• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1358-1364
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• 2002

Presently, Multimedia data are increasing suddenly in broadcasting and internet fields. For retrieval of still images in multimedia database, content-based image retrieval system is implemented in this paper that user can retrieve similar objects from image database after choosing a wanted query region of object. As to extract color features from query image, we transform color to HSV with proposed method that similarity is obtained it through histogram intersection with database images after making histogram. Also, query image is transformed to gray image and induced to wavelet transformation by which spatial gray distribution and texture features are extracted using banded autocorrelogram and GLCM before having similarity values. And final similarity values is determined by adding two similarity values. In that, weight value is applied to each similarity value. We make up for defects by taking color image features but also gray image features from query image. Elevations of recall and precision are verified in experiment results.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.530-540
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• 2003

As the amount of information on Internet sites increases, it becomes more necessary to provide information in efficient ways. However, information search methods based on Boolean combination of keywords that most sites provide are difficult to express user's intention adequately so that there are numerous unexpected search results. This paper proposes a conversational agent that provides users with accurate information in a friendly manner through natural language conversation. The agent recognizes user's intention by applying finite state automata to natural language queries, utilizes the intention for structured pattern matching with response knowledge, and thus provides answers that are robust against changes in word order and consistent with the user's intention. To show its practical utility, the agent is applied to the problem of introducing a Web site. The results show that the conversational agent has the ability to provide accurate and friendly responses.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.5
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• pp.430-437
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• 2021

In this paper, we propose a robust face recognition method against soft errors with a deep convolutional generative adversarial network(DCGAN) based compensation method by a cross-layer approach. When soft-errors occur in block data of JPEG files, these blocks can be decoded inappropriately. In previous results, these blocks have been replaced using a mean face, thereby improving recognition ratio to a certain degree. This paper uses a DCGAN-based compensation approach to extend the previous results. When soft errors are detected in an embedded system layer using parity bit checkers, they are compensated in the application layer using compensated block data by a DCGAN-based compensation method. Regarding soft errors and block data loss in facial images, a DCGAN architecture is redesigned to compensate for the block data loss. Simulation results show that the proposed method effectively compensates for performance degradation due to soft errors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.146-159
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• 2018

This study analyzed what premium features significantly affect customer satisfaction and their recommendation, and what factors significantly affect product attributes. In the process, first, the loyalty program and the customer compensation program were studied to determine the impact of the customer satisfaction and recommendation. The study analyzed that quality and design of product properties had significant effects on all factors, but the brand was not significantly affected. Second, while superiority, differentiation and scarcity of luxury items are significant to customer satisfaction but superiority is only significant in relation to recommendation intention. Third, the preceding study shows that the customer compensation program has a significant impact on sales growth, but the study found that it was not for imported luxury car customers. Fourth, if the royalties program is low in awareness, it has been analyzed that the scarcity and customer satisfaction relationships among luxury goods have been adjusted. On the contrary, if there is a high level of awareness, it is analyzed that there is a control effect customer satisfaction and differentiation among luxury brands. In the conclusion, in order to satisfy customers at the import luxury car market, the differentiation of luxury goods by standard index must be strengthened and the brand must be strengthened among the attributes of the product. In addition, by raising awareness of the royalties program, the relationship between differentiation and customer satisfaction can be enhanced.

• Journal of Aerospace System Engineering
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• v.13 no.4
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• pp.26-36
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• 2019

The precise alignment between optical components is required in high-resolution earth observation satellites. However, the misalignment of optical components occurs due to external factors such as severe satellite launch environment and space environment. A satellite optical system with a focus mechanism is required to compensate for the image quality degraded by these misalignments. This study designed, fabricated, aligned precisely, and carried out a performance tests for the image quality of the system. The satellite optical camera performance tests were carried out to check the image quality change by operating the focus mechanism and to analyze the satellite optical system MTF by photographing USAF target using the autocollimator. According to the experimental results, the misalignments can be compensated sufficiently with the focus mechanism. Finally the basic data for re-focusing algorithm of the optical system was obtained through this study.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.6
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• pp.397-404
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• 2019

Linear Shaped Charge (LSC) that is widely used as separation system in aerospace system has to charge lots of explosives due to lack of uniformity. In addition, it is hard to optimize shape of liner and explosives because of manufacturing process. In order to overcome aforementioned drawbacks, Precision Linear Shaped Charge (PLSC) is currently under development. PLSC is made in two steps: prepare liner independently and charge explosive uniformly. In this study, PLSC is designed to have proper amount of explosives and penetration test of PLSC with different stand-off distance from liner to target is conducted to confirm penetration performance. Based on the penetration test results of PLSC, the numerical analysis method using AUTODYN is established and verified. Penetration mechanism and characteristics of PLSC is analyzed from the numerical and experimental results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.190-197
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• 2020

Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.25-38
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• 2022

With the diversification of payment methods and games, related financial accidents are causing serious problems for users and game companies. Recently, game companies have introduced an Fraud Detection System (FDS) for game payment systems to prevent financial incident. However, FDS is ineffective and cannot provide major evidence based on judgment results, as it requires constant change of detection patterns. In this paper, we analyze abnormal transactions among payment log data of real game companies to generate related features. One of the unsupervised learning models, Autoencoder, was used to build a model to detect abnormal transactions, which resulted in over 85% accuracy. Using X-FDS (Explainable FDS) with XAI-SHAP, we could understand that the variables with the highest explanation for anomaly detection were the amount of transaction, transaction medium, and the age of users. Based on X-FDS, we derive an improved detection model with an accuracy of 94% was finally derived by fine-tuning the importance of features that adversely affect the proposed model.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.116-126
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• 2006

The purpose of this study is to analyze the growing course of Busan, Gimhae and Jinhae and further find patterns of the urban growth. This study shows that patterns of the urban growth differ from city to city, being influenced by the city's characteristics. Acknowledging this fact would help the decision maker to determine the developing plan of the urban. The methodology for this study is as follows; Fuzzy set concept is applied to minimize the data loss. At the same time, the AHP is used to give a relative weight to each factor. In order to be able to manage the change based on the dynamic model and time, Cellular Automata is introduced to simulate the growth of urban. The results show that the pattern of Gimhae's and Jinhae's growth is the same, whereas that of Busan is different from them. That is to say, each city has regional characteristics. And the pattern of the urban growth is influenced by the regional conditions of the city.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.333-338
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• 2017

In recent years, there has been an increasing demand for healthcare services that can periodically monitor health status and maintain health by increasing the weight training population. However, injuries in the absence of trainer are increasing with the increase in the number of members in the fitness training center. Therefore, there is a need for a system that can periodically monitor the user's exercise state and assist in systematic and safe exercise even when the trainer is absent. In this study, we developed an auto training system that can effectively manage the exerciser while supporting the strength movement. The auto training system consists of a cable mount module, a control module, and a training information monitoring module. In order to evaluate performance of the developed system, the assistant force tests are carried out. Experimental results showed that the assistant force works well when the exerciser is out of power.