• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.376-379
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• 2010

인간의 학습과 기억현상에 있어서 멀티모달 데이터를 사용하는 것은 단순 모달리티 데이터를 사용하는 것에 비해서 향상된 효과를 보인다는 여러 연구 결과가 있어왔다. 이 논문에서는 인간의 순차적인 정보처리와 생성현상을 기계에서의 시뮬레이션을 통해서 기계학습에 있어서도 동일한 현상이 나타나는지에 대해서 알아보고자 하였다. 이를 위해서 가중치를 가진 랜덤 하이퍼그래프 모델을 통해서 순차적인 멀티모달 데이터의 상호작용을 하이퍼에지들의 조합으로 나타내는 것을 제안 하였다. 이러한 제안의 타당성을 알아보기 위해서 비디오 데이터를 이용한 문장생성을 시도하여 보았다. 이전 장면의 사진과 문장을 주고 다음 문장의 생성을 시도하였으며, 단순 암기학습이나 주어진 룰을 통하지 않고 의미 있는 실험 결과를 얻을 수 있었다. 단순 텍스트와 텍스트-이미지 쌍의 단서를 통한 실험을 통해서 멀티 모달리티가 단순 모달리티에 비해서 미치는 영향을 보였으며, 한 단계 이전의 멀티모달 단서와 두 단계 및 한 단계 이전의 멀티모달 단서를 통한 실험을 통해서 순차적 데이터의 단계별 단서의 차이에 따른 영향을 알아볼 수 있었다. 이를 통하여 멀티 모달리티가 시공간적으로 미치는 기계학습에 미치는 영향과 순차적 데이터의 시간적 누적에 따른 효과가 어떻게 나타날 수 있는지에 대한 실마리를 제공할 수 있었다고 생각된다.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.

• Annual Conference of KIPS
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• 2003.11b
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• pp.631-634
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• 2003

이동체 기술은 자동차, 비행기, 선박 등과 같이 시간에 따라 공간상의 위치를 변경하는 시공간 객체에 대한 효율적인 데이터를 관리를 의미한다. 최근 정보통신 기술의 발전으로 이동차량의 위치를 측정하는 다양한 방법이 개발되었으며, 이를 기반으로 하는 개별적인 응용 시스템들이 개발되었다. 그러나 대부분의 기존의 관련 시스템은 특정한 단일의 측위 장치와 통신 방법만을 고려하여 구축되었기 때문에 이들간 데이터의 원활한 공유가 어려운 문제가 있다. 따라서 이 논문에서는 기존의 추적 기술을 토대로 생성된 다양한 형태의 위치 데이터를 통합하는 이동체 위치 데이터 인터페이스 모형을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.71-78
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• 2014

The RFID-tag objects can be recognized by a distinct reader where it is installed. The RFID-tag objects are likely described as storages rather than the mobiles in the use of GPS. As RFID tags are large in number compared to moving objects, so the storing and retrieval costs are highly expensive. Here, two solutions for spatio-temporal model taking account of the feature in the tagged objects are proposed. First, the moving-tag objects are expressed by the terms "now" as well as "path location". Second, the size of storing index was noticeably reduced by not saving the tag information of palletizing products but mapping the tagged objects.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.615-620
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• 2013

With the development of smartphones, the number of applications for smartphone increases sharply. As a result, users need to try several times to find their favorite apps. In order to solve this problem, we propose a recommendation system to provide an appropriate app list based on the user's log information including time stamp, location, application list, and so on. The proposed approach learns three recommendation models including Naive-Bayesian model, SVM model, and Most-Frequent Usage model using temporal and spatial attributes. In order to figure out the best model, we compared the performance of these models with variant features, and suggest an hybrid method to improve the performance of single models.

• Annual Conference of KIPS
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• 2006.05a
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• pp.537-540
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• 2006

실세계의 복잡하고 종합적인 정보를 빠르고 효율적으로 분석 처리할 수 있는 지리정보시스템(GIS : Geographic Information System)의 효용성이 인식되면서 전력산업에서도 전국의 시설물 관리를 위해 수치지리정보를 구축하였다. 한편, 약 10만호의 고압고객을 대상으로 15분 단위의 전력사용량을 무선통신망을 이용하여 자동원격검침(AMR: Automatic Meter Reading)하고 있다. 본 논문에서는 산재된 대용량의 AMR 시계열성 데이터와 공간성을 지니는 전력설비 데이터를 이용하여 시각적 수요분석 및 공간적 분포특성 부하분석을 할 수 있는 새로운 활용모델을 개발하고 그 결과를 제시하고자 한다.

• Spatial Information Research
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• v.17 no.3
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• pp.361-370
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• 2009

As the increasing interests of spatial information for different application area such as disaster management, there are many researches and development of indoor spatial data models and real-time evacuation management systems. The application requires to determine and optical paths in emergency situation, to support evacuees and rescuers. The optimal path in this study is defined to guide rescuers, So, the path is from entrance to the disaster site (room), not from rooms to entrances in the building. In this study, we propose a time-dependent optimal routing algorithm to develop real-time evacuation systems. The network data that represents navigable spaces in building is used for routing the optimal path. Associated information about environment (for example, number of evacuees or rescuers, capacity of hallways and rooms, type of rooms and so on) is assigned to nodes and edges in the network. The time-dependent optimal path is defined after concerning environmental information on the positions of evacuees (for avoiding places jammed with evacuees) and rescuer at each time slot. To detect the positions of human beings in a building per time period, we use the results of evacuation simulation system to identify the movement patterns of human beings in the emergency situation. We use the simulation data of five or ten seconds time interval, to determine the optimal route for rescuers.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.189-193
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• 2005

본 연구에서는 시공간 제약뿐만 아니라, 데이터의 다양성에 따른 제약조건까지도 최소화하여 온라인상에서 지리정보 활용성을 제고하기 위해 기존의 국가지리정보유통망을 지리정보통합포털로 발전시키기 위한 방안을 제시하였다. 이를 위해 미국의 지리정보포털인 GOS(Geospatial One-Stop)를 모델로 하여 우리나라 국가지리정보유통망을 지리정보통합포털로 발전시키기 위한 모델을 수립하였다. 지리정보통합포털 모델은 개방형 분산프로세싱 시스템 구조에 대한 In 국제표준인 RM-ODP를 기반으로 하여 전사적 관점, 정보관점, 전산관점, 공학관점에서 수립하였다. 이를 통해 국가지리정보유통망을 기반으로 각종 지리정보 및 지리정보서비스에 대한 접근성을 제고함으로써 국가차원에서 GIS활용도를 높이는데 기여할 수 있을 것으로 기대된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.291-297
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• 2014

Due to the rapid increase in demand for transportation of human and freight in modern railway systems, the CBTC system has been proposed, which is the solution for improvement of the line capacity that has been limited by the conventional track circuit based train control system. In the CBTC system, higher reliability of the communication system should be guaranteed for the safety of passengers and trains. However, due to the inherent characteristics of the wireless channel environment, performance degradations are inevitable. The diversity techniques can increase the reliability of data transmission using multiple antennas. In this paper, we investigate the performance of the STBC in the railway channel environment. Rician fading model is used for the viaduct scenarios which take important roles in the railway system. Also, considered is the Doppler effect which is an important factor in the mobile communication system. Simulations are performed to analyze the performance of the STBC in various channel environments. Results show that the performance degradation due to the phase error in viaduct scenarios is independent of the diversity order but is affected by the constellation of the modulation.