• The korean journal of orthodontics
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• v.52 no.2
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• pp.102-111
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• 2022

Objective: To develop and explore the usefulness of an artificial intelligence system for the prediction of the need for dental extractions during orthodontic treatments based on gender, model variables, and cephalometric records. Methods: The gender, model variables, and radiographic records of 214 patients were obtained from an anonymized data bank containing 314 cases treated by two experienced orthodontists. The data were processed using an automated machine learning software (Auto-WEKA) and used to predict the need for extractions. Results: By generating and comparing several prediction models, an accuracy of 93.9% was achieved for determining whether extraction is required or not based on the model and radiographic data. When only model variables were used, an accuracy of 87.4% was attained, whereas a 72.7% accuracy was achieved if only cephalometric information was used. Conclusions: The use of an automated machine learning system allows the generation of orthodontic extraction prediction models. The accuracy of the optimal extraction prediction models increases with the combination of model and cephalometric data for the analytical process.

• Journal of KSNVE
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• v.7 no.4
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• pp.621-629
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• 1997

For computer aided design and costruction of low noisy power plants, indoor and outdoor noise prediction program has been developed. The program utilizes the predefined data of noise sources and building materials and has the faculty to estimate the source level using the empirical formula in case of the measured data not being available. In the noise prediction, the mutual noise propagation between indoor and outdoor sites are considered. The outdoor noise source in the calculation of geometric divergence effects is modelled as the omni-directional finite line or planar source according to the source geometry and the receiving points. Outdoor noise prediction is carried out to consider the diffraction effect due to plant structures as well as the attenuation effect due to atmospheric absorption and soft ground. The results of indoor and outdoor noise prediction for a recently constructed diesel engine power plant show good agreement with the measured.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2771-2778
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• 2014

In this paper, we propose an algorithm that select efficient relay nodes using information of network environment and nodes. The proposed algorithm can be used changeable weight factors as following network environment in node density. The routing protocols adopting store-carry-forward method are used for solving network problems occurred by unstable end-to-end connection in Delay Tolerant Networks(DTNs). Exiting DTN routing algorithms have problems that large latency and overhead because of deficiency of network informations. The proposed algorithm could be provide a solution this problems using changeable weight factor and prediction of network environment. Thus, selected relay nodes work efficiently in unstable and stressed network environment. Simulation results show that enhancement performance as overhead, delivery ratio, average latency compared to exiting DTN routing algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.452-459
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• 1997

For computer aided design and construction of low noisy power plants, indoor and outdoor noise prediction program has been developed. The program utilizes the predefined data of noise sources and building materials and has the faculty to estimate the source level using the empirical formula in case of the measured data not being available. In the noise prediction, the mutual noise propagation between indoor and outdoor sites are considered. The outdoor noise source in the calculation of geometric divergence effects is modelled as the omni-directional finite line or planar source according to the source geometry and the receiving points. Outdoor noise prediction is carried out to consider the diffraction effect due to plant structures as well as the attenuation effect due to atmospheric absorption and soft ground. The results of indoor and outdoor noise prediction for a recently constructed diesel engine power plant show good agreement with the measured.

• Water for future
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• v.13 no.2
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• pp.55-62
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• 1980

It is very important thing that the high tide prediction along the sea-side before the typhoon landing. In Korea, every year somewhere of the near sea-shore has been suffered much damages by the high tide during typhoon season, and the governement has to spend much of the reserved budget to rescue and reconstruction the damaged facilities in the seas-shore area. In this point of view, as none of the high tide prediction program in Korea, the author aims to develope this kind of study, so that this application program may dedicate the concerned organizations such as Ministry of Construction, Commerce and Industry, and Agriculture Forestry and Fishery, etc. Due to developed the software of high speed electronic computer in recently, the complicated numerical analysis can be solve very conviniently. So the author tries to prepare the high tide predecation program using the equation of motion and continous in the fluide dynamics by the constant time and distance of the differentation method. The input data for this program are the weather chart and depth data of the mattered bay, inner-sea or outer-sea. This program has been applied on the Pohan inner harbor as a model and find ort the program computation results is coincide with the observed values of "FRAN" typhoon in 1976 at the Pohang harbor.ng harbor.

• Computers and Concrete
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• v.3 no.2_3
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• pp.177-195
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• 2006

Slipforming is a construction method in which the forms move continuously during the placement of concrete. This paper presents the development of a computer aided program designated as "CADSLIPFORM" for slipforming operations. The program incorporates maturity methods for the prediction of initial setting times of slipform concrete layers using laboratory data (time-temperature histories and setting times of concrete mixtures at different temperatures) and generates slipform mock-up times. The performance of CADSLIPFORM is validated by comparing simulated mock-up times with those estimated in the field through conventional hard front by rod (R) method. Moreover, the program versatility is demonstrated by illustrating mock-up simulations for different cases with variable slipform parameters such as: number and thickness of concrete layers, concrete temperature (simulating variable setting times) and slipform speed. The program also incorporates the choice of Freiesleben Hansen & Pederson (FHP) and Carino & Tank (CT) maturity functions. CADSLIPFORM can assist user to develop reliable schedule of slipforming operation suitable for a specific project by optimizing various slipform parameters.

• IE interfaces
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• v.11 no.1
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• pp.175-182
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• 1998

The maintainability prediction of an underwater military system is considered. A general and parctical prediction method for maintainability using MIL-HDBK-472 is presented. We develop a computer program to predict MTTR of an underwater military system. A case study is made to explain the proposed maintainability prediction method.

• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.11-18
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• 1999

Proper fatigue life prediction procedures are needed for mechanical structures which requires high durability and reliability. In this paper, a fatigue life prediction procedure has been developed for predicting fatigue life of moving structure under variable loadings. The developed procedure was efficiently applied for a fatigue life calculation of a container crane. Especially, the procedure is useful for safety assessment by computer simulation. A computer program was developed for fatigue life assessment by adopting the forementioned procedure.

• 유체기계공업학회:학술대회논문집
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• 2000.12a
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• pp.91-98
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• 2000

Developed is a computer program for the prediction of the aero-acoustic performance characteristics such as discharge pressure, efficiency, power and noise level in the basic design step of axial flow fan. The flow field and the aerodynamic performance of fan are analyzed by using the streamline curvature computing scheme with total pressure loss and flow deviation models. Fan noise is assumed to be generated due to the pressure fluctuations induced by wake vortices of fan blades and to radiate via dipole distribution. The vortex-induced fluctuating pressure on blade surface is calculated by combining thin airfoil theory and the predicted flow field data. The predicted aerodynamic performances, sound pressure level and noise directivity patterns of fan by the present computer program are favorably compared with the test data of actual fan. Furthermore, the present computer program is shown to be very useful in optimizing design variables of fan with high efficiency and low noise level and in analyzing their design sensitivities.