• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.63-69
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• 2009

Climate change has influenced on various sectors including ecosystem, water resource, natural hazards and health and so on. Thus, it is essential to more accurately assess climate change impact and prepare adaptation strategy. However, it is difficult to assess for climate change impact on various sectors with integrated form due to various data format by sectors. In this study, we prepared criteria and indicators for assessing climate change impact and integrated GIS based data which in correspond to indicators based on spatio-temporal information using GIS. Finally we suggest a guideline to assess vulnerability of each sectors to climate change based on integrated spatio-temporal information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2885-2891
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp, and then propose an improved two-stage tweet bot detection algorithm by computing an entropy based on spatio-temporal information. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.286-289
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• 2003

In this paper, the performance of W-CDMA system with smart antenna is analyzed for angular spread in spatio-temporal wideband vector channel. We consider correlation between any two elements of antenna array, the angle spread of multipath, and structure of antenna array in this channel model. And each multipath is assumed as a reflective wave from only one direction. Several multipaths within one chip are distinguished into each one and the strongest signal is selected. As a result, the performance of the W-CDMA system with smart antenna in spatio-temporal wideband vector channel has been considerably improved in proportion to the increase of angular spread.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.211-221
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• 2016

The human spatial mobility information is in high demand in various businesses; however, there are only few studies on human mobility because spatio-temporal data is insufficient and difficult to collect. Now with the spread of smartphones and the advent of social networking services, the spatio-temporal data began to occur on a large scale, and the data is available to the public. In this work, we compared the movement behavior of residents and tourists by using geo-tagged tweets which contain location information. We chose Seoul to be the target area for analysis. Various creative concepts and analytical methods are used: grid map concept, cells visited concept, reverse geocoding concept, average activity index, spatial mobility index, and determination of residents and visitors based on the number of days in residence. Conducting a series of analysis, we found significant differences of the movement behavior between local residents and tourists. We also discovered differences in visiting activity according to residential countries and used applications. We expect that findings of this research can provide useful information on tourist development and urban development.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.89-101
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• 2015

Outbreaks of highly pathogenic avian influenza(HPAI) subtype H5N8 have occurred in Korea, January 2014 and it continued more than a year until 2015. And more than 5 million heads of poultry hads been damaged in 196 farms until May 2014. So, we studied the spatial, temporal and spatio-temporal patterns of the HPAI epidemics for understanding the propagation and diffusion characteristics of the 2014 HPAI. The results are expressed using GIS. Throughout the study period three epidemic waves occurred over the time. And outbreaks made three clusters in space. First spatial cluster is adjacent areas of province of Chungcheongbuk-do, Chungcheongnam-do and Gyeonggi -do. Second is Jeonlabuk-do Gomso Bay area. And the last is Naju and Yeongam in Jeollanam-do. Also, most of spatio-temporal clusters were formed in spatially high clustered areas. Especially, in Gomso Bay area space density and spatio-temporal density were concurrent. It means that the effective prevention activity for HPAI was carried out. But there are some exceptional areas such as Chungcheongbuk-do, Chungcheongnam-do, Gyeonggi-do adjacent area. In these areas the outbreak density was high in space but the spatio-temporal cluster was not formed. It means that the HPAI virus was continuing inflow over a long period.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.36-44
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• 2018

VR(Virtual Reality) and AR(Augmented Reality) devices are becoming more common, and the need for proper contents presentation techniques in such environments has been growing ever since the popularization of the devices. One of the contents is the spatio-temporal data, which has become more prominent since it could be both generated and consumed by a large number of ordinary users. In this work, the researcher analyzed the characteristics of spatio-temporal data as a source for visualization in VR and AR environment, and categorized prior visualization methods for such data, which were devised for traditional monitors. The researcher also reviewed the hardware specification of state-of-the-art devices, and examined the possibility of adopting the previous visualization approaches. This work is expected to contribute in designing spatio-temporal visualization for VR and AR environment by utilizing their unique characteristics.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.214-223
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• 2006

Recently there is a need to store and process enormous spatial data in spatio-temporal databases. For effective query processing in spatio-temporal databases, selectivity estimation in query optimization techniques, which approximate query results when the precise answer is not necessary or early feedback is helpful, has been studied. There have been selectivity estimation techniques such as sampling-based techniques, histogram-based techniques, and wavelet-based techniques. However, existing techniques in spatio-temporal databases focused on selectivity estimation for future extent of moving objects. In this paper, we construct a new histogram, named T-Minskew, for query optimization of past spatio-temporal data. We also propose an effective selectivity estimation method using T-Minskew histogram and effective histogram maintenance technique to prevent frequent histogram reconstruction using threshold.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.34-43
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• 2005

We will catch the spatio-temporal changes that analyse the unknown topography of Go-Gunsan Islands using Landsat TM satellite images into an unsupervised ISODATA classification and a supervised nearest likelihood classification. Each sedimental topography has the different characteristics according to building the Saemangeum embarkment. We will deal with the distribution of sedimental shapes using ERDAS Imagine 8. 6. The result that classifies specifically topographic properties of our research area be considered to get use of establishing the reclaiming program and predicating the reclaimed sedimental topography. The research area can be classified into tidal flats and sea level using band 4 among 7 bands of Landsat TM. Also band 5 can be used to classify the special unknown shapes of tidal flats. We will clarify the efficiency that spatio-temporal sedimental changes can be extracted through processing satellite images. Therefore, the spatio-temporal unknown topography change monitoring using satellite images is expected to be very useful to clarify whether the tidal flat is generated or not in the Go-Gunsan Islands at the outer side of the embarkment after constructing completely the Saemangeum tidal embarkment.

• 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.