• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.95-104
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• 2015

Recently, collecting and analyzing method of users location has been studied due to the development of mobile devices. There is analyzing method using Semantic Location History in order to identify of characteristics and extract pattern and predict trajectory of users. We should extraction of Stay Point in order to use Semantic Location History. The Conventional extraction method of Stay Point is not accuracy of location of Stay Points because it does not specify the GPS log of users. Also, Conventional extraction method of Stay Point cannot distinguish indoors and outdoors. In this paper, we implement extraction method of Stay Point in which specify the GPS log of users and extraction of Stay Point at indoors only. Stay Point(nearSP) specifies the nearest GPS log of users from generated Stay Point by conventional extraction method. And, Stay Point(indoorSP) specifies the GPS log of users that user get into the building. Our experimental results, accuracy of Stay Point is improved, and capacity of output data decrease than Conventional extraction method. Also, we were able to distinguish Stay Point of indoors and outdoors.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1196-1198
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• 2015

최근 모바일 기기의 발전으로 사용자의 위치를 수집하고 분석하는 방법들이 연구되고 있다. 이러한 방법들 중 하나인 궤적 데이터 마이닝은 사용자의 궤적을 바탕으로 의미 있는 정보를 추출하기 위해 사용된다. 궤적 데이터 마이닝을 수행하기 위해서는 사용자의 GPS로그를 분석하여 Stay Point를 추출하는 과정이 선행되어야 한다. 기존의 Stay Point 추출 방법은 실내와 실외의 Stay Point를 구분하지 못한다. 본 논문에서는 기존의 Stay Point 알고리즘을 보완하기 위해 GPS 데이터 분포를 고려하여 실내에서 머무른 지점만을 추출하는 Stay Point 알고리즘을 제안한다.

• Smart Media Journal
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• v.5 no.4
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• pp.26-40
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• 2016

Recent researches have been conducted for a user of the position acquisition and analysis since the mobile devices was developed. Trajectory data mining of location analysis method for a user is used to extract the meaningful information based on the user's trajectory. It should be preceded by a process of extracting Stay Point. In order to carry out trajectory data mining by analyzing the user of the GPS Trajectory. The conventional Stay Point extraction algorithm is low confidence because the user to arbitrarily set the threshold values. It does not distinguish between staying indoors and outdoors. Thus, the ambiguity of the position is increased. In this paper we proposed extraction method of Stay Point using a statistical analysis. We proposed algorithm improves position accuracy by extracting the points that are staying indoors and outdoors using Gaussian distribution. And we also improve reliability of the algorithm since that does not use arbitrarily set threshold.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.81-91
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• 2012

Recently, as location-determination of indoor users is available with the development of variety of localization techniques for indoor location-based service, diverse indoor location based services are proposed. Accordingly, it is necessary to develop individualized POI recommendation service for recommending most interested points of large-scale commercial spaces such as shopping malls and departments. For POI recommendation, it is necessary to study the method for exploring location which users are interested in location with considering user's mobility in large-scale commercial spaces. In this paper, we proposed POI recommendation system with the definition of users' as 'Stay point' in order to consider users' various interest locations. By using the proposed algorithm, we analysis users' Stay points, then mining the users' visiting pattern to finished the proposed. POI Recommendation System. The proposed system decreased data more dramatically than that of using user's entire mobility data and usage of memory.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.125-133
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• 2008

According to longer and longer span, dynamic instability of stay cable should be prevented. Dynamic instability occurs mainly symmetric 1st mode and antisymmetric 1st mode in stay cable. Especially symmetric 1st mode has a lot of influence on sag. Therefore fundamental frequency of stay cable is different from that of taut sting. Irvine, Triantafyllou, Ahn etc. analyzed dynamic behavior of taut cable with sag through analytical technical and their researches give important results for large bounds of Irvine parameter. But each research shows mutually different values out of characteristic (cross-over or mode-coupled) point and each solution of frequency equations of all researchers can be very difficultly found because of their very high non-linearity. Presented study focuses on fundamental frequency of stay cable. Generalized mechanical energy with symmetric 1st mode vibration shape satisfied boundary conditions is evolved by Rayleigh-Ritz method. It is possible to give linear analytic solution within characteristic point. Error by this approach shows only below 3% at characteristic point against existing researches. And taut cable don't exceed characteristic point. I.e. high accuracy, easy solving techniques, and a little bit limitations. Therefore presented study can be announced that it is good study ergonomically.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.490-495
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• 2000

This paper presents the dynamic behavior of stay cable with Lead-Shear damper( LSD) near the support. This kind of research about the dynamic behavior of LSD is essential to design LSD in order to mitigate the ambient vibration of stay cable. The hysteresis curve of LSD was assumed to be perfect elasto-plastic behavior based on the real hysteretic behavior of such lead-based dampers. Mechanical model of LSD was equivalent Kelvin model and sag effect of stay cable was considered. Yielding force (also referred as size) of LSD was selected as a design parameter. Effects of tension of stay cable and installation point of LSD were studied. It was found that optimal size of LSD exists for each case of stay cable.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• Journal of International Academy of Physical Therapy Research
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• v.5 no.1
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• pp.696-700
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• 2014

This study was carried out to identify the influence of continuous physical therapy on long-stay elderly patients. This study classified 92 patients who had been hospitalized for one year into experimental group who continued to perform physical therapy and control group who did not conduct physical therapy and these two groups were classified into 0.5 point-questionable group, 1 point-mild dementia group, and 2 point-moderate dementia group based on the Clinical Dementia Rating Scale(CDR) when they were hospitalized in order to analyze the changes at the early stage of hospitalization and after one year has passed. As a result, it was appeared that both in CDR 0.5-point subgroup of questionable group and in CDR 1-point subgroup of mild dementia group, CDR was statistically significantly reduced in the experimental group whose physical therapy was continuously performed than in the control group whose physical therapy was not performed(p<.05) and that there was no significant difference in changes in the CDR between experimental group and control group in CDR 2-point group, which is a moderate dementia group.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.292-292
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• 2022