• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.23-27
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• 2005

Humans perceptually segment events, but models that predict where events will be segmented are limited. Developing a detailed model may be hard because of the overlapping quality of events (i.e., one can smile and walk at the same time, but the endpoint of each event can be different). However, some aspects of events appear to be universally represented in the world's languages. For example, path, the trajectory of an object's movement, is one of the most universally encoded event features. Although it is generally encoded in the prepositions of English (e.g., up), in other languagesit is encoded in the verbs (e.g., descendere). Linguistic universals may represent basic levels of event perception. Here we consider how one of these, path, might be parsed. Because the spatiotemporal projection of paths to an observation point is similar to the spatial projection of objects, we tested the hypothesis that path segmentation and object segmentation would be based on similar image properties, such as discontinuities in orientation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1737-1745
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• 2000

In the last decade, considerable research effort has been studied ot multi-dimensional GIS and many spatiotemporal operations and query languages have been proposed. Many of them have focused on designing of operation, which process with data that is valid at current point in time. But, research that studied to updata operation that updates or inserts the past data is very rare. This paper designs an update operation and an insertion operation for integrity of past data of multi-dimensional GIS, and propose a new data model for efficient processing of the operations.

• Proceedings of the KSRS Conference
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• v.1
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• pp.79-81
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• 2006

Geostationary ocean satellite, unlike other sun-synchronous polar-orbit satellites, will be able to take a picture of a large region several times a day (almost with every one hour interval). For geostationary satellite, the target region is fixed though the location of sun is changed always. Thus, the ocean signal of a given target point is largely dependent on time. In other words, the ocean signal detected by geostationary satellite sensor must translate to the signal of target when both sun and satellite are located in nadir, using another correction model. This correction is performed with a standardization of signal throughout relative geometric relationship among satellite - sun - target points. One signal value of a selected pixel point of the target region of Geostationary Ocean Colour Imager (GOCI) would be set up as a standard, and the ratio of all remained pixel point can be calculated. This relative ratio called bidirectional factor, the result of modelling of spatiotemporal variation of bidirectional factor is shown.

• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.109-127
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• 2010

The Network Centric Warfare(NCW) is based on the linkage of forces by network to employ them as they are centralized, even though they are scattered. Also it can be used to overcome spatiotemporal obstacles. Under the concept of NCW, cognitive and social areas are getting more weight than information technology and physical ones. In this study we tried to investigate the affecting factors to execute NCW effectively by user's point of view to place the focus on cognitive and social aspects. We obtained some affirmative results that affect to conduct NCW in Korea. The advanced western NCW can be applicable in theoretically in Korea, however to employ NCW more effectively we need Korean style NCW which portrays the Korean realities and circumstances.

• Information Systems Review
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• v.11 no.1
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• pp.181-196
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• 2009

New domains in the analysis of the behavior of moving objects, particularly within human social settings, are generating research interest due to significant advances in the accuracy and production cost of global positioning system (GPS) devices. However, although potential applications have been described in multiple research areas, practical and viable business implementations of GPS technology remain challenging. This paper combines the potential of GPS capabilities with the analytical power of OLAP and data visualization to examine data on the movements of visitors in a zoological garden. Based on this example, the benefits and limitations of the application of GPS technology to the analysis of human spatial behavior are discussed.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1953-1972
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• 2022

The COVID-19 pandemic has resulted in a profound impact on large-scale gatherings throughout the world. Social distancing has become one of the most common measures to restrict the spread of the novel Coronavirus. Islamic pilgrimage attracts millions of pilgrims to Saudi Arabia annually. One of the mandatory rituals of pilgrimage is the symbolic stoning of the devil. Every pilgrim is required to perform this ritual within a specified time on three days of pilgrimage. This ritual is prone to congestion due to strict spatiotemporal requirements. We propose a pedestrian simulation model for implementing social distancing in the stoning ritual. An agent-based simulation is designed to analyze the impact of inter-queue and intra-queue spacing between adjacent pilgrims on the throughput and congestion during the stoning ritual. After analyzing several combinations of intra-queue and inter-queue spacings, we conclude that 25 queues with 1.5 meters of intra-queue spacing result in an optimal combination of throughput and congestion. The Ministry of Hajj in Saudi Arabia may benefit from these findings to manage and plan pilgrimage more effectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.356-359
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• 2009

최근 센서와 모바일 기술의 발달에 따라 대용량 데이터 처리가 가능해지고, 유비쿼터스와 텔레매틱스 등의 도입으로 공간 데이터가 다양한 환경에 응용되거나 활용 분야가 점차 증가하고 있다. 특히 사용자에게 다양한 공간 데이터를 제공하는 수치지도의 활용성이 점차 증가하고 있다. 기존의 수치지도 관리 시스템은 이력에 대한 체계적인 관리방법과 공간 객체의 변화를 분석 또는 이력에 대한 질의 처리에 대한 구체적인 방안이 없는 실정이다. 따라서 이 논문에서는 효율적인 이력 관리를 위해 시공간 데이터 모델을 설계하고 그 모델을 기반으로 공간 객체의 이력 관리 기법을 제안한다. 제안된 모델을 통해 효율적인 이력 관리 및 시간에 대한 질의 처리가 가능하며, 사용자에게 정확한 이력 정보를 제공할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.374-376
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• 2023

최근 환율 예측에 관한 다양한 연구가 진행되어 왔다. 이러한 추세에 대응하여 본 연구에서는 Pearson 상관 계수 및 상호 정보를 사용하여 외환 시장의 환율 변동을 분석하는 다중 연결 네트워크를 구축하였다. 본 연구에서는 이러한 구성된 환율 변화에 대한 시공간 의존성 네트워크를 만들고 그래프 기계 학습의 잠재력을 조사하여 예측 정확도를 향상시키려고 노력하였다. 본 연구 결과는 선형 및 비선형 종속 네트워크 모두에 대해 그래프 신경망을 활용한 임베딩을 활용하여 기존의 기계 학습 알고리즘과 결합시킬 경우 환율 변화의 예측력이 향상될 수 있음을 경험적으로 확인하였다. 특히, 이러한 결과는 통화 간 상호 의존성에만 의존하여 추가 데이터 없이 달성되었다. 이 접근 방식은 데이터 효율성을 강화하고 그래프 시각화를 통해 설명력 있는 통찰력을 제공하며 주어진 데이터 세트 내에서 효과적인 데이터를 생성하여 예측력을 높이는 결과로 해석할 수 있다.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1167-1176
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• 2004

Along the advent of Internet technology, the computing environment has been considerably changed in many application domains. Especially, a lot of researches for e-Logistics have been done for the last 3 years. The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. To construct effectively the e-Logistics framework, researches on the development of the Moving Object Technology(MOT) including GPS and GIS with spatiotemporal databases technique so far has been done The Moving Object Technology stands for the efficient management for the spatiotemporal objects such as vehicles, airplanes, and vessels which change continuously their spatial location along with time flows. However, most systems manage just only the location information detected lately by many reasons so that the uncertainty processing for the past and future location of the moving objects is still very hard. In this paper, we propose the moving object uncertainty model and system design for e-Logistics applications. The MOMS architecture in e-Logistics is suggested and the detailed explain of sub-systems including the uncertainty processor of moving objects is described. We also explain the comprehensive examples of MOMS and uncertainty processing in Delivery Parcel Application that is one of major application of e-Logistics domain.