• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.10
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• pp.7-16
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• 2007

In this paper, we introduce a new design environment for efficient multiprocessor system-on-chip design space exploration. The design environment takes a process network model as input system specification. The process network model has been widely used for modeling signal processing applications because of its excellent modeling power. However, it has limitation in predictability, which could cause severe problem for real time systems. This paper proposes a new approach that enables static analysis of a process network model by converting it to a hierarchical synchronous dataflow model. For efficient design space exploration in the early design step, mapping application to target architectures has been a crucial part for finding better solution. In this paper, we propose an efficient mapping algorithm. Our mapping algorithm supports both single bus architecture and multiple bus architecture. In the experiments, we show that the automatic conversion approach of the process network model for static analysis is performed successfully for several signal processing applications, and show the effectiveness of our mapping algorithm by comparing it with previous approaches.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.95-101
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• 2008

Modeling of stock prices forecast has been considered as one of the most difficult problem to develop accurately since stock prices are highly correlated with various environmental conditions including economics and political situation. In this paper, we propose a agent system approach to predict Korea Composite Stock Price Index (KOSPI) using neural network and statistical methods. To minimize mean of prediction error and variation of prediction error, agent system includes sub-agent modules for feature extraction, variables selection, forecast engine selection, and forecasting results analysis. As a first step to develop agent system for KOSPI forecasting, twelve economic indices are selected from twenty two basic standard economic indices using principal component analysis. From selected twelve economic indices, prediction model input variables are chosen again using best-subsets regression method. Two different types data are tested for KOSPI forecasting and the Prediction results showed 11.92 points of root mean squared error for consecutive thirty days of prediction. Also, it is shown that proposed agent system approach for KOSPI forecast is effective since required types and numbers of prediction variables are time-varying, so adaptable selection of modeling inputs and prediction engine are essential for reliable and accurate forecast model.

• Journal of Korea Water Resources Association
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• v.48 no.6
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• pp.425-438
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• 2015

The objective of this study was to evaluate simulation of agricultural water supply considering yearly variation of irrigation efficiency. The water supply data of the Idong reservoir from 2001 through 2009 was collected and used for this study. Total 6 parameters including irrigation efficiency (Es), drainage outlet height, and infiltration, were used for sensitivity analysis, calibration, and validation. Among the parameters, the Es appeared to be the most sensitivity parameter. The Es was calibrated on a yearly basis considering sensitivity and time-varying characteristic, while other parameters were set to fixed values. The statistics of percent bias (PBLAS), Nash-Sutcliffe efficiency (NSE), and root means square error to the standard deviation of measured data (RSR) for a monthly step were 2.7%, 0.93, and 0.26 for the calibration, and 3.9%, 0.89, and 0.32 for the validation, correspondently. The results showed a good agreement with the observations. This implies that the modeling only with appropriate parameter values, apart from modeling approaches, can simulate the real supply operation reasonably well. However, the simulations with uncalibrated parameters from previous studies produced poor results. Thus, it is important to use calibrated values, and especially, we suggest the Es's yearly calibration for simulating agricultural water supply.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.7-17
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• 2009

The development of wireless communication MAC layer is usually released as SoC which is a combination in hardware and software. In this system development environment, an environment for software development and verification is necessary because the hardware development takes a lot of time priori to completion. In integrated development of hardware and software, simulation environment of hardware and software provided by hardware modeling using HDL at RTL and ISS respectively. By increasing the development complexity of system, ESL design modeling systems at higher abstraction level than RTL has already prompted. The ESL design is divided untime model and time model. This paper present design and implementation of MCU for untime model simulation, not time model. Proposed MCU can optimize the system at early step of system development and move up the development completion time by verifying the system function easily and rapidly than part required exact time in untime model. In this paper, we present an MCU module based on SystemC and UC/OS-II Module providing real-time operate system.

• Korean Journal of Construction Engineering and Management
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• v.22 no.6
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• pp.3-14
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• 2021

In the Chinese construction industry, the utilization of Building Information Modeling (BIM) aims to increase the total output of the construction industry by solving the problem of inefficient interoperability in the construction industry. In 2011, the Chinese Ministry of Housing and Urban-Rural Development despite the technical advantages of BIM and the government policy, the BIM adoption rate in China is lower than 45%. Meanwhile, as the South Korean construction industry is a step ahead of its Chinese counterpart in introducing and utilizing BIM, it is expected that BIM is more actively utilized and accepted in South Korea than in China. According to a comparative study based on the hype-cycle theory, South Korea is at a more advanced stage of introducing BIM, than in China. This study aimed to suggest how to increase BIM utilization rates in China. To this end, this study comparatively analyzed factors affecting BIM acceptance between China and South Korea. For the comparative analysis of the BIM acceptance factors between China and South Korea, literature reviews on the technology acceptance model (TAM) and BIM acceptance model were carried out, and based on that, the BIM acceptance factors were classified. Other BIM acceptance factors were also added and considered, as they reflected Chinese national characteristics and construction industry. As for the derived BIM acceptance factors, construction project participants, especially actual BIM users in China and South Korea, were targeted for the survey. A t-test using SPSS 22.00 was carried out to identify significant differences in data. Finally, based on the t-test results, this study suggested ways of improving the BIM utilization rate in China. Based on the findings, this study is expected to contribute to activating BIM adoption in the Chinese construction industry and also to set a theoretical foundation for future studies on BIM utilization in the industry.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• Resources Recycling
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• v.31 no.6
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• pp.81-91
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• 2022

The use of lithium-ion batteries increases significantly with the rapid spread of electronic devices and electric vehicle and thereby an increase in the amount of waste batteries is expected in the near future. Therefore, studies are continuously being conducted to recover various resources of cathode active material (Ni, Co, Mn, Li) from waste battery. In order to recover the cathode active material, black mass is generally recovered from waste battery. The general process of recovering black mass is a waste battery collection - discharge - dismantling - crushing - classification process. This study focus on the crushing/classification process among the processes. Specifically, the particle size distribution of various samples at each crushing/classification step were evaluated, and the particle shape of each particle fraction was analyzed with a microscope and SEM (Scanning Electron Microscopy)-EDS(Energy Dispersive Spectrometer). As a result, among the black mass particle, fine particle less than 74 ㎛ was the mixture of cathode and anode active material which are properly liberated from the current metals. However, coarse particle larger than 100 ㎛ was present in a form in which the current metal and active material were combined. In addition, this study developed a PBM(Population Balance Model) system that can simulate two-species mixture sample with two different crushing properties. Using developed model, the breakage parameters of two species was derived and predictive performance of breakage distribution was verified.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.35-44
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• 2023

In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.1-12
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• 2014

Recently, the reenaction of place's memories that were considered sense of place based on its historical and structural characteristic were assumed important topics for recovering and making the park from industrial sites, such as factory, industrial complex, industrial city, labor residential development, landfill, etc., to the public all over the world. This research aimed to conduct some preliminary data for making the park's sense of place highly. So, after conducting the structural forms of sense of place for Seoul Forest and Seonyudo Park that were designed and built by considering its place memories actively, park planning and design implications that were considered its sense of place were suggested. The research results those were derived from the structural forms of sense of place for Seoul Forest and Seonyudo Park's are the following. First, the Structural Equation Modeling(SEM) on Seoul Forest and Seonyudo Park were determined that the natural-physical, artificial-physical, and experiential environmental factors' satisfaction of Seoul Forest and Seonyudo Park have an effect on forming the Sense of Place. In addition, the sense of place was affected by the willingness to visit. Second, according to its physical environment, the experiential factors, such as plays, exercises and etc., were more important relatively. Therefore, experiential factors should be considered significantly with physical factors to make the sense of place highly. Third, even the places were under similar category, the factors' and valuables' relative importance were changed. As the results of structural equation modeling said, specific valuables' related with each factors would be differentiated due to the places' characteristics. For example, the results were showed that natural-physical factor was more important than artificial-physical factor in Seoul Forest. On the other hand, artificial-physical factor was more important than the natural- physical factor. This research carries some significance for applying a quantitative research method(structural equation modeling) to various place to conduct the sense of place's structural model, for suggesting relative specific methods to make the sense of place, and for being a step forward to substance of sense of place. If further studies conduct focusing on various places to draw the forming models of sense of place that were based this research's analysis methods and results, those researches would contribute to make the urban place meaningful, characteristically and affectionately. Furthermore, those researches would contribute in making a humane and competitiveness city.