• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2C
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• pp.59-69
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• 2009

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in crystalline rocks like gneiss, granite, and so on, a prediction model was developed by the use of a decision tree model. The classification standard of the selected prediction model is composed of the slope angle, the coefficient of permeability and the void ratio in the order. The computer program, SHAPP ver. 1.0 for prediction of slope hazards around an important national facilities using GIS technique and the developed model. To prove the developed prediction model and the computer program, the field data surveyed from Jumunjin, Gangneung city were compared with the prediction result in the same site. As the result of comparison, the real occurrence location of slope hazards was similar to the predicted section. Through the continuous study, the accuracy about prediction result of slope hazards will be upgraded and the computer program will be commonly used in practical.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.451-458
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• 2011

In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.

• Journal of ILASS-Korea
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• v.1 no.3
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• pp.37-50
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• 1996

Computational fluid dynamics was used to optimize an A/C duct. Three dimensional flow analysis in an automotive A/C duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. Additionally, we studied the effect of location variation of 2nd branch on exit flow ratio and could find optimal location of 2nd branch. The design of an A/C duct was modeled and calculated to enhance the airflow distribution in each outlet using the STAR-CD computational fluid dynamics software. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the future, adoption of CFD to design an A/C duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

• The Journal of the Korean life insurance medical association
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• v.2 no.1
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• pp.260-266
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• 1985

Pregancy is a part of women's life and is common process experienced by most women. On the other hand, a few cannot be pregnant. There are many reasons of infertility and myoma uteri of pelvic mass is a rare reason of infertility. Complication of pregnancy accompanied with myoma uteri is largely affected by the size or location of mass and the incidence by myoma uteri in pregnancy rarely happened, but mass with long pedunculus causes torsion as uterus is getting bigger. In labor myoma uteri causes the abnormal condition of fetal presentation and results in the abnormal childbirth. In case of myoma uteri, maternal mortality is low and there by medical hazards also decrease, but as the life insurance medical is the extensive prediction science, we believe that the prediction of perinatal or the condition of afterbirth by knowing the location, size of myoma uteri contributes to the medical examination. We experienced one case of Elderly primigravida with myoma uteri in Med Dept of Dae Han Kyouk life Insurance Co. Ltd. which the insured with medical examination believe herself as menopause. So we report the observations with studies.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.10a
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• pp.124-127
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• 2000

The finite element analyses of the wrinkling initiation and growth in the sheet metal forming process provide the detailed information about the wrinkling behavior of sheet metal. The direct analyses of the wrinkling initiation and growth, however, bring about a little difficulty in complex industrial problems because it needs large memory size and long computation time. For the description of wrinkling growth, the mesh elements should be sufficiently small and the size of finite element matrix becomes large. In the static implicit finite element method therefore, the direct analysis of wrinkling growth in a complex sheet metal forming process is rather difficult. From the industrial viewpoint of tooling design, the readily available information of possibility and location of wrinkling is sometimes more preferable to the detailed time-consuming information. In the present study, therefore, the wrinkling factor that shows locations and relative possibility of wrinkling initiation is proposed as a convenient tool of relative wrinkling estimation based on the energy criterion. The location and relative possibility of wrinkling initiation are predicted by calculating the wrinkling factor in various sheet metal forming processes such as cylindrical cup deep drawing, spherical cup deep drawing, and elliptical cup deep drawing. The wrinkling factor is also implemented in the analysis of the door inner stamping process to predict wrinkling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.909-937
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• 2011

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.6
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• pp.56-62
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• 2005

The fatigue analysis and lifetime evaluation are very important in design procedure to assure the safety and reliability of the rubber components. Fatigue lifetime prediction methodology of the rubber component was proposed by incorporating the finite element analysis and fatigue damage parameter from fatigue test. Finite element analysis of 3D dumbbell specimen and rubber component were performed based on a hyper-elastic material model determined from material test. The Green-Lagrange strain at the critical location determined from the FEM was used for evaluating the fatigue damaged parameter of the natural rubber. Fatigue life of the rubber component are predicted by using the fatigue damage parameter at the critical location. Predicted fatigue lifes of the rubber component agreed fairly well the experimental fatigue lives.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.12-14
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• 2021

A sensor registry system (SRS) provides semantic metadata about a sensor based on location information of a mobile device in order to solve a problem of interoperability between a sensor and a device. However, if the GPS of the mobile device is incorrectly received, the SRS receives incorrect sensor information and has a problem in that it cannot connect with the sensor. This paper proposes a dual collaboration strategy based on geographical embedding and LSTM-based path prediction to improve the probability of successful requests between mobile devices and sensors to address this problem and evaluate with the Monte Carlo approach. Through experiments, it was shown that the proposed method can compensate for location abnormalities and is an effective multicasting mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.3
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• pp.164-168
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• 2002

Yield prediction model of rice based on the boundary line analysis of the relationships between rice yield and meteorological conditions during rice growing period was reported in the previous report (Kim et al, 2001). Using the 15-year data of the 20 locations used for the model formulation and of the 12 locations not used, the model was tested for its predictability of location to location, year to year, and variety to variety variation of rice yield. The model predicted reliably the mean yield differences among locations, the yearly yield variation in each location, and the yield variation by variety. However, the model showed relatively lower predictability for the years of cool weather injury especially in mountainous locations. In conclusion, the model using boundary line analysis could be used to predict the yield responses to meteorological conditions during rice growth period and the locational, yearly, and varietal variations of rice yield. And the predictability of the present yield prediction model might be improved by including the boundary line analysis for the other factors such as soil characteristics, fertilization levels, etc.