• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.83-85
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• 2000

멀티미디어 서버는 시간 제약성을 가지는 멀티미디어 데이터를 정해진 시간 이내에 디스크로부터 검색해야 하므로 디스크 검색 요청 이전에 디스크 서비스 시간을 예측하여 제한된 시간 이내에 종료된다는 것을 보장해야 한다. 리눅스는 자원의 이용률 및 시스템 성능을 향상시키기 위해서 선행 읽기와 페이지 캐쉬 등의 기법들을 사용하고 있는데 이러한 기법들의 사용으로 디스크 서비스 시간은 매우 가변적이게 된다. 본 논문에서는 리눅스 파일 시스템을 개선하여 디스크 서비스 시간의 가변성이 최소화되도록 하고 이를 기반으로 정밀한 회전 지연 시간 모델에 의한 디스크 서비스 시간의 예측 기법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.662-664
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• 2008

위치기반 검색, 광고, SNS, 지도 등 사용자의 위치에 기반한 다양한 서비스들이 모바일 디바이스 사용자에게 제공되어 지고 있다. 그러나 이러한 서비스들은 대부분 현재시점의 사용자의 위치 정보를 기반으로 하고 있어, 제공 가능한 서비스 영역이 제한되어 있다. "Where" 뿐만이 아니라, "When-Where-What" 을 안다면 이러한 제한을 극복하고 사용자에게 보다 편리하고 유용성 있는 정보와 서비스 제공이 가능할 것이다. 본 연구에서는 모바일 디바이스에서 생성 가능한 사용자의 라이프 로그를 효율적으로 수집하고, 수집된 로그를 분석하여 사용자의 행동 예측 데이터를 제공하는 시스템을 제안하였다. 제안 시스템은 라이프로그에 기반한 사용자의 행동 예측을 가능하게 하여, 이를 통한 다양한 응용서비스 제공을 지원한다.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1594-1609
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• 2010

In the case that multiple services are in race condition for limited I/O resource, the services or processes with lower priority occasionally occupy most of limited I/O resource. And it decreases QoS and performance of important services and makes it difficult to efficiently use limited I/O resource. Although system administrator allocates I/O resource according to priority of process, he/she can't know or expect how much resource will be used by the specific process. Due to these reasons, it causes the problem that he/she can't guarantee the service QoS and performance stability. Therefore, in this paper, we propose service based disk I/O control supporting predictable I/O bandwidth to resolve upper problems. Proposed I/O control guarantees the service QoS and performance stability by supporting the service based predictable I/O bandwidth and it makes limited I/O resource to be efficiently used in respect of service.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.5
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• pp.587-596
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• 2008

For Wireless internet service in Metropolitan area, optimum location selection for base station and cell planning are critical process in determining service coverage by accurate prediction of Wave Propagation Characteristics. Due to different kinds of characteristics in service area such as lay of land, natural feature and material, height and width of artificially made building, it has a great impact on the transmission and distance recovery of wireless network service. Therefore, these facts may cause substantial barriers in predicting & analyzing the expected level of service quality and providing it to subscribers. In this thesis, we have simulated the process to improve quality and coverage of the service by adjusting the location of Base station and the antenna angle that influence the service after the basic location of base station is selected according to the wave prediction model. Based on this simulations test, we have demonstrated the results in which subscribers would get higher quality of wireless internet service along with bigger coverage and the improved quality in the same service coverage area through optimization process of base station.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.247-248
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• 2023

한인가정상담소의 발표에 따르면 COVID-19의 확산이 본격 시작된 2020년에 '부부·파트너 간 갈등'이 상담소 내담자의 가장 큰 비중을 차지한다. 이러한 상황에서 본 논문은 웹 기반의 이혼 확률 예측 서비스를 구현함으로써 상담 전 부부 사이의 심각성을 파악하는 데 도움을 주고자 한다. 서비스를 구현하기 위해 Kaggle에 공개된 이혼 예측 데이터를 활용하여 설문지에 대한 응답을 기반으로 이혼 확률을 예측하는 인공지능 모델을 생성하고 웹에 적용하였다.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.68-83
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• 2019

The number of pedestrian traffic accident fatalities is three times the number of car accidents in South Korea. Serious accidents are caused especially at intersections when the vehicle turns to their right. Various pedestrian collision warning services have been developed, but they are insufficient to prevent dangerous pedestrians. In this study, P2CWS is developed to warn approaching vehicles based on the pedestrians' characteristics. In order to evaluate the performance of the service, actual pedestrian data were collected at the intersection of Daejeon, and comparative analysis was carried out according to pedestrian characteristics. As a result, the performance analysis showed a higher accordance when the characteristics of the pedestrian is considered. Accordingly, we can conclude that identifying pedestrian characteristics in predicting the pedestrian crossing is important.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.349-352
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• 2009

본 연구는 협력적 필터링 기법을 이용한 선호도 예측 과정에서 발생하는 추가 정보를 이용하여 선호도 예측 정확도를 향상시킬 수 있는 방안에 대하여 연구하였다. 본 연구에서는 특정 상품에 대한 목표 고객의 선호도 예측에 선정된 이웃의 수와 선호도 예측 정확도와의 관계를 분석하였다. 분석을 위하여 선호도 예측 과정에 선정된 이웃의 수를 4분위수로 4집단으로 구분하여 구분 집단 간 선호도 예측 정확도에 차이가 나타남을 알 수 있었으며 각 집단의 예측 오차들의 평균들을 이용하여 선형의 보정함수를 제안한다. 본 연구의 결과를 바탕으로 추천시스템에서 이웃 수를 이용한 보정함수를 이용하면 예측 정확도를 높일 수 있다.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.503-513
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• 2005

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods. In the prediction accuracy test of the method, high sensitivity($77\%$) and specificity($95\%$) are achieved for test protein pairs containing common domains with teaming sets of proteins in a Yeast. The stability of the method is also manifested through the testing over DIP CORE, HMS-PCI, and TAP data. Performance, openness and flexibility are the major design goals and they are achieved by adopting parallel execution techniques, web Services standards, and layered architecture respectively. In this paper, several representative user interfaces of the system are also introduced with comprehensive usage guides.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.242-247
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• 2009

Recently an intelligent system is developed for the service what users want not a passive system which just answered user's request. This intelligent system is used for personalized recommendation system and representative techniques are content-based and collaborative filtering. In this study, we propose a prediction system which is based on the techniques of recommendation system using a collaborative filtering and a fuzzy system to solve the collaborative filtering problems. In order to verify the prediction system, we used the data that is user's rating about movies. We predicted the user's rating using this data. The accuracy of this prediction system is determined by computing the RMSE(root mean square error) of the system's prediction against the actual rating about the each movie and is compared with the existing system. Thus, this prediction system can be applied to base technology of recommendation system and also recommendation of multimedia such as music and books.