• Journal of the Korean Applied Science and Technology
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• v.36 no.4
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• pp.1410-1419
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• 2019

In this research, it is to find a method that frost does not form on the outdoor unit to develop a heat pump capable of heating in cold regions. For this reason, we produced an incubator capable of creating an environment of -25℃, and constructed an experimental apparatus so that experiments in the room were possible. However, it is necessary to grasp the characteristics of the air reaching the front of the heat pump outdoor unit installed in the experimental apparatus, and flow analysis was performed using ANSYS CFX, which is general-purpose software. As a result, the flow velocity of the air reaching the front of the outdoor unit in the outdoor unit chamber in the entire region of the simulation conditions (5.0 to 7.5 m/s) has many differences in the upper and lower portions, resulting in a natural state. It turned out that the condition can not be satisfied. Therefore, it is determined that it is necessary to additionally install a frequency divider at the front of the outdoor unit to make the flow velocity constant.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.38 no.2 s.115
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• pp.1-8
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• 2006

In this study a process simulation method was used to analyze the accumulation phenomena of anionic starch in the process white water as the closure level of a fine paper making process is increased. A pilot paper machine was used as a model process. Dynamic simulations of the influence of white water usage ratio and uncoated broke addition ratio on the variation of process variable was monitored as a function of time. Results from the dynamic simulations showed that the volume of reservoirs affected the dynamic behavior of the process. The dynamic behavior of flow rate and dissolved starch concentration in process units were different from each other. The speed of the change of dissolved starch concentration in process units was depend on the starting point of the change of dissolved starch concentration, the length of circulation loop, and the volume of reservoirs.

• Solar Energy
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• v.17 no.1
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• pp.103-111
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• 1997

The purpose of this research is the study of characteristics of heat transfer in a heat pipe controlled by solenoid valve. A solenoid valve located to the adiabatic section between evaporator and condenser of heat pipe was used to control the valve action for effective energy transfer of the industrial exchanger machine. By the results presented in this study temperature difference between evaporator and condenser increases with increasing the temperature frequency and with decreasing the temperature amplitude. When inclination angle and flow rate of cooling water increases, the temperature amplitude is reached to the steady state rapidly with increasing the temperature frequncy.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.101-108
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• 2002

A specially-built EMM (Electrochemical Micro Machining) / PECM (Pulse Electrochemical Machining) cell, a electrode tool filled with non-conducting material, a electrolyte flow control system and a small & stable gap control unit are developed to achieve accurate dimensions of recesses. Two electrolytes, aqueous sodium nitrate and aqueous sodium chloridc arc applied in this study. The farmer electrolyte has better machine-ability than the latter one because of its appropriate changing to the transpassive state without pits on the surface of workpiece. It is easier to control the machining depth precisely by micrometer with pulse current than direct current. This paper also presents an identification method for the machining depth by in-process analysis of machining current and inter electrode gap size. The inter electrode gap characteristics, inc1uding pulse current, effective volumetric electrochemical equivalent and electrolyte conductivity variations, are analyzed based on the model and experiments.

• Korean Journal of Computational Design and Engineering
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• v.19 no.3
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• pp.214-223
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• 2014

This paper presents a bottleneck detection framework using simulation approach in a wafer FAB (Fabrication). In a semiconductor manufacturing industry, wafer FAB facility contains various equipment and dozens kinds of wafer products. The wafer FAB has many characteristics, such as re-entrant processing flow, batch tools. The performance of a complex manufacturing system (i.e. semiconductor wafer FAB) is mainly decided by a bottleneck. This paper defines the problem of a bottleneck process and propose a simulation based framework for bottleneck detection. The bottleneck is not the viewpoint of a machine, but the viewpoint of a step with the highest WIP in its upstream buffer and severe fluctuation. In this paper, focus on the classification of bottleneck steps and then verify the steps are not in a starvation state in last, regardless of dispatching rules. By the proposed framework of this paper, the performance of a wafer FAB is improved in on-time delivery and the mean of minimum of cycle time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4310-4330
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• 2020

With the continuous emergence of new applications and cyberattacks and their frequent updates, the need for automatic protocol reverse engineering is gaining recognition. Although several methods for automatic protocol reverse engineering have been proposed, each method still faces major limitations in extracting clear specifications and in its universal application. In order to overcome such limitations, we propose an automatic protocol reverse engineering method using a two-pathway model based on a contiguous sequential pattern (CSP) algorithm. By using this model, the method can infer both command-oriented protocols and non-command-oriented protocols clearly and in detail. The proposed method infers all the key elements of the protocol, which are syntax, semantics, and finite state machine (FSM), and extracts clear syntax by defining fine-grained field types and three types of format: field format, message format, and flow format. We evaluated the efficacy of the proposed method over two non-command-oriented protocols and three command-oriented protocols: the former are HTTP and DNS, and the latter are FTP, SMTP, and POP3. The experimental results show that this method can reverse engineer with high coverage and correctness rates, more than 98.5% and 99.1% respectively, and be general for both command-oriented and non-command-oriented protocols.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.420-423
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• 2009

SOA는 최근 급부상한 패러다임으로 개발단위의 상태 변화가 사라지고, 데이터 흐름 중심이 아닌 메시지 흐름 중심으로 변하는 등의 기존 전통적 개발방법들과 차이점을 가지고 있다. 이러한 변화는 상태 변화를 표기하는 FSM(Finite State Machine)을 사용할 수 없다는 문제점을 가져왔고, 따라서 새로운 테스트 케이스 생성방법이 필요하게 되었다. 본 논문에서는 이러한 문제점을 해결하기 위해 메시지 흐름을 이용하여 서비스의 테스트 케이스를 생성하는 기법을 제안한다. BPM(Business Process Modeling)을 사용하여 단순한 그래프로 만들고 기존의 단순 비순환 그래프를 만드는 기법을 적용하여 테스트 시퀀스를 만든다. 그리고 테스트 시퀀스마다 순차 다이어그램을 만들고 메시지 흐름을 추출하여 테스트 케이스를 완성한다. 이 기법을 통해 웹서비스 뿐만 아니라 일반적인 서비스에 대한 테스트 케이스 생성을 가능하게 하며, 모델링 재사용을 통해 테스트 케이스 생성에 소요되는 추가 비용을 감소 시킬 수 있다.

• Elastomers and Composites
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• v.48 no.4
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• pp.282-287
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• 2013

Slot coating has been widely spread in photo resist coating on glass for flat display monitor. High quality of coating is required as high quality of image in display is needed. Coating quality in the slot coating is divided into nozzle direction quality and machine direction quality. Nozzle direction quality is related to flow uniformity inside the die whereas machine direction quality is related to die lip design and operational conditions. In this study coating uniformity in the machine direction of slot coating has been investigated through computer simulation. Die lip angle and die lip length were considered as outside die geometry and coating speed was considered as operational condition. Coating behavior has been analyzed and coating quality has been evaluated through computer simulation. Coating thickness decreased and coating uniformity increased as coating speed increased. However, the stability of meniscus formation was reduced and subsequently coating stability was reduced as coating speed increased. Coating thickness deviation decreased as die lip angle increased in down stream die. Coating thickness decreased and time to reaching steady state increased as increased die lip length in down stream die.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.