• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.26-30
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• 2020

In this paper, we studied the problem if the experiment number occurring in order to identify defect in scaffold. We need to change each of the 5 print factor to predict defect when printing disk type scaffold using FDM 3d printer. So then the number of scaffold print will be more than 100,000 times. This experiment number is difficult to perform in the field. In order to solve this problem, we have produced a prediction model based on machine learning multiple linear regression using print conditions and defect scaffold data for print conditions. The prediction model produced was verified through experiments. The verification confirmed that the error was less than 0.5 %. We have confirmed that satisfied within the target margin of error 5 %.

• Nuclear Engineering and Technology
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• 제55권11호
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• 디지털융복합연구
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• 제13권4호
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• pp.205-210
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• 2015

자동차산업의 발전과 함께 M2M(Machine-to-Machine)통신이 자동차 산업분야에서 많은 관심이 되고 있다. M2M은 기상, 환경, 물류, 국방, 농.축산 등에서 사용하기 시작하여 장비들이 자동으로 상황에 맞추어 통신을 하고 상황에 맞는 동작을 함으로써 운영해가는 시스템이다. 자동차에서도 차량내부 장치 간, 차대 차, 차와 교통시설물, 차와 주변의 환경 등에 적용되고 있다. 그러나 통신시스템의 특성상 전송구간에서 공격자의 공격에 대한 문제가 있으며 자동차의 운행, 제어계통 및 엔진제어 등에 공격자의 공격이 진행되면 안전에 심각한 문제가 발생하게 된다. 따라서 디바이스 간 보안통신에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 차량의 디바이스간 안전한 통신을 위해 해시함수 및 수학적 복잡한 공식을 이용하여 프로토콜을 설계하였으며 프로토콜 정형검증 도구인 Casper/FDR을 이용하여 실험하였으며 제안한 프로토콜이 각종 공격에 안전하게 동작되며 실제 적용할 때 효과적임을 확인하였다.

• 대한임베디드공학회논문지
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• 제14권4호
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• 대한기계학회논문집
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• 제16권1호
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• pp.22-30
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• 1992

The free vibrations of the outer-clamped spinning annular disk which simulates a wafer cutting machine are investigated. The effects of the initial tension, the centrifugal force and outer-fixture extension caused by spinning on the vibration characteristics of the disk are considered. The modal parameters of the disk are calculated by using Galerkin's method as the rotating speed and initial tension are varied. Laboratory experiments are also performed with a rotating and stationary disk, and, it is found that experimental and simulation results are in good agreement.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.450-450
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• 2000

This paper presents a software design simulation method for controlling multiple mechanism carrier system (MMCS), which is mainly used in a wrapping machine or a case packing machine. This method uses a mechanical tool-work interactive model proposed in this paper, in order to represent the interactive behaviors between some tools and a work driven by their tools, in which low effect states of a work are defined. Based on this method, a 3-D simulation system has been built. It consists of shape modeling of each device, behavior definitions of tools, and control logic using if-then expression. By applying it to a ase packing machine having about 30 mechanical devices and 100 inputs/outputs for control, the effectiveness of this method has been shown in general verification of control logic specification in an early software design phase and the possibility of smooth communication tool between mechanical and software designers.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.707-712
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• 1994

An Enhanced Shopfloor Oriented Programming(AESOP) system is developed as a programming utillity of the CNC turning machine. The developed system is specially designed to give a beginner the convenience for CNC part programming with graphical interaction between a machine operator and the AESOP system. The combination of process-oriented cycles and various contour programming as well as an immediate tool path verification support the easiness and swiftness of a part program generation in the shopfloor. Since the AESOP system has been designed to operate on the basis of MS-Windows in the PC-embedded CNC system, it is also useful for the training of the part programming by utilizing provailing personal computers in the educational department.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.464-469
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• 2023

The government has set the mechanization of paddy agriculture as a national task, aiming to achieve over 70% by 2025. The main objective is to stabilize the farming costs of rural households due to the aging and feminization of rural areas, as well as the shortage of agricultural labor. In response to this, the Korea Rural Economic Institute operates a farm machinery rental business. However, there are challenges in selecting and managing rental machinery, including issues related to labor, costs, verification, and time. Additionally, there is a limit to upgrades, and overseas models are being imported and used for transplanters and rice planters, which do not conform to domestic standards and face maintenance difficulties. In order to solve the difficulties of the agricultural machine rental business, we intend to develop an application that shares domestic and foreign machines purchased and used by individuals at a low cost and use them in gun-level administrative districts.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.

• 한국정밀공학회지
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• 제23권8호
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• pp.154-162
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• 2006

By laying its drum horizontally, front-loaded washing machine mostly used in Europe that uses the head of the water to launder was appropriate for washing only small amount of laundry. However, the demands of customers are requiring front-loaded washing machine to handle big capacity laundry as well, and have faster rotation speed to increase drying ability. To meet such demands, more stress from bending and twisting are complexly loaded onto the shaft supporting the horizontal drum, causing problems in fracture strength and fatigue life. Shafting system is mainly divided into flange and shaft. Flange is located between the drum and shaft, transferring power from the shaft to drum, and acting as a supporter of the back of the drum. Shaft is connected from the flange to insert production, transferring power from the motor to drum, and mainly acting as stiffness against the horizontal weight of the shafting system. In this paper, strength analysis and experiment were executed on both the shaft and flange of front-loaded washing machine to suggest the design improvement of shafting system for big capacity, high-rotation drying. Also, verification of this evaluation was executed on fracture strength and fatigue life for studied shaft system.