• International Journal of Contents
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• 제6권1호
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• pp.47-52
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• 2010

Skyline queries are an important new search capability for multi-dimensional databases. Most of the previous works have focused on processing skyline queries over static data set. However, most of the real applications deal with the dynamic data set. Since dynamic data set constantly changes as time passes, the continuous skyline computation over dynamic data set becomes ever more complicated. In this paper, we propose a multiple layer grids method for continuous skyline computation (MLGCS) that maintains multiple layer grids to manage the dynamic data set. The proposed method divides the work space into multiple layer grids and creates the skyline influence region in the grid of each layer. In the continuous environment, the continuous skyline queries are only handled when the updating data points are in the skyline influence region of each layer grid. Experiments based on various data distributions show that our proposed method outperforms the existing methods.

• Phonetics and Speech Sciences
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• 제7권2호
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• pp.157-162
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• 2015

This study reports on the effective way of displaying dynamic formant information on F1-F2 space. Conventional ways of F1-F2 space (different name of vowel triangle or vowel rectangle) have been used for investigating vowel characteristics of a speaker or a language based on statistics of the F1 and F2 values, which were computed by spectral envelope search method. Those methods were dealing mainly with the static information of the formants, not the changes of the formant values (i.e. dynamic information). So a better way of investigating dynamic informations from the formant values of speech signal is suggested so that more convenient and detailed investigation of the dynamic changes can be achieved on F1-F2 space. Suggested method used visualization of static and dynamic information in overlapped way to be able to observe the change of the formant information easily. Finally some examples of the implemented display on some cases of the continuous vowels are shown to prove the usefulness of suggested method.

• The Bulletin of The Korean Astronomical Society
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• 제41권2호
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• pp.49.3-50
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• 2016

Deep Ecliptic Patrol of the Southern Sky (DEEP-South) observations have been conducted officially during the off-season for exoplanet search since October 2015. Most of the allocated time for DEEP-South is devoted to targeted photometry, Opposition Census (OC), of Near Earth Asteroids (NEAs) to increase the number of such objects with known physical properties. It is efficiently achieved by multiband, time series photometry. This Opposition Census (OC) mode target objects near their opposition, with km-sized PHAs in the early stage and goes down to sub-km objects. Continuous monitoring of the sky with KMTNet is optimized for spin characterization of various kinds of asteroids, including binaries, satellites, slow/fast- and non-principal axis-rotators, and hence is expected to facilitate the debiasing of previously reported lightcurve observations. We present the preliminary lightcurves of NEAs from year one of the DEEP-South with our long term plan.

• ETRI Journal
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• 제40권4호
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• pp.471-482
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• 2018

This paper proposes the necessity of a walking period in footstep planning and details situations in which it should be considered. An optimization-based fast footstep planner that takes the walking period into consideration is also presented. This footstep planner comprises three stages. A binary search is first used to determine the walking period. The front stride, side stride, and walking direction are then determined using the modified rapidly-exploring random tree algorithm. Finally, particle swarm optimization (PSO) is performed to ensure feasibility without departing significantly from the results determined in the two stages. The parameters determined in the previous two stages are optimized together through the PSO. Fast footstep planning is essential for coping with dynamic obstacle environments; however, optimization techniques may require a large computation time. The two stages play an important role in limiting the search space in the PSO. This framework enables fast footstep planning without compromising on the benefits of a continuous optimization approach.

• Journal of the Korea Society for Simulation
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• 제28권1호
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

• Korean Institute of Interior Design Journal
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• 제26권2호
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• pp.3-12
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• 2017

This study has analyzed the features of attention to spacial composition seen in "Seeing ${\leftrightarrow}$ Seen" Correlation of continuous move in the space. The eye-tracking was employed for collecting the data of attention features to the space so that the correlation between visual perception and space could be estimated through the attention features to the difference between spacial composition and display. First, it was confirmed that the attention features varied according to the structure of shops and the exposure degree of selling space, which revealed that, while causing the customers' less attention to both sides of shops, the vanishing-point structure characteristically made their eyes focused on the central part. Second, their initial observation activities were found to be active at the height of their eyes. Third, 10 images were selected as objects for continuous experiment. There was a concern that the central part of each image would be paid intense attention to during the initial observation, but only two of those were found to be so. Fourth, there had been a study result of eye-tracking experiment that the attention had been concentrated on the central part of the image first seen. This study, however, revealed that such phenomenon is limited to the first image. Accordingly, it is necessary to draw up such method for ensuring reliability in order to use the data acquired from any eye-tracking experiment as exclusion of the initial attention time to the first image or of unemployment of the initial image-experiment to analysis.

• Journal of Ocean Engineering and Technology
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• 제17권6호
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• pp.53-57
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• 2003

Optimum design of most structural system requires that design variables are regarded as discrete quantities. This paper presents the use of Genetic Algorithm for determining the optimum design for truss with discrete variables. Genetic Algorithm are know as heuristic search algorithms, and are effective global search methods for discrete optimization. In this paper, Elitism and the method of conferring penalty parameters in the design variables, in order to achieve improved fitness in the reproduction process, is used in the Genetic Algorithm. A 10-Bar plane truss and a 25-Bar space truss are used for discrete optimization. These structures are designed for stress and displacement constraints, but buckling is not considered. In particular, we obtain continuous solution using Genetic Algorithms for a 10-bar truss, compared with other results. The effectiveness of Genetic Algorithms for global optimization is demonstrated through two truss examples.

• Wind and Structures
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• 제39권3호
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• pp.175-190
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• 2024

Aerodynamic shape optimization is very useful for enhancing the performance of wind-sensitive structures. However, shape parameterization, as the first step in the pipeline of aerodynamic shape optimization, still heavily depends on empirical judgment. If not done properly, the resulting small design space may fail to cover many promising shapes, and hence hinder realizing the full potential of aerodynamic shape optimization. To this end, developing a novel shape parameterization scheme that can reflect real-world complexities while being simple enough for the subsequent optimization process is important. This study proposes a machine learning-based scheme that can automatically learn a low-dimensional latent representation of complex aerodynamic shapes for bluff-body wind-sensitive structures. The resulting latent representation (as design variables for aerodynamic shape optimization) is composed of both discrete and continuous variables, which are embedded in a hierarchy structure. In addition to being intuitive and interpretable, the mixed discrete and continuous variables with the hierarchy structure allow stakeholders to narrow the search space selectively based on their interests. As a proof-of-concept study, shape parameterization examples of tall building cross sections are used to demonstrate the promising features of the proposed scheme and guide future investigations on data-driven parameterization for aerodynamic shape optimization of wind-sensitive structures.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제25권12호
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the KSME Conference
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.