• The korean journal of orthodontics
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• v.21 no.3
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• pp.591-601
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• 1991

To determine the difference in cephalometric measurements between centric relation and centric occlusion, 60 patient-20 patients for each malocclusion group-were examined with the cephalograms in centric relation and in centric occlusion. The results are as follows: 1. There are differences in cephalometric measurements with the mandible in the two different position, and some measurements are statistically significant. 2. No clinically useful prediction may be made from cephalometric radiographs concerning the amount of mandibular deflection from centric relation to centric occlusion. 3. If, the large differences in the cephalometric measurements with the mandible in the two different position, the analysis with the cephalogram in centric occlusion is needed to be compensated with the other clinical approach.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.12 no.3
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• pp.159-169
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• 1983

The thermal Conductivities along the position of spherical shaped fruits, such as, apple, mandarine orange. citrus hagyul were predicted by the analysis of the cooling curves obtained by the hydrocooling procedure using ice water. The thermal conductivity was independent of temperature. The thermal conductivities along the position of the fruits were nearly constant, but their small deviations were inherited by the improper spherical shape and the heterogenous structural composition of the fruits. The thermal conductivities of apple, mandarine orange, and citrus hagyul were found to be 0.353, 0.430, and $0.397\;Kcal/mh^{\circ}C$, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.114-123
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• 1998

In the end milling process, the information of the surface errors plays an important role in adaptive control systems for precision machining. As the measuring accuracy of the surface errors directly matches the control's, it is an important factor for evaluating the performance of the system. In order to obtain the surface errors, the prediction using the cutting force, torque, motor power etc. is frequently practiced owing to the easiness in measurement. In the implementation of the prediction, the information on the cutting depths make it concrete and precise. Actually the axial depth of cut limits the range of the calculation. In general, it is not easy to know the cutting depths due to irregular shape of workpieces, inaccurate positioning of them on the table of machine tool, and machining error in the previous cutting. In addition to, even if cutting depths are informed, it is difficult to match the individual position of the cutter on the varying shape of the work material. This work suggests an algorithm estimating the cutting depths based on cutting force and makes it precise to predict the surface error. The proposed algorithm can be applied in more extensive cutting situations, such as presence of the tool wear, change of the work material hardness, etc.

• Fire Science and Engineering
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• v.23 no.5
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• pp.17-23
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• 2009

Moisture evaporates, when concrete is exposed to fire, not only at concrete surface but also at inside the concrete to adjust the equilibrium and transfer properties of moisture. The equilibrium properties of moisture are described by means of water vapor sorption isotherms, which illustrate the hysteretical behavior of materials. In this paper, the prediction method of the moisture distribution inside the concrete members at fire is presented. Finite element method is employed to facilitate the moisture diffusion analysis for any position of member. And the moisture diffusivity model of high strength concrete by high temperature is proposed. To demonstrate the validity of this numerical procedure, the prediction by the proposed algorithm is compared with the test result of other researcher. The proposed algorithm shows a good agreement with the experimental results including the vaporization effect inside the concrete.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.1-6
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• 2003

The Delayed Feedback Control method (DFC) proposed by Pyragas applies an input based on the difference between the current state of the system, which is generating chaos orbits, and the $\tau$-time delayed state, and stabilizes the chaos orbit into a target. In DFC, the information about a position in the state space is unnecessary if the period of the unstable periodic orbit to stabilize is known. There exists the fault that DFC cannot stabilize the unstable periodic orbit when a linearlized system around the periodic point has an odd number property. There is the chaos control method using the prediction of the $\tau$-time future state (PDFC) proposed by Ushio et al. as the method to compensate this fault. Then, we propose a method such as improving the fault of the DFC. Namely, we combine DFC and PDFC with parameter W, which indicates the balance of both methods, not to lose each advantage. Therefore, we stabilize the state into the $\tau$ periodic orbit, and ask for the ranges of Wand gain K using Jury' method, and determine the quasi-optimum pair of (W, K) using a genetic algorithm. Finally, we apply the proposed method to a discrete-time chaotic system, and show the efficiency through some examples of numerical experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.342-347
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• 2003

It is essential to develop an algorithm for the estimate of link travel velocity and for the supply and control of travel information in the context of intelligent transportation information system. The paper proposes the fuzzy logic based prediction of link travel velocity. Three factors such as time, date and velocity are considered as major components to represent the travel situation. In the fuzzy modeling, those factors were expressed by fuzzy membership functions. We acquire position／velocity data through GPS antenna with PDA embedded probe vehicles. The link travel velocity is calculated using refined GPS data and the prediction results are compared with actual data for its accuracy.

• Journal of Ocean Engineering and Technology
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• v.22 no.2
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• pp.34-41
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• 2008

As a basic study for developing a forecasting/estimating system that predicts water quality changes when Deep Sea Water (DSW) drains to the ocean after using it, this study was carried out as follows: 1) numerical simulation of the present state at DSW developing region in the East sea using SWEM, 2) numerical prediction of water quality changes by effluent DSW, 3) analysis of influence degree 'With defined DEI (DSW effect index) at F station. On the whole, when DSW drained to the ocean, Chl-a, COD and water-temperature were decreased and DIN, DIP and DO were increased by effluent DSW, and Salinity was steady. According to analysis of influence degree, the influence degree of DIN was the highest and it was high in order of Chl-a, COD, Water-temperature, DO, DIP and Salinity. The influence degree classified by DSW effluent position was predicted that suiface outflow was lower than bottom outflow. Ad When DSW discharge increased 10 times, the influence degree increased about $5{\sim}14$ times.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1260-1265
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• 2009

Topographical features in South Korea is characterized that 70% of territory is composed of the mountains that can experience intense rainfall during storms in the summer and autumn. Efficient planning and management of landscape becomes utmost important since the cutting slopes in the mountain areas have been increased due to the limited construction areas for the roadway and residential development. This paper proposed an efficient way of slope management for the landslide risk by developing Web-GIS landslide risk management system. By deploying the Logistic Regression Analysis, the system could increase the prediction accuracy that the landslide disaster might be occurred. High resolution survey technology using GPS and Total-Station could extract the exact position and visual shape of the slopes that accurately describe the slope information. Through the proposed system, the prediction of damage areas from the landslide could also make it easy to efficiently identify the level of landslide risks via web-based user interface. It is expected that the proposed landslide risk management system can support the decision making framework during the identification, prediction, and management of the landslide risks.

• The Journal of the Korea Contents Association
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• v.4 no.2
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• pp.21-27
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• 2004

In an urban area telecommunication using wireless system, the accurate prediction and analysis of wave propagation characteristics are very important to determine the service area optimized selection of base station, and eel design, etc. In the stage of these analyses, we have to present the propagation prediction mood which is varied with the type of antenna, directional angle, and configuration of the ground in our urban area in addition we need to perform an analysis of the conventional mode which is similar to ours and dig out the parameters to evaluate the wave environment before the cell design for the selected area. In this paper, we propose a wave propagation prediction model concerning the topography and obstacles in our urban area. We extract the parameters and apply them to the proposed wave environment for the simulation analyzing the propagation characteristics. Throughout these analyzing procedure, we extracted the essential parameters such as the position of the base station, the height of topography, and adequate type and height of the antenna with our preferable cuteness.