• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.368-368
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• 2022

The Soil and Water Assessment Tool (SWAT) has been widely used to simulate the long-term hydrological conditions of a catchment. Two output variables, outflow and sediment yield have been widely investigated in the field of water resources management, especially in determining the conditions of ungauged subbasins. The presence of missing data in weather input data can cause poor representation of the climate conditions in a catchment especially for large or mountainous catchments. Therefore, in this study, a custom module was developed and evaluated to determine the efficiency of utilizing basic spatial interpolation methods in the estimation of weather input data. The module has been written in Python language and can be considered as a pre-processing module prior to using the SWAT model. The results of this study suggests that the utilization of the proposed pre-processing module can improve the simulation results for both outflow and sediment yield in a catchment, even in the presence of missing data.

• 한국산업보건학회지
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• 제32권3호
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• pp.231-241
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• 2022

Objectives: The purpose of this study is to evaluate the input status of exposure-related information in the working environment monitoring database (WEMD) and special health examination database (SHED) for the construction of a national exposure surveillance system. Methods: The industrial and process code input status of WEMD and SHED for 21 carcinogens from 2014 to 2016 was compared. Data from workers who performed both work environment monitoring and special health examinations in 2019 and 2020 were extracted and the actual status of input of industrial and process codes was analyzed. We also investigated the cause of input errors through a focus group interview with 12 data input specialists. Results: As a result of analyzing WMED and SHED for 21 carcinogens, the five-digit industrial code matching rate was low at 53.5% and the process code matching rate was 19% or less. Among the data that simultaneously conducted work environment monitoring and special health examination in 2019 and 2020, the process code matching rate was very low at 18.1% and 5.2%, respectively. The main causes of exposure-related data input errors were the difference between the WEMD and SHED process code input systems from 2020, the number of standard process and job codes being too large, and the inefficiency of the standard code search system. Conclusions: In order to use WEMD and SHED as a national surveillance system, it is necessary to simplify the number of standard code input codes and improve the search system efficiency.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(2)
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• pp.101-104
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• 2002

This paper propose that is algorithm of power dissipation reduction in the high level synthesis design for DSP(Digital Signal Processor), as the portable terminal system recently demand high power dissipation. This paper obtain effect of power dissipation reduction and switching activity that increase correlation of operands as input data of function unit. The algorithm search loop or repeatedly data to the input operands of function unit. That can be reduce the power dissipation using the new low power high level synthesis algorithm. In this Paper, scheduling operation search same nodes from input DFG(Data Flow Graph) with correlation coefficient of first input node and among nodes. Function units consist a multiplier, an adder and a register. The power estimation method is added switching activity for each bits of nodes. The power estimation have good efficient using proposed algorithm. This paper result obtain more Power reduction of fifty percents after using a new low power algorithm in a function unit as multiplier.

• 사물인터넷융복합논문지
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• 제9권2호
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• pp.71-76
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• 2023

본 논문에서는 단일 수신기가 사용되는 환경에서 정확한 거리 추정을 위해 심층 인공신경망 (Deep Neural Network, DNN)을 활용한 Smoothed Received Signal Strength Indicator (RSSI) 기반 거리 추정 기법을 제안한다. 제안 기법은 거리 추정 정확도 향상을 위해 Data Splitting, 결측치 대치, Smoothing 단계로 구성된 전처리 과정을 수행하여 Smoothed RSSI 값을 도출한다. 도출된 다수의 Smoothed RSSI 값은 Multi-Input Single-Output(MISO) DNN 모델의 Input Data로 사용되며 Input Layer와 Hidden Layer를 통과하여 최종적으로 Output Layer에서 추정 거리로 반환된다. 제안 기법의 우수성을 입증하기 위해 제안 기법과 선형회귀 기반 거리 추정 기법의 성능을 비교하였다. 실험 결과, 제안 기법이 선형회귀 기반 거리 추정 기법 대비 29.09% 더 높은 거리 추정 정확도를 보였다.

• 한국정보통신학회논문지
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• 제24권5호
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• pp.600-608
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• 2020

머신러닝은 학습 데이터로부터 목적함수를 구성하고, 테스트 데이터를 통해 목적함수의 확인함으로써 발생하는 데이터에 대한 예측을 수행한다. 머신러닝에서 입력데이터는 전처리 과정을 통해 정규화 과정을 거친다. 이런 정규화는 입력데이터의 평균과 표준편차를 이용하여 표준화하거나, 수치 데이터가 아닌 nominal value는 one-hot 코드 형태로 변환하는 방식을 이용한다. 그러나 이 전처리 과정만으로 문제를 해결할 수 없다. 이러한 이유로 본 논문에서 입력데이터의 정규화를 위해 온톨로지를 이용하는 방법을 제안한다. 이를 위한 테스트 데이터는 모바일 기기로부터 수집된 와이파이 장치의 RSSI값을 이용하고, 수집된 데이터의 노이즈와 이질적 문제는 온톨로지를 이용하여 정제하는 방법을 제시한다.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.433-443
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• 2003

In this study, we provide a comparison of multivariate Q-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus well known to those who study statistics. We can analyze data through the direct Input method(command) in SAS and use of menu method in SPSS, Minitab and S-plus. The analysis performance method is chosen by the high frequency of use. Widely we compare with each Q-techniques form according to input data, input option, statistical chart and statistical output.

• 대한의용생체공학회:의공학회지
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• 제12권3호
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• pp.191-202
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• 1991

This paper describes ECG data compression algorithm using neural network. As a learning method, we use back error propagation algorithm. ECG data compression is performed using learning ability of neural network. CSE database, which is sampled 12bit digitized at 500samp1e/sec, is selected as a input signal. In order to reduce unit number of input layer, we modify sampling ratio 250samples/sec in QRS complex, 125samples/sec in P & T wave respectively. hs a input pattern of neural network, from 35 points backward to 45 points forward sample Points of R peak are used.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1996년도 추계학술대회논문집
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• pp.181-184
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• 1996

Fuzzy hierarchical analysis(FHA) has the usefulness to allow decision maker's ambiguities when comparing two alternatives. But, for easiuly appling it to a decision problem, the handling its many data and for decision makers much not knowing fuzzy theory are the obstacles to must be overcomed even if the results of final fuzzy weights can be computed by a personal computer. This paper decribes that FHA is revised, and input/output interfaces are developed to collect input data easily and interprete the fuzzy resultlts. Finally, a fuzzy decision process is suggested with them.

• 전자공학회논문지S
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• 제34S권12호
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• pp.30-40
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• 1997

This paper presents a design method of fuzzy control systems by clustering the data in the subspace of the input-output produyct space. In the case of servo control, most input-outputdata are concentrated in thye steady-state region, and the the clustering will result in only steady-state fuzzy rules. To overcome this problem, we divide the input-output product space into some subspaces according to the state of input variables. The fuzzy control system designed by the subspace clustering showed good transient response and smaller steady-state error, which is comparable with the reference fuzzy system.