• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2371-2379
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• 2017

For the drone that is active in a wide search area, the time to grasp the target in the field of applications such as searching for emergency patients, monitoring of natural disasters requiring prompt warning and response, that is, the speediness of target detection is very important. In the actual operation of drone, the time for target detection is highly related to collaboration between drones and search algorithm to efficiently search the navigation area. In this research, we will provide a search method with cooperation of drone based on target existence probability to solve the problem of quickness in drone target search. In particular, the proposed method increases the probability of finding a target and shorten the search time by transmitting high-altitude drone search results to a low-altitude drone after searching first and performing more precise search. We verify the performance of the proposed method through several simulations.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.13-18
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• 2015

This paper proposes an optimum vision system analysis and a reliable high-precision positioning system that converges a GNSS and a vision system in order to resolve position error and outdoor shaded areas two disadvantages of GNSS. For location determination of the object, it should receive signal from at least four GNSS. However, in urban areas, exact location determination is difficult due to factors like high buildings, obstacles, and reflected waves. In order to deal with the above problem, a vision system was employed. First, determine an exact position value of a target object in urban areas whose environment is poor for a GNSS. Then, identify such target object by a vision system and its position error is corrected using such target object. A vehicle can identify such target object using a vision system while moving, make location data values, and revise location calculations, thereby resulting in reliable high precision location determination.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.745-748
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• 1996

Korea Composite Stock Price Index (KOSPI) was predicted using Cascade Correlation Network (CCN) model. CCN was suggested, by Fahlman and Lebiere [1990], to overcome the limitations of backpropagation algorithm such as step size problem and moving target problem. To test the applicability of CCN as a function approximator to the stock price movements, CCN was used as a tool for univariate time series analysis. The fitting and forecasting performance fo CCN on the KOSPI was compared with those of Multi-Layer Perceptron (MLP).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.474-477
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• 1996

In this paper, a numerical method is developed to solve the 2 dimensional missile/target persuit-evasion game. The numerical solver for the problem is composed of two parts: parametrization of the kinematic equations of motion using collocation and optimization of the parametrized minimax problem using a nonlinear programming. A numerical example is solved to verify the performance of the proposed numerical scheme.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.141-145
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• 2000

A systematic method to find the optimal blank shape for sheet forming is proposed by coupling the numerical simulation technique. A weighted parameter was introduced in order to simplify the multi-variable optimization problem to a single-variable problem. The proposed method has been applied to the blank design of drawing processes to obtain the near-net shape within the required error bound after forming, Excellent results have been obtained between the numerical results and the target contour shapes. Through the investigation the proposed systematic method for optimal blank design is found to be effective in the practical forming processes

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.129-133
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• 2023

Classification or prediction problem is how to solve it using a specific feature to obtain the predicted class. A wheat seeds specifications 4 3 classes of seeds will be used in a prediction process. A multi linear regression will be built, and a prediction error ratio will be calculated. To enhance the prediction ratio an ANN model will be built and trained. The obtained results will be examined to show how to make a prediction tool capable to compute a predicted class number very close to the target class number.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.849-854
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• 2007

It is difficult that we collect only target documents from the Innumerable Web documents. One of solution to the problem is that we select target documents on the Web site which services many documents of target domain. In this paper, we will propose an intelligent crawling method collecting needed documents based on URL pattern script defined by XML. Proposed crawling method will efficiently apply to the sites which service structuralized information of a piece with database. In this paper, we collected 50 thousand Web documents using our crawling method.

• Journal of The Korean Dental Society of Anesthesiology
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• v.12 no.3
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• pp.177-181
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• 2012

Amyotrophic lateral sclerosis (ALS) is one of the major neurodegenerative diseases that involves degeneration at all levels of the motor system- from the cortex to the anterior horn of the spinal cord. Patients with ALS often have difficulty of ambulation for dental treatment though they have poor oral hygiene state. General anesthesia may cause respiratory problem due to its high sensitivity to muscle relaxant and weakened upper airway. In this case report, 38-year-old female patient with ALS required many dental treatments. Conscious sedation with intravenous target controlled infusion method was successfully employed and patient was discharged without any complications.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.3
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• pp.177-183
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.17-24
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• 2015

Mixed acceptance sampling plans for quantity of products in prepackages are widely used for compliance testing. To pass testing, random samples jointly comply with two legal requirements: (i) the average net content of an inspection lot shall be not less than the labelled quantity and (ii) the numbers of under-filled prepackages in a sample are less than or equal to permitted numbers. This paper discusses some drawbacks of the acceptance sampling plans and requirements recommended in OIML R87 (KS A 50087 translated by Korean) developed by the International Organization of Legal Metrology and evaluates the producer's and consumer's risks. In addition, problem of determining a target value in filling processes of prepackages under the OIML R87 requirements is addressed and illustrated with a numerical example.