• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.1-8
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• 2008

With growing interest in location-based service (LBS), there is increasing necessity for nearest neighbor (NN) search through query while the user is moving. NN search in such a dynamic environment has been performed through the repeated applicaton of the NN method to the search segment, but this increases search cost because of unnecessary redundant calculation. We propose slabbed continuous nearest neighbor (Slabbed_CNN) search, which is a new method that searches CNN in the search segment while moving, Slabbed_CNN reduces calculation costs and provides faster services than existing CNN by reducing the search area and calculation cost of the existing CNN method through reducing the search segment using slabs.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.6
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.2 s.140
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.9-12
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• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1011-1014
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• 1999

In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.223-232
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• 2001

This paper describes Genetic Algorithm-Based Relay Search Method, RS-GA, which is developed in this study to search the multiple design variables in the design space. The RS-GA based on Simple-GA consists of some functions to search many variables from some wide variable space. It repeats a Simple-GA, that is the convergence process of the Simple-GA, which makes many time reiteration itself. From the results of the numerical studies, it was actually found that RS-GA can search all peak-variable from the 2D functions including 5 peaks. Finally, RS-GA applied for design-strengthening problems in composite plate girder bridges using the external prestressing technique is also verified.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.290-294
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• 2021

Experts have designed popular and successful model architectures, which, however, were not the optimal option for different scenarios. Despite the remarkable performances achieved by deep neural networks, manually designed networks for classification tasks are the backbone of object detection. One major challenge is the ImageNet pre-training of the search space representation; moreover, the searched network incurs huge computational cost. Therefore, to overcome the obstacle of the pre-training process, we introduce a network adaptation technique using a pre-trained backbone model tested on ImageNet. The adaptation method can efficiently adapt the manually designed network on ImageNet to the new object-detection task. Neural architecture search (NAS) is adopted to adapt the architecture of the network. The adaptation is conducted on the MobileNetV2 network. The proposed NAS is tested using SSDLite detector. The results demonstrate increased performance compared to existing network architecture in terms of search cost, total number of adder arithmetics (Madds), and mean Average Precision(mAP). The total computational cost of the proposed NAS is much less than that of the State Of The Art (SOTA) NAS method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.119-122
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• 2003

This paper presents an efficient huffman decoding method based on the multiple branch technique. In the proposed search method, the internal node which does not contain a leaf node are removed for decrease the searching time and the memory consumption. The proposed search method gives 44％ of improved in searching time and 34％ of decreased in memory requirement compared to the binary search method.

• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.269-272
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• 2010

In this paper, we propose the computation reduction methods of delta pitch search that is used in G.723.1 vocoder. In order to decrease the computational amount in delta pitch search the characteristic of proposed algorithms is as the following. First, scheme to reduce the computation amount 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.