligent navigation system. In order to verify the performance of proposed heuristic search, it is compared with $A^*$ search method through simulation in view of the CPU time, the optimization of path and the amount of memory usage.

• Speech Sciences
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• v.11 no.3
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• pp.165-172
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• 2004

In this paper, we propose the computational complexity reduction methods of delta pitch search that is used in G.723.1 vocoder. In order to decrease the computational complexity in delta pitch search the characteristic of proposed algorithms is as the following. First, scheme to reduce the computational complexity in delta pitch search uses NAMDF. Developed the second scheme is the skipping technique of lags in pitch searching by using the threshold value. By doing so, we can reduce the computational amount of pitch searching more than 64% with negligible quality degradation.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.157-167
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• 2005

This paper presents a new perturbation technique for developing efficient iterated local search procedures for the asymmetric traveling salesman problem(ATSP). This perturbation technique uses global information on ATSP instances to speed-up computation and to improve the quality of the tours found by heuristic method. The main idea is to escape from a local optima by introducing perturbations on the out-of-kilter arcs in the problem instance. For a local search heuristic, we use the Kwon which finds optimum or near-optimum solutions by applying the out-of-kilter algorithm to the ATSP. The performance of our algorithm has been tested and compared with known method perturbing on randomly chosen arcs. A number of experiments has been executed both on the well-known TSPLIB instances for which the optimal tour length is known, and on randomly generated Instances. for 27 TSPLIB instances, the presented algorithm has found optimal tours on all instances. And it has effectively found tours near AP lower bound on randomly generated instances.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.199-208
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• 2008

Tagging represents one of the Web 2.0 technology, and has an appropriate mechanism for the classification of dynamically changing Web informations. This technique is capable of searching the Web informations using the user specified tags, but still it has a limitation of providing only the limited informations to the tags. Therefore, in order to search the related informations easily, we need to extend this technique further to search not only the desired informations through the designated tags and also the related informations. In this paper, we first have designed and developed an algorithm that can get a desired tag cluster, which is capable of collecting the searched tags along with the related tags. We first performed a test to compare the difference between the user collected tag data through RSS and the reduced data. The second test focused on the accuracy of extracted related tags that depends on the similarity functions, such as the Pearson Correlation and Euclidean. Finally, we showed the final results visually using the graph algorithm.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.47-55
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• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.102-105
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• 2010

Traditional Pub/Sub(Publish/Subscribe) Systems search all subscriptions that match an incoming event by broker(i.e. it is not considering the accuracy of matching between an incoming event and subscriptions and only consider that an event either matches a subscription or not). However, subscriptions that match an event may have priority, therefore, we need priority Pub/Sub system. In this paper, we define what the accuracy means in order to prioritize among subscriptions and propose the Priority Retrieval Technique based on accuracy that able to search subscriptions. The Priority Retrieval Technique is based on IS-Lists. We can search the results ordered by accuracy.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.107-116
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• 2014

When an incoming Global Positioning System (GPS) signal is acquired, pull-in search performs a finer search of the Doppler frequency of the incoming signal so that phase lock loop can be quickly stabilized and the receiver can produce an accurate pseudo-range measurement. However, increasing the accuracy of the Doppler frequency estimation often involves a higher computational cost for weaker GPS signals, which delays the position fix. In this paper, we show that the Doppler frequency detectable by a long coherent auto-correlation can be accurately estimated using a complex-weighted sum of consecutive short coherent auto-correlation outputs with a different Doppler frequency hypothesis, and by exploiting this we propose a noise resistant, low-cost and highly accurate Doppler frequency and phase estimation technique based on a reverse directional application of the finite rate of innovation (FRI) technique. We provide a performance and computational complexity analysis to show the feasibility of the proposed technique and compare the performance to conventional techniques using numerous Monte Carlo simulations.