• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.4
• /
• pp.395-401
• /
• 1999

In this paper, a temperature controller for a semiconductor test handler is proposed. First, a handware system for identification and control is established using RTD sensors, an A/D converter, solid state relays, a heater, and a computer system. Second, using ARMAX model and least square method, a chamber model for the design of a controller is identified through experiments. The identified model is verified to describe the real plant very well in the sense that it shows very similar input-output responses to those of the real system. With the identified model an LQG controller is designed. Frequency response of the designed controller shows that it has 15 dB of gainmargin and (-50˚, +50˚) of phase margin. Experiment with a real test handler demonstrates a good performance in the sense that its overshoot and steady state error are smaller and response time is faster, compared with those of a conventional PID controller.

• Geomechanics and Engineering
• /
• v.13 no.6
• /
• pp.997-1010
• /
• 2017

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

• Journal of Multimedia Information System
• /
• v.9 no.1
• /
• pp.1-10
• /
• 2022

China is a big country in animal fur industry. The total production and consumption of fur are increasing year by year. However, the recognition of fur in the fur production process still mainly relies on the visual identification of skilled workers, and the stability and consistency of products cannot be guaranteed. In response to this problem, this paper proposes a feature fusion-based animal fur recognition network on the basis of typical convolutional neural network structure, relying on rapidly developing deep learning techniques. This network superimposes texture feature - the most prominent feature of fur image - into the channel dimension of input image. The output feature map of the first layer convolution is inverted to obtain the inverted feature map and concat it into the original output feature map, then Leaky ReLU is used for activation, which makes full use of the texture information of fur image and the inverted feature information. Experimental results show that the algorithm improves the recognition accuracy by 9.08% on Fur_Recognition dataset and 6.41% on CIFAR-10 dataset. The algorithm in this paper can change the current situation that fur recognition relies on manual visual method to classify, and can lay foundation for improving the efficiency of fur production technology.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.145-152
• /
• 2022

Recently, interest in the precast concrete (PC) construction method has been increasing. The PC construction process consists of i) design, ii) production, iii) transportation, and iv) installation. A PC field manager at the site submits a shipment request form to the factory one to three days before the installation of the PC component. Numerous matters should be considered in writing a shipment request form. Incorrect shipment request forms may cause standby resources, waste of resources, premature work conclusion, or excessive work. These issues can lead to an increase in construction costs, replanning of PC component installation, or rework. In order to prevent such problems, PC component installation should be simulated based on the shipment request form. Accordingly, this study aims to identify factors influencing the operability of shipment request forms for PC construction. To this end, this study derived factors influencing i) initiation of the activity, ii) addition or deletion of activities, and iii) an increase or decrease in the activity execution time. As a result, this study identified flow, the features of PC components, condition of PC components, unloading location, installation location, input equipment and labor, number of anchors, number of supports, weather, strike, and accident. Further studies should verify the factors derived in this study based on focus group interviews.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.11 no.5
• /
• pp.813-821
• /
• 2000

The engineering of satellite communication systems at frequencies above 10GHz requires a method for estimating rain-caused outage probabilities on the earth-satellite path. A procedure for predicting a rain attenuation distribution from a point rainfall rate distribution is, therefore, needed. In order to predict rain attenuation on the satellite link, several prediction models such as ITU-R, Global, SAM, DAH model, have been developed and used at a particular propagation condition, they may not be appropriate to a propagation condition in Korean territory. In this paper, a new rain attenuation prediction method appropriate to a propagation condition in Korea is introduced. Based on the results from ETRI measurements, a new method has been derived for an empirical approach with an identification on the horizontal correction factor as in current ITU-R method, and the vertical correction factor has been suggested with decreasing power law as a function of rainfall rate. This proposed model uses the entire rainfall rate distribution as input to the model, while the ITU-R and DAH model approaches only use a single 0.01% annual rainfall rate and assume that the attenuation at other probability levels can be determined from that single point distribution. This new model was compared with several world-wide prediction models. Based on the analysis, we can easily know the importance of the model choice to predict rain attenuation for a particular location in the radio communication system design.

• Journal of KIISE:Software and Applications
• /
• v.30 no.10
• /
• pp.904-911
• /
• 2003

In this paper, we propose an effective method for the distinction between machine-printed and handwritten Korean address images. It is important to know whether an input image is handwritten or machine-printed, because methods for handwritten image are quite different from those of machine-printed image in such applications as address reading, form processing, FAX routing, and so on. Our method consists of three blocks: valid connected components grouping, feature extraction, and classification. Features related to width and position of groups of valid connected components are used for the classification based on a neural network. The experiment done with live Korean address images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.85%.

• Korean Journal of Construction Engineering and Management
• /
• v.11 no.2
• /
• pp.25-34
• /
• 2010

The building construction projects include a variety of risk factors due to uncertainties. To succeed in the projects, it is important how risks are managed. Risk management is composed of identification, analysis and response. Especially, the risk analysis is important to objectively calculate significance of risk factors. This paper evaluates a method to find priorities of risks using the AHP(Analytic Hierarchy Process). The method has some defects; (1) the consistency becomes weak as the number of pair-wise compared risks is large, and (2) the input and output procedures are complex when risks are added to or removed from a risk database. Thus the paper adopts the PROMETHEE(Preference Ranking Organization METHod Enrichment Evaluations) analysis process which is able to overcome the limitation of the AHP restricted to 9 risk factors. The PROMETHEE makes the procedure of risk analysis simple, when the risk factors pull out and put in the risk database. The purpose of this study is to provide process of risk analysis to use the PROMETHEE.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.4
• /
• pp.41-55
• /
• 1995

In this paper, an optimal idenfication method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together wlth optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzzy-neural networks(FNNs) are tuned automatically using improved modified complex method and modified learning algorithm. For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activateti sluge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.

• Journal of Navigation and Port Research
• /
• v.32 no.3
• /
• pp.215-221
• /
• 2008

Dynamic characteristics of a structure, i.e., natural frequency and mode shape, have been widely using as an input data in the area of structural integrity or health monitoring which combined with the damage evaluation and structural system identification techniques. It is very difficult, however, to get those information by the conventional modal analysis method from large structures, such as the offshore structure or the long-span bridge, since the source of vibration is not available. In this paper, a method to obtain the frequencies and the mode shapes of a large span truss structure using only acceleration responses is studied. The calculation procedures to obtain acceleration responses and frequency response functions are provided utilizing a numerical model of the truss, and the process to extract natural frequencies and mode shapes from the modal analysis is cleary explained. The extracted mode shapes by proposed method are compared with those from eigenvalue analysis for the estimation of accuracy. The validity of the mode shapes is also demonstrated using an existing damage detection technique for the truss structure by simulated damage cases.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.3
• /
• pp.145-156
• /
• 2000

In this paper, we propose a new methodology which includes the optimal design procedure of Polynomial Neural Networks(PNN) structure for model identification of complex and nonlinear system. The proposed PNN algorithm is based on GMDA(Group Method of Data handling) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. In other words, the PNN uses high-order polynomial as extended type besides quadratic polynomial used in GMDH, and the number of input of its node in each layer depends on that of variables used in the polynomial. The design procedure to obtain an optimal model structure utilizing PNN algorithm is shown in each stage. The study is illustrated with the aid of pH neutralization process data besides representative time series data for gas furnace process used widely for performance comparison, and shows that the proposed PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and prediction capabilities of model is evaluated and also discussed.