• 한국통신학회논문지
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• 제28권1A호
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• pp.47-53
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• 2003

본 논문에서는 155 Mb/s급 멀티플렉서-디멀티플렉서를 단일소자로 설계하였다. 이 소자는 초고속 전송망의 전송노드 역할을 하는 2.5 Gb/s SDH 전송시스템에 적용되어 51 Mb/s의 병렬 데이터들을 155 Mb/s의 직렬 데이터로 다중화 하거나 155 Mb/s 직렬 데이터들을 51 Mb/s의 병렬 데이터로 역 다중화 하는 기능을 수행한다 소자의 저속부는 TTL로 접속되고 고속부는 100K ECL로 접속되며 0.7${\mu}m$BiCMOS gate array로 제작되었다 설계 제작된 소자는 180˚의 155 Mb/s 데이터 입력 phase margin을 가지며 출력 데이터 skew는 470ps, 소비전력은 2.0W 이하의 특성을 보인다.

• 동아시아경상학회지
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• 제9권1호
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• pp.41-51
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• 2021

Purpose - The purpose of this study is to propose strategies of improving efficiency of 20 listed port companies in China based on analysis of their input-output indexes from 2014 to 2018. Research design, data, and methodology - In this paper, the relevant input-output indicators of 20 listed port companies in China from 2014 to 2018 were adopted. Data derived from the company annual reports announced by Shanghai stock exchange and Shenzhen stock exchange. Comprehensive efficiency and pure technical efficiency were measured from output perspective by DEA and Malmquist index, and efficiency changes and regional efficiency were analyzed. Result - The results showed that the efficiency value of 20 listed port companies in China fluctuated and increased during 2014-2018, regional efficiency was unbalanced, and change of MPI was influenced by internal factors and external factors. Listed port companies affected by internal and external factors needed to make appropriate response to internal and external factors. Conclusion - The research conclusion can provide important reference information about management and planning for port companies in China and related areas. However, this paper is limited to the availability of data. So the improvement scheme for listed companies in inefficient regional ports needs further study, such as using AHP method.

• 대한산업공학회지
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• 제40권1호
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• pp.84-99
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• 2014

In this study, determinant input-output variables are identified for calculating Data Envelopment Analysis (DEA) efficiency scores relating to evaluating the efficiency of government-sponsored research and development (R&D) projects. In particular, this study proposes a systematic framework of design and analysis of experiments, called "all possible DEAs", for pinpointing DEA determinant input-output variables. In addition to correlation analyses, two modified measures of time series analysis are developed in order to check the similarities between a DEA complete data structure (CDS) versus the rest of incomplete data structures (IDSs). In this empirical analysis, a few DEA determinant input-output variables are found to be associated with a typical public R&D performance evaluation logic model, especially oriented to a mid- and long-term performance perspective. Among four variables, only two determinants are identified : "R&D manpower" ($x_2$) and "Sales revenue" ($y_1$). However, it should be pointed out that the input variable "R&D funds" ($x_1$) is insignificant for calculating DEA efficiency score even if it is a critical input for measuring efficiency of a government-sonsored R&D project from a practical point of view a priori. In this context, if practitioners' top priority is to see the efficiency between "R&D funds" ($x_1$) and "Sales revenue" ($y_1$), the DEA efficiency score cannot properly meet their expectations. Therefore, meticulous attention is required when using the DEA application for public R&D performance evaluation, considering that discrepancies can occur between practitioners' expectations and DEA efficiency scores.

• 산업경영시스템학회지
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• 제45권3호
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• pp.57-65
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• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• 대한산업공학회지
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• 제23권4호
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• 한국정보통신학회논문지
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• 제14권3호
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• pp.559-564
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• 2010

복잡한 비선형 시스템을 예측하기 위하여 GMDH(Group Method of Data Handling) 알고리듬을 사용할 수 있다. 기존의 GMDH 알고리듬은 정해진 절차에 의해 입력층부터 중간층들을 거쳐 출력층에서 시스템의 예측 출력을 생성한다. 각 층의 출력은 전 층의 출력에 의해서만 생성된다. 그러나 전형적인 GMDH 알고리듬에서 층별로 최적의 구조가 결정되지만 전체적으로는 최적의 구조가 결정되지 않을 수도 있다는 문제점을 해결하기 위해 예측된 출력을 실제의 출력과 비교하여 그 에러를 피드백하여 전체적으로 최적의 구조를 가지는 GMDH 예측 모델을 구성함으로 써 보다 정확한 예측이 가능하도록 하였다. 제안된 알고리듬이 기존의 알고리듬보다 성능이 향상된 것을 컴퓨터 시뮬레이션을 통해 검증하였다.

• 물과 미래
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• 제28권1호
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• pp.81-90
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• 1995

본 연구에서는 장기간의 수문기상자료를 보유하고 있으나 유출량자료의 관측년한이 짧은 유역에서 장기간의 월유출량자료를 확장하고 예측할 수 있는 추계학적 시스템 모형을 개발하고자 한다. 그 방법으로 주기성과 경향성을 갖는 월유출량, 월강수량 및 윌증발량자료를 시계열 분석하여 seasonal ARIMA 형태의 단변량 모형을 유도하는 한편, 각 계열간의 교차상관분석으로부터 월강수량 및 윌증발량을 입력변수로 하고 월유출량을 출력변수로 하는 다중 입력-단일 출력관계의 설명모형을 유도하여 단변량 시계열모형과 비교 검토하였다. 본 연구의 결과 월유출량자료의 확장과 예측에 있어서 다중 입출력모형의 정확성과 적용가능성이 매우 높은 것으로 판단되었다.

• 산경연구논집
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• 제8권5호
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• pp.7-13
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• 2017

Purpose - The purpose of this paper is to analyze the relationship between the real exchange rate and the output, which is based on the macroeconomic equilibrium theory in China. Its aim will be to verify whether the change in the real exchange rate has a significant effect on the output or not. Research design, data, and methodology - This study endeavors tries to investigate the correlation among economic variables under the macroeconomic market (the commodity market and the money market) equilibrium. So, time-series data from 1990 to 2016 is applied to establish a vector auto-regression (VAR) model so as to perform an empirical analysis. Results - The empirical results reveal that an increase in the real exchange rate will result in an increase in the output in the short run. However, the empirical results also indicate that this kind of mechanism cannot work in the long run. Conclusions - The effect of a decrease of real exchange rate on output is significant in the short run. Also, this paper suggests that the total supply and the total demand can promote economic growth. The fiscal and money policy play a significant role in economic growth in China as well.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2216-2218
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• 2002

A system identification is to measure the output in the presence of a adequate input for the controlled system and to estimate the mathematical model in the basic of input output data. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input-output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input-output case with the observed noise. In recent the adjusted least squares method is suggested as a consistent estimation method in the system identification not with the observed noise input but with the observed noise output. In this paper we have developed the adjusted least squares method from the least squares method and have made certain of the efficiency in comparing the estimating results with the generating data by the computer simulations.

• Journal of Radiation Protection and Research
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• 제41권4호
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• pp.373-377
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• 2016

Background: Experiments with small electrochemical apparatus were previously carried out for detecting low-energy neutrinos under irradiation of reactor neutrinos and under natural neutrino environment. The experimental result indicated that the output current of reactor-neutrino irradiated detector was appreciably larger than that of natural environmental one. Usual interaction cross-sections of neutrinos are quite small, so that they do not explain the experimental result at all. Materials and Methods: To understand the experimental data, we propose that some biological products may generate AV-type scalar field B0, leading to a large interaction cross-section. The output current generation is ascribed to an electrochemical process that may be assisted by weak interaction phenomena. Dissolved oxygen concentrations in the detector solution were measured in this study, for the purpose of understanding the mechanism of the detector output current generation. Results and Discussion: It was found that the time evolution of experimental output current was mostly reproduced in simulation calculation on the basis of the measured dissolved oxygen concentration. Conclusion: We mostly explained the variation of experimental data by using the electrochemical half-cell analysis model based on the DO concentration that is consistent to the experiment.