• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.160-171
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• 2008

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.39-52
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• 2006

With the recent the use of spatio-temporal data mining which can extract various knowledge such as movement patterns of moving objects in history data of moving object gets increasing. However, the existing movement pattern extraction methods create lots of candidate movement patterns when the minimum support is low. Therefore, in this paper, we suggest the STMPE(Spatio-Temporal Movement Pattern Extraction) algorithm in order to efficiently extract movement patterns of moving objects from the large capacity of spatio-temporal data. The STMPE algorithm generalizes spatio-temporal and minimizes the use of memory. Because it produces and keeps short-term movement patterns, the frequency of database scan can be minimized. The STMPE algorithm shows more excellent performance than other movement pattern extraction algorithms with time information when the minimum support decreases, the number of moving objects increases, and the number of time division increases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.388-394
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• 2007

In wireless network, we propose a predictive location update scheme which considers mobile user's(MU's) mobility patterns. MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.53-60
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• 2006

Handover of WiBro is based on 802.16e hard handover scheme. When PSS is handover, it is handover that confirm neighbor's cell condition and RAS ID in neighbor advertisement message. Serving RAS transmits HO-notification message to neighbor RAS. Transmiting HO-notification message to neighbor RAS, it occurs many signaling traffics. Also, When WiBro is handover, It occurs many packet loss. Therefore, user suffer service degradation. LPM handover is supporting seamless handover because it buffers data packets during handover. So It is proposed scheme that predicts is LPM handover and reserves target RAS with pre-authentication. These schemes occur many signaling traffics. In this paper, we propose PSS Movement Prediction to solve signaling traffic. Target RAS is decided by old data in history cache. When serving RAS receives HO-notification-RSP message to target RAS, target RAS inform to crossover node. And crossover node bicast data packet. If handover is over, target RAS forward data packet. Therefore, It reduces signaling traffics but increase handover success rate. When history cache success, It decrease about 48% total traffic. But When history cache fails, It increase about 6% total traffic

• Journal of the Ergonomics Society of Korea
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• v.29 no.3
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• pp.331-336
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• 2010

The purpose of this study was to identify the effect of the craniocervical posture on swallowing and hyoid bone movement with sitting posture in wheelchair, and to provide basic data for developing a treatment program for dysphagia. A total of sixty healthy adults without a history of dysphagia who were guardians or care assistants of inpatients at Hospital K underwent video fluoroscopy performed by physiatrists from April to July 2009. The results of the fluoroscopy were analyzed based on the measurement of hyoid bone movements. The hyoid bone movement(horizontal, vertical, and diagonal) was significantly high in the neutral craniocervical, chin-tuck, and sixty degrees extension postures, in descending order(p<.05). It was found that the neutral craniocervical posture is the most effective posture for hyoid bone movement with sitting posture in wheelchair.

• Journal of the Korean earth science society
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• v.25 no.3
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• pp.152-159
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• 2004

The purpose of this study was to explore characteristics of natural history museum exhibits from the viewpoint of science education. A total of ninety exhibits for this study were examined in national science museums of Korea and Japan. Exhibits of Tokyo national science museum were again divided into two groups: the old and traditional types, and the new and renovated ones. Even though analyzing data was not undertaken through quantitative statistical process, the interpretation of the data was valid enough to fulfill the purpose of the research. While there were clear changes and differences between the old and the new types of exhibits in Tokyo national science museum, the old part of Tokyo museum was similar to one in Korea. Based on analyzing the new types of Tokyo museum, the current movement in the field of natural history museums of Korea explicitly has toward utilizing more science education concepts and ideas.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.83-95
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• 2021

In this study, various usage patterns were analyzed after establishing a data mart for micro mobility analysis based on the rental history of public bicycles in Seoul. Rental history data is origin-destination data that includes the rental location and time, and the return location and time. About 1500 rental locations were classified according to the characteristics of the location to create a 'station type' dimension. We also created a 'path type' dimension that displays whether the rental location and return location are the same. In addition, a derived variable called speed, which is obtained by dividing the distance used by the time used, is added, and through this, the characteristics of the riding area and the reason for the rental can be estimated. Meanwhile, administrative district link, administrative neighborhood link, and station type link were created to apply network analysis. Through this analysis, the roles and proportions of administrative districts, public facilities, and private facilities engaged in micro-mobility services were visualized. 49.9% of rentals occur at rental offices near transportation facilities, and half of them occur at rental offices near subway stations. The number of rentals during the evening rush hour is more than double that of the morning rush hour. When the path type is unidirectional, there is a fixed destination, so the distance and time used are short, and the movement speed tends to be high. In the case of round-trip, the purpose of use is exercise or leisure, so the distance and time used are long, and the movement speed is slow. It is expected that the results of the analysis can be used as reference materials for selecting new rental locations, providing convenient services for users, and developing user-specialized products.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.15-26
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• 2018

This is a qualitative study conducted to understand and explain the experience of nursing students' exploring historic sites of independence movement overseas. The study's participants were 24 nursing students in the first and second graders who participated in a program to explore the historic sites of independence movement overseas at a college in C County, Gyeongsangbuk-do. The data collection period was from December 23, 2017 to December 25, 2017. The data collection was carried out in an open self-reporting process, and the collected data were analyzed using the qualitative content analysis method of Krippendorff[13]. Based on the analysis of the experience of nursing students' exploring historic sites of independence movement overseas 19 sub-theme, 10 themes, and 4 categories were derived. The four categories are "Our History Represented in the wake of the independence movement", "Footprint projected of an independent activist ", " Rage Boiling But Hope Remaining", "blooming patriotism through reflection". The results of this study provided an understanding of nursing students' experience in exploring the historical sites of independence movement and have shown that nursing students had the opportunity to recognize the history of independence movements, inspire patriotism and reflect on their attitude as nurses. In addition, institutional efforts and resources should be supported to address the lack of policies on the preservation of the historic sites for independence movements overseas, which are dependent on the private sector.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.97-104
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• 2017

Location prediction has been successfully utilized to provide high quality of location-based services to customers in many applications. In its usual form, the conventional type of location prediction is to predict future locations based on user's past movement history. However, as location prediction needs are expanded into much complicated cases, it becomes necessary quite frequently to make inference on the locations that target user visited in the past. Typical cases include the identification of locations that infectious disease carriers may have visited before, and crime suspects may have dropped by on a certain day at a specific time-band. Therefore, primary goal of this study is to predict locations that users visited in the past. Information used for this purpose include user's demographic information and movement histories. Data mining classifiers such as Bayesian network, neural network, support vector machine, decision tree were adopted to analyze 6868 contextual dataset and compare classifiers' performance. Results show that general Bayesian network is the most robust classifier.

• Journal of The Geomorphological Association of Korea
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• v.17 no.3
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• pp.31-47
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• 2010

The history of mass movement has been reconstructed from the Angol basin in Guryongcheon drainage basin. Sedimentary facies study, radiocarbon dating, particle size analysis, magnetic susceptibility and geomorphological analysis have been performed to reconstruct the paleo-environmental history of Angol basin. From 40,480 to 9,850yrBP there were five periods of slope instability and from 9,850yrBP to present there were at least four periods of slope instability. Magnetic susceptibility curves match well with the sedimentary facies data. This study may help reconstruct the denudational history of the small basins in Cheonan area and could be the cornerstone of the paleo-climatological study of the Korean Peninsula.