• Journal of Digital Convergence
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• v.12 no.4
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• pp.277-283
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• 2014

Fuzzy modeling is generally using the given data and the fuzzy rules are established by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is presented by selection of the input variables, the number of space division and membership functions and in this paper the consequent part of the fuzzy rule is identified by polynomial functions in the form of linear inference and modified quadratic. Parameter identification in the premise part devides input space Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. In this paper, membership function of the premise part is dividing input space by using trapezoid-type membership function and by using gas furnace process which is widely used in nonlinear process we evaluate the performance.

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.997-1002
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• 2002

Traditional prediction models have been developed with a fixed equation form based on the limited number of data and parameters. If new data is quite different from original data, then the model should update not only its coefficients but also its equation form. However, artificial neural network (ANN) does not need a specific equation form. Instead of that, it needs enough input-output data. Also, it can continuously re-train the new data, so that it can conveniently adapt to new data. Therefore, the purpose of this paper is to develop the I-PreConS (Intelligent system for PREdiction of CONcrete Strength using ANN) that provides in-place strength information of the concrete to facilitate concrete form removal and scheduling for construction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12A
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• pp.1223-1228
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• 2006

Closed-form expressions for capacity bounds of multiuser diversity combined with maximum ratio transmission (MRT) and maximum ratio combining (MRC) at each link are presented under the assumption of independent and quasi-static flat multiple-input multiple-output (MIMO) Rayleigh fading channels. The analysis results precisely agree with the numerical verification results and clearly show the impact of MRT/MRC on multiuser diversity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1082-1086
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• 2008

Multiple-input multiple-output (MIMO) is an efficient technology to increase data rate in wireless networks due to bandwidth and power limitations. Data transmission rate between transmitter and receiver is determined by channel capacity. MIMO has an advantage of reliable communication over wireless channel because of utilizing the channel capacity properly. In this letter, we drive a new formula, closed form capacity formula, using confluent hypergeometric function.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.5
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• pp.387-392
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• 2017

There is a constant demand for hull variation related to ship design. Various input variables are generally given to achieve the objective functions assigned by each variation process. When dealing with geometric shapes accompanied by nonlinear operations during the variation process, vague relationships or uncertainties among input variables are commonly observed. Therefore, it is strongly recommended to identify those uncertainty factors in advance. A method to modify the shape of a closed hull form with a new area and a centroid had been introduced as a new process of hull variation. Since uncertainty between input variables still existed in the method, however, it was not easy for the user to enter the area and the corresponding centroid. To overcome this problem, a method is presented in this paper to provide the feasible region of centroids for a given area. By utilizing the concept and techniques used in the statistics such as the number of samples, probability, margin error, and level of confidence, this method generates the distribution of possible centroids along the regression curve. The result shows that the method helps the user to choose an appropriate input value following his or her design intention.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.85-94
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• 2018

The cultural industry is treated as the sunrise industry in modern society. It has taken an increasing role in promoting the economic growth. Due to this, this paper attempts to explore the dynamic relationship between cultural industry and the economic growth. On the grounds of Cobb-Douglas production function, the cultural industry is regarded as a determinant such as the labor input and the capital input to impact the economic growth. Meanwhile, the quarterly datum form 2000-Q1 to 2017-Q4 are employed to perform an empirical analysis via the vector error correction model. The GDP is treated as an independent variable. The input of capital, the input of labor and the total input of cultural industry are treated as dependent variables. Furthermore, a menu of statistical approaches such as the co-integration test and the impulse response function will be used to testify the dynamic relationship between cultural industry and economic growth. Via the Johansen co-integration test, the results report that the cultural industry has a obviously positive effect on economic growth. Through the vector error correction estimation, the results also report that the cultural industry also has a significantly positive effect on economic growth, but less than that of the Johansen co-integration test. This paper provides a view that the cultural industry is a kind of a determinant to promote the economic growth. Therefore, the China's government should pay much attention to the cultural industry construction.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Proceedings of the KIEE Conference
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• 1995.07c
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• pp.1317-1319
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• 1995

In this paper, we studied reduction characteristics of NOx gas produced from diesel engine combustion using by point-plane electrode. Here, input voltage forms were types of three [DC, AC, DC Positive pulse] and NOx gas of 1700ppm was composed of NO 1665ppm, $NO_2$ 35ppm on balance of $N_2$. We investigated NOx reduction characteristics as various of parameters, are gas flow rate, input voltage form and, humidity. From the results of study, reduction characteristics of NOx exhibited good when gas flow rate was small, input voltage was DC and much humidity were contained to NOx gas.