• Journal of Korean Society of Water and Wastewater
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• v.11 no.3
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• pp.105-111
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• 1997

Taken from the entrance of Juam Dam to 11km long as survey, this study predicted the bed change according to the movement of sediment in jet flow zone. The result of applying compound model and jet model turned out to be satisfactory, though the latter was the better. The jet constant of Juam Dam could be controlled between 0.5 and 0.65. In the jet flow zone of the dam, the prediction of the bed change by the numerical motel showed almost the same to the observed data.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.100-101
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• 2019

For buildings where a large number of the evacuees who are restricted to evacuation behavior compared to normal people, evacuation safety zones should be secured against fire. In order to form a safe haven safety zone, we are going to predict the performance of the building and describe the plan to secure a safe haven zone accordingly.

• Journal of the Korean earth science society
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• v.34 no.4
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• pp.303-312
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• 2013

Typhoon Sanba was selected for describing the Korea Meteorological Administration (KMA) Global Data Assimilation Prediction System (GDAPS) model bias tendency in forecast for the interaction between mid-latitude trough and movement speed of typhoon. We used the KMA GDAPS analyses and forecasts initiated 00 UTC 15 September 2012 from the historical typhoon record using Typhoon Analysis and Prediction System (TAPS) and Combined Meteorological Information System-3 (COMIS-3). Sea level pressure fields illustrated a development of the low level mid-latitude cyclogenesis in relation to Jet Maximum at 500 hPa. The study found that after Sanba entered the mid-latitude domain, its movement speed was forecast to be accelerated. Typically, Snaba interacted with mid-latitude westerlies at the front of mid-latitude trough. This event occurred when the Sanba was nearing recurvature at 00 and 06 UTC 17 September. The KMA GDAPS sea level pressure forecasts provided the low level mid-latitude cyclone that was weaker than what it actually analyzed in field. As a result, the mid-latitude circulations affecting on Sanba's movement speed was slower than what the KMA GDAPS actually analyzed in field. It was found that these circulations occurred due to the weak mid-tropospheric jet maximum at the 500 hPa. In conclusion, the KMA GDAPS forecast tends to slow a bias of slow movement speed when Sanba interacted with the mid-latitude trough.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.435-444
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• 2009

In the case of oil spill accident at sea, information concerning the movement of spilled oil is important in making response strategies. Aircrafts and the satellites have been utilized for monitoring of spilled oil. In these days, numerical models are using to predict the movement of the spilled oil. In the future a coupling method of modeling and remote sensing data should be needed to predict more correctly the spilled oil. The purpose of this paper is to present an application of satellite image data to an oil spill prediction model as an initial condition. Environmental Fluid Dynamics Computer Code (EFDC) was used to predict the movement of the oil spilled from Hebei Spirit incident occurred in Taean coastal area on December 7,2007. In order to make the model initial condition and to compare the model results, two satellite images, KOMPSAT-2 MSC and ENVISAT ASAR obtained on December 8 and 11, were used during the period of the oil spill incident. The model results showed an improvement for the prediction of the spilled oil by using the initial condition deduced from satellite image data than the initial condition specified at the oil spill incident site in the respects of the distributed spilled area.

• PNF and Movement
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• v.22 no.1
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• pp.43-54
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• 2024

Purpose: Falls among persons older than 65 years are a significant concern due to their frequency and severity. This study aimed to develop a vest-type embedded artificial intelligence (AI) system capable of detecting and predicting falls in various scenarios. Methods: In this study, we established and developed a vest-type embedded AI system to judge and predict falls in various directions and situations. To train the AI, we collected data using acceleration and gyroscope values from a six-axis sensor attached to the seventh cervical and the second sacral vertebrae of the user, considering accurate motion analysis of the human body. The model was constructed using a neural network-based AI prediction algorithm to anticipate the direction of falls using the collected pedestrian data. Results: We focused on developing a lightweight and efficient fall prediction model for integration into an embedded AI algorithm system, ensuring real-time network optimization. Our results showed that the accuracy of fall occurrence and direction prediction using the trained fall prediction model was 89.0% and 78.8%, respectively. Furthermore, the fall occurrence and direction prediction accuracy of the model quantized for embedded porting was 87.0 % and 75.5 %, respectively. Conclusion: The developed fall detection and prediction system, designed as a vest-type with an embedded AI algorithm, offers the potential to provide real-time feedback to pedestrians in clinical settings and proactively prepare for accidents.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.25 no.4
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• pp.324-329
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• 1999

The facial esthetics are much affected by nasal changes due to especially its central position in relation to facial outline and so appropriately evaluated should be the functional and esthetic aspects of the nose associated with the facial appearance. Generally, a maxillary surgical movement is known to induce the changes of nasolabial morphology secondary to the skeletal repositioning accompanied by muscular retraction. These changes can be desirable or undesirable to individuals according to the direction and amount of maxillary repositioning. We investigated the surgical changes of bony maxilla and its effects to nasal morphology through the analysis of the lateral cephalogram in the Le Fort I osteotomy. Subjects were 10 patients(male 2, female 8, mean age 22.3 years) and cephalograms were obtained 2 weeks before surgery(T1) and 6 months after surgery(T2). The surgical maxillary movement was identified through the horizontal and vertical repositioning of point A. Soft-tissue analysis of the nasal profile was performed employing two angles: nasal tip projection(NTP), columellar angle(CA). Also, alar base width(ABW) was assessed directly on the patients with a slide gauge. The results were as follows; 1. Both anterior and superior movement above 2mm of maxilla rotated up nasal tip above 1mm. Either anterior or superior movement above 2mm of maxilla made prediction of the amount & direction of NTP changes difficult. Especially, a correlation between horizontal movement of maxilla and NTP rotated-up was P<0.01. 2. Both much highly anterior and superior movement of maxilla is accompanied by more CA increase than either highly. Especially, the correlation between horizontal movement of maxilla and CA change was P<0.05. 3. Anterior and/or superior movement of maxilla was accompanied by the unpredictable ABW widening. 4. The amount of changes of NTP, CA, and ABW is not in direct proportion to amout of anterior and/or superior movement of maxilla. 5. Nasal morphologic changes following Le Fort I osteotomy are affacted by not merely bony repositioning but other multiple factors.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.83-87
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• 2007

This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dead-reckoning path prediction, the error between the estimated and the actual static values which is over the threshold based on the shared object location requires interpolation and multicasting of the previous location by the ESPDU of DIS. The shared dynamic data of the 3D virtual environment is implementation using the VRML.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.233-240
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• 2003

A GIS-based tunnelling risk management system (GIS-TURIMS) has been developed in this study The developed system uses ArcView 8.2 as a basic platform and the built-in interface(VBA) has been used to perform first-order simplified analyses for prediction of tunnelling-induced ground movements and building damage assessment. The main emphasis in this study was to develop a working framework that can be used in the perspective of tunnelling risk management. The developed system is capable of carrying out computationally intensive first-order analyses for ground movement prediction as well as building/utilities damage assessment with fully taking advantage of the GIS technologies. This paper describes the concept and details of the GIS-TURIMS development and implementation.

• 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.

• 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.