• Korean Journal of Oriental Medicine
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• v.12 no.2 s.17
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• pp.85-92
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• 2006

Pulse is one of the basic diagnostic information of TKM(Traditional Korean Medicine). To quantify and standardize pulse diagnosis, we had collected an amount of clinical data from May 2005 by using newly developed pulse analyzer. But there were many noises in pulse wave according to measuring method, environment, operator and condition of patient. So some data can’t be included for analyzing diagnosis. To reduce noises from measuring pulse and to collect reliable pulse wave data, we made the process map of measuring method and applied six sigma project. With this we can improved the method of measuring pulse wave in collecting clinical data. The project follows a disciplined process of five macro phases: define, measure, analyze, improve and control (DMAIC). A process map and C-E diagram are used to identify process input and output variables. The major input variables are selected by using C&E matrix, and process map is developed by analyzing input variables. And the optimum process conditions are going to be controled to avoid in increasing loss of collecting pulse wave data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.86-98
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• 2022

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.

• Korean Institute of Interior Design Journal
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• v.13 no.3
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• pp.187-196
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• 2004

The purpose of this study is to develope'a digital space design process using user's motion data' through a theoretical and experimental study. In the progress of developing a developing of design process, this study was concentrated on searching a digital method applying user's interactive reflections. As introducing a concept of space form being generated by user's experiences, we proposed'a digital design process using user's motion data'. In the experimental stage, user's motion data were extracted and transferred as digital information by user behavior analysis, optical motion capture system, immersive VR system, 3D softwares com computer programming. As the result of this study, another useful digital design process was embodied by building up a digital form-transforming method using 3D softwares providing internal algorithm. This study would be meaningful in terms of attempting a creative and interactive digital space design method, avoiding dehumanization of existing ones through the theoretical study and the experimental approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.210-212
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• 1996

Random drift rate (i.e., random drift in angle rate) of a gyro represents the major error source of inertial navigation systems that are required to operate over long time intervals. It is uncorrectable and leads to an increase in the error with the passage of time. In this paper a technique is presented for analyzing random process from experimental data and the results are presented. The problem of estimating the a priori statistics of a random process is considered using time averages of experimental data. Time averages are calculated and used in the optimal data-processing techniques to determine the statistics of the random process. Therefore the contribution each component to the gyro drift process can be quantitatively measured by its statistics. The above techniques will be applied to actual gyro drift rate data with satisfactory results.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.37-47
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• 1996

This paper presents an automatic tele-inspection scheme for the remotely manufacturing process. The remote-manufacturing process is continuously monitored and a crucial process is captured by CCD Camera. The captured image is compressed by neural network and JPEG, and it is sent directly to the assembly plant for incoming inspection. Massive image data require broadband channel to transmit them to remote distance, but sender is able to transmit them to receiver in use common channel by compressing massive image data in the high ratio. After the receiver reconstructs the compressed image to be transmitted, the reconstructed image is also directly used for automatic inspection of the process. The Experimental results show that the proposed inspection mechanism could be effectively implemented for real applications.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.433-439
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• 2007

A ubiquitous environment in construction requires integrating hardware and software systems. Currently the Construction System Integration Lab (CSIL) at Pusan National University is currently studying the application of ubiquitous technology for better communication in the construction process. In this paper, a pilot of Ubiquitous Concrete Pour System (u-CPS) has been presented to demonstrate the effectiveness of data exchange in the concrete pour process. The u-CPS environment takes advantage of the RFID technology for collecting construction data. The pilot can automatically generate the data for concrete pour work such as departure time, arrival time, concrete pour time. Construction managers can keep track of the progress of concrete pour work using the information. A case study was done for a building construction using the pilot system, the result of which demonstrated that the RFID-base system can help improve the effectiveness of data communication during the concrete pour process.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.22-28
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• 2021

Multivariate processes, such as chemical and mechanical process, power plants are operated in a state where several facilities are complexly connected, the fault of a particular system can also have fatal consequences for the entire process. In addition, since process data is measured in an unstable environment, outlier is likely to be include in the data. Therefore, monitoring technology is essential, which can remove outlier from measured data and detect failures in advance. In this paper, data obtained from dynamic and multivariate process models was used to detect fault in various type of processes. The dynamic process is a simulation of a process with autoregressive property, and the multivariate process is a model that describes a situation when a specific sensor fault. Mahalanobis distance was used to remove outlier contained in the data generated by dynamic process model and multivariate process model, and fault detection was performed using ICA. For comparison, we compared performance with and a conventional single ICA method. The proposed fault detection method improves performance by 0.84%p for bias data and 6.82%p for drift data in the dynamic process. In the case of the multivariate process, the performance was improves by 3.78%p, therefore, the proposed method showed better fault detection performance.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.85-92
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• 2019

In this paper, we extract the quantitative relation data of activities from the workflow event log file recorded in the XES standard format and connect them to rediscover the workflow process model. Extract the workflow process patterns and proportions with the rediscovered model. There are four types of control-flow elements that should be used to extract workflow process patterns and portions with log files: linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative routing patterns. In this paper, we focus on four of the factors, disjunctive routing, and conjunctive path. A framework implemented by the authors' research group extracts and arranges the activity data from the log and converts the iteration of duplicate relationships into a quantitative value. Also, for accurate analysis, a parallel process is recorded in the log file based on execution time, and algorithms for finding and eliminating information distortion are designed and implemented. With these refined data, we rediscover the workflow process model following the relationship between the activities. This series of experiments are conducted using the Large Bank Transaction Process Model provided by 4TU and visualizes the experiment process and results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2164-2168
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• 2003

Real time control system such as in factory automation fields, defense field, aerospace, railway industries, financial trading and so forth, includes multiple computers on multiple nodes, and share data to process various actions and functions. This is similar to multitasking in a multiprocessor computer system. The task processing efficiency of such system is proportionally increased by process speed of each process computer. And also it is greatly influenced by communication latencies of each node. To provide proper operation of such real time system, a network that can guarantee deterministic exchange of certain amount of data within a limited time is required. Such network is called as a real time network. As for modern distributed control system, the timeliness of data exchange gives important factor for the dynamics of entire control system. In a real time network system, exchanged data are determined by off-line design process to provide the timeliness of data. In other word, designer of network makes up a network data table that describes the specification of data exchanged between control equipments. And by this off-line design result, the network data are exchanged by predetermined schedule. First, this paper explains international standard real time network TCN (Train Communication Network) applied to the KHST (Korean High Speed Train) project. And then it explains the computer program developed for design tool of network data table of TCN.

• International Journal of Contents
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• v.13 no.2
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• pp.21-28
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• 2017

Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.