• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.727-730
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• 2000

Recently, RoboCup soccer simulation has been regarded as a good benchmark problem for multiagent researches. Soccer agents have to make decision based on visual and auditory information, which are sent from the soccer server. In order to develop a strong team, we have to design decision-making process of each player agent. However, it is very difficult for us to design the decision-making processes in detail, because we don't know what actions of each player are effective for the team. In this paper, we attempt to apply co-evolutionary method, which is one type of analogies of evolution, to improve the team play. Agents have hand coded basic skills, which include dribble, shoot, pass etc. Agents already can play autonomously and independently. Individual agent skills are characterized by some parameters. By coevolving teams with these parameters, we obtained relatively interesting teams, in which players behave cooperatively in order to win the soccer game. From some experiments, we discuss what teams are evolved.

• Journal of the Korea Computer Graphics Society
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• v.23 no.4
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• pp.21-29
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• 2017

Previous visual analytics researches has focused on reducing the uncertainty of predicted results using a variety of interactive visual data exploration techniques. The main purpose of the interactive search technique is to reduce the quality difference of the predicted results according to the level of the decision maker by understanding the relationship between the variables and choosing the appropriate model to predict the unknown variables. However, it is difficult to create a predictive model which forecast time series data whose overall trends is unknown such as youth physical growth data. In this paper, we pro pose a novel predictive analysis technique to forecast the physical growth value in small pieces of time series data with un certain trends. This model estimates the distribution of data at a particular point in time. We also propose a visual analytics system that minimizes the possible uncertainties in predictive modeling process.

• Journal of Korean Society for Quality Management
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• v.48 no.2
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• pp.297-307
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• 2020

Purpose: The purpose of this study is to analyze the factors that affect ammunition performance by applying data mining techniques to the Ammunition Stockpile Reliability Program (ASRP) data of the 155mm propelling charge. Methods: The ASRP data from 1999 to 2017 have been utilized. Logistic regression and decision tree analysis were used to investigate the factors that affect performance of ammunition. The performance evaluation of each model was conducted through comparison with an artificial neural networks(ANN) model. Results: The results of this study are as follows; logistic regression and the decision tree analysis showed that major defect rate of visual inspection is the most significant factor. Also, muzzle velocity by base charge and muzzle velocity by increment charge are also among the significant factors affecting the performance of 155mm propelling charge. To validate the logistic regression and decision tree models, their classification accuracies have been compared with the results of an ANN model. The results indicate that the logistic regression and decision tree models show sufficient performance which conforms the validity of the models. Conclusion: The main contribution of this paper is that, to our best knowledge, it is the first attempt at identifying the significant factors of ASPR data by using data mining techniques. The approaches suggested in the paper could also be extended to other types ammunition data.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.226-227
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• 2007

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.73-76
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• 2004

본 연구는 사출 성형에 있어서의 불량과 그에 따른 해결책을 Visual Basic을 이용하여 전산 정보화함으로써 성형 불량 대책을 제공, Gate와 Runner를 최적화하는 지적 결정 시스템을 개발하였다. 체계적인 기술이 정립되어 있지 않는 플라스틱 성형의 문제점을 최소화하고 재료비 절감, 설계 납기일 단축, 제품 품질 향상을 그 목적으로 하고 있다.

• Knowledge Management Research
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• v.21 no.3
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• pp.27-44
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• 2020

In order to solve the user's information overload problem, recommender systems infer users' preferences and suggest items that match them. The collaborative filtering (CF), the most successful recommendation algorithm, has been improving performance until recently and applied to various business domains. Visual information, such as book covers, could influence consumers' purchase decision making. However, CF-based recommender systems have rarely considered for visual information. In this study, we propose VizNCS, a CF-based deep learning model that uses visual information as additional information. VizNCS consists of two phases. In the first phase, we build convolutional neural networks (CNN) to extract visual features from image data. In the second phase, we supply the visual features to the NCF model that is known to easy to extend to other information among the deep learning-based recommendation systems. As the results of the performance comparison experiments, VizNCS showed higher performance than the vanilla NCF. We also conducted an additional experiment to see if the visual information affects differently depending on the product category. The result enables us to identify which categories were affected and which were not. We expect VizNCS to improve the recommender system performance and expand the recommender system's data source to visual information.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.629-635
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• 2012

Tracked robots usually have poor localization performance because of slippage of their tracks. This study proposes a new localization method for tracked robots that uses fuzzy fusion of stereo-camera-based visual odometry and encoder-based wheel odometry. Visual odometry can be inaccurate when an insufficient number of visual features are available, while the encoder is prone to accumulating errors when large slips occur. To combine these two methods, the weight of each method was controlled by a fuzzy decision depending on the surrounding environment. The experimental results show that the proposed scheme improved the localization performance of a tracked robot.

• Journal of Radiation Industry
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• v.18 no.1
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• pp.15-21
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• 2024

The Non-Proliferation Treaty (NPT) is the basis of global efforts to prevent the spread of nuclear weapons. In Republic of Korea, safety measures are integrated with NPT approval through agreements with the International Atomic Energy Agency (IAEA) and the Safeguards Agreement. In contrast, Democratic People's Republic of Korea (DPRK), initially an NPT member, withdrew, refusing IAEA nuclear inspections. This inhibits the precise management of DPRK's nuclear facilities and limits access to related information. The Korean Peninsula, politically divided, sees DPRK in control of nuclear weapons. Although the IAEA periodically evaluates DPRK's nuclear facilities, there's a research gap in contamination and site management with nuclear activities. Recognizing the presence or absence of such activities is crucial for peaceful nuclear endeavors. This proposal suggests the number and locations for environmental sample collection using the Visual Sample Plan (VSP) software for nuclear activity analysis. VSP software is sample collection locations and quantities through statistical tests on collected data, ensuring reliability for decision-making. The proposal identifies sites and facilities for nuclear activity analysis based on IAEA safety reports, utilizing the software's embedded methods. Suggested sampling locations for undisclosed nuclear activities employ VSP's embedded techniques, including 'Show that at least some high % of the sampling area is acceptable' to confirm contamination and 'Estimate the Mean' to evaluate the average contamination level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.153-160
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• 2009

A hierarchical network between Mobile-WiMAX and WLAN systems is to make it possible to utilize wireless internet services including time sensitive applications such as VoIP, VOD, visual telephony etc. During the process of vertical handoff decision from Mobile-WiMAX to WLAN hotspot, vertical handoff delay causes user dissatisfaction because it doesn't provide the seamless wireless internet service. We make use of type of service (ToS) parameters in IEEE 802.16e specification as the criterion parameter of vertical handoff decision process in hierarchical Mobile-WiMAX/WLAN networks. In this paper, we propose the process of vertical handoff decision for seamless wireless internet service which is sensitive to time delay. If type of service is time sensitive application, the decision of vertical handoff is withdrawn until the service is terminated. In focus on user satisfaction, if the proposed traffic management strategy in hierarchical Mobile-WiMAX/WLAN networks is used, user will utilize seamless wireless internet services including time sensitive applications.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.342-356
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• 2009

This paper presents a vote decision-based deinterlacing scheme for false directional error correction(VDD) to convert interlaced signal into non-interlaced signal using only one fields. The VDD using the vote decision goes through four steps process. The first step extracts regions having doubt of false edge using MM-ELA method. In these regions, the edge direction is decided by the majority vote using upper adjacent pixels's information through the second step. But, we still have undecided directions, which will be decided by the majority vote and the directional average decision at the third step. This step preserves the edge directions and minimizes visual degradation. Finally, the last step interpolates undecided pixels using DOI method which can consider the fine edge direction. Although the VDD with hierarchical structure has a high complexity, it can extract delicate edge compared to other pixel-by-pixel or window-by-window deinterlacing algorithms. Simulation results show that it has significantly improved both the subjective and objective qualities of the reconstructed images.