• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.391-394
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• 1996

The effects of time-sampling on nonlinear output regulation problem is investigated. Output regulatedness is preserved under time sampling as in linear systems, however output regulatability is not robust with respect to time-sampling, and thus one needs to seek an approximate nonlinear sampled-data output regulator.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.257-264
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• 2005

This paper suggests a heuristic algorithm for the clustering problem. Clustering involves grouping similar objects into a cluster. Clustering is used in a wide variety of fields including data mining, marketing, and biology. Until now there are a lot of approaches using Self-Organizing Feature Maps(SOFMs). But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of k output-layer nodes, if they want to make k clusters. This approach has problems to classify elaboratively. This paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We can find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. We use the well known IRIS data as an experimental data. Unsupervised clustering of IRIS data typically results in 15 - 17 clustering error. However, the proposed algorithm has only six clustering errors.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.41-51
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• 2006

Clustering is to group similar objects into clusters. Until now there are a lot of approaches using Self-Organizing feature Maps (SOFMS) But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of c output-layer nodes, if they want to make c clusters. This approach has problems to classify elaboratively. This Paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We un find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. The proposed algorithm was tested on well-known IRIS data and TSPLIB. The results of this computational study demonstrate the superiority of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1726-1729
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• 1997

In general, the solvability of linear robust output regulation problem are not preserved under time-sampling. Thus, it is found that the digital regulator implemented by itme-sampling of anlog output regulator designed based on the continuous-time linear system model is nothing but a 1st order approximation with respect to time-sampling. By the way, one can design an improved sampled-data regulator with respect to sampling time by utilizing the intrinsic structure of the system. In this paper, we study the system structures which it is possible to design an improved sampled-data regulator with respect to sampling time.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.65-73
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• 1997

The effects of time-sampling on linear output regulation problem is ivestigated. It is found that the solvability of linear output regulation problem is generally not robust with respect to time-sampling although the solvability of that for single inut and single output linear systems and the solvability of linear robust output regulation problem are preserved under time-sampling. The resutls imply that one needs to seek a better approximate sampled-data output regulator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.129-134
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• 1997

The purpose of this study is to estimate the distribution rate of R&D input on R&D output in major manufacturing industrial sector. The distribution rate is estimated on time-series data for the period 1980 to 1996. The data used in this study can be divided into the two categories. 1) R&D output data (Patent, Utility) 2) R&D input data (R&D expenditure, R&D workers) The raw data of R&D expenditure is transformed into R&D stock. And the specific production function is used to represent the interaction between R&D input and output. The production function shows the maximum rate of R&D output that can be achieved by certain given, technologically possible, R&D input combinations. The main findings can be summarized as follows. 1) There was a diminishing return between R&D input and output$(\alpha+\beta<1). 2) R&D output growth was more affected by R&D expenditures than R&D workers. 3) R&D workers were more contributed highly to Patent granted than Utility model.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.680-684
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• 2005

This paper presents a data-based stability analysis of a MIMO linear time-invariant discrete-time system, as an extension of the previous results for a SISO system. In the MIMO case, a similar discussion as in the case of a SISO system is also applied, except that an augmented input and output space is considered whose dimension is determined in relation to both the orders of the input and output vectors and the numbers of inputs and outputs. As certain subspaces of the input and output space, both output data space and closed-loop data space are defined, which contain all the behaviors of a system, respectively, with zero input in open-loop and with a control input in closed-loop. Then, we can derive the data-based stability conditions, in which the open-loop stability can be checked by using a data matrix whose column vectors span the output data space and the closed-loop stability can also be checked by using a data matrix whose column vectors span the closed-loop data space.

• Korean Journal of Organic Agriculture
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• v.26 no.4
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• pp.619-628
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• 2018

This study analyze the economic effect of chemical fertilizer. We used the input and output data, and the analysis variables include production output nitrogen, phosphoric acid, potassium, seeds, and labor. The main results are as follows. First, for spring potatoes, potassium increases to a certain level of output, but over a certain stage, the output decreases as the input increases. Optimal use of potassium in the calculation of spring potatoes can achieve the effect of reducing input costs and increasing output simultaneously. Second, radish In autumn, nitrogen increases to a certain level, but over a certain stage it represents a reverse U-shaped relationship in which output decreases as input increases. This means that reducing the amount of fertilizer input increases the output. This means that soil-related agricultural big data can contribute to the management of nutrients and greenhouse gas reduction in agricultural land.

• Journal of Technology Innovation
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• v.7 no.1
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• pp.176-186
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• 1999

This paper starts out by reviewing the literature that in different ways utilizes patent data as an output of Research ＆ Development (R&D) investment. The main focus, however, is an analysis of time-lag between industrial R&D input and its output. To achieve this research's purpose, the basic data associated with the industrial R&D input (expenditure, researchers) and output (applied patent and utilities) for the past 15 years, from 1980 to 1994, in the areas of electrical-electronic, mechanical and chemical industries have been collected. And the raw input data were altered into real flow data (but stock data) using Laspeyres approach and analyzed using multiple regression analysis, especially stepwise regression analysis. The result of this study can be summarized as follows: a) The time-lag; between industrial R&D input and its output is within 1 to 3 years. b) The time-lag: of patents was longer than that of utility models. c) The time-lag: in electrical-electronic, chemical industry was longer than that of the mechanical industry.

• Progress in Superconductivity
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• v.5 no.1
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• pp.17-20
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• 2003

We have designed and measured a SFQ(Single Flux Quantum) DFFC and an Inverter(NOT) for superconducting ALU(Arithmetic Logic Unit) development. To optimize the circuit, we used Julia, XIC, and L meter for circuit simulations and circuit layouts. The Inverter was consisted of a D Flip-Flop, a data input, a clock input and a data output. If a data pulse arrives at the inverter, then the output reads ‘0’ (no output pulse is produced) at the next clock period. If there is no input data pulse, it reads out ‘1’(output pulse is produced). The DFFC was consisted of a D flip-Flop, an Inverter, a Data in, a Clock in and two outputs. If a data pulse arrives at the DFFC circuit, then the output2 reads ‘1’ at the next clock period, otherwise it reads out ‘1’ to output1. Operation of the fabricated chip was performed at the liquid helium temperature and at the frequencies of 1KHz.