• KIEAE Journal
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• v.16 no.6
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• pp.129-134
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• 2016

Today, natural ventilation systems are widely applied in multi-family housing. However, studies using the wind data trend line of the blower door test are insufficient. Purpose: Through this study, we will propose a computational method about ventilation performance of natural ventilation systems by conducting blower door test. Method: First, we sealed the gaps between the main systems including the natural ventilation system and conducted the blower door test. Next, the natural ventilation system was opened, the blower door test was conducted, and the difference in air flow rate between when closed and when opened was checked. Blower door test was carried out with a pressure difference of 50 Pa. Result: Therefore, the ventilation performance of the natural ventilation system was checked by drawing a trend line using the data to calculate the air flow rate at 2 Pa of the natural ventilation equipment standard pressure difference.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.871-877
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• 2012

An error analysis of PPP (Precise Point Positioning) using IF (Ionosphere Free) combination is given in this paper. It is shown that the performance of the ordinary model with positions, clock bias, integer ambiguities and ionosphere delay as unknowns is equivalent to that of an ionosphere difference combination where ionosphere delay is cancelled out. Furthermore, it is shown that IF combination is an ionosphere difference combination but not unique. It is also proved that all difference models show same performances. The error analysis evaluated with a hardware simulator and real measurements show that the ionosphere delay is effectively eliminated by IF combination or equivalently by the ionosphere difference combination. However, if bias errors such as troposphere, clock bias or multipath are included in the measurements, the performance of the IF combination is degraded because the bias errors are amplified by the ionosphere difference operation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.5-7
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• 1996

We propose a triangulation method based on stereo vision angles. We setup stereo vision systems which extract the depth information to a moving object by detecting a moving object using difference image method and obtaining the depth information by the triangulation method based on stereo vision angles. The feature point of a moving object is used the geometrical center of the moving object, and the proposed vision system has the accuracy of 0.2mm in the range of 400mm.

• Journal of the Korean Mathematical Society
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• v.53 no.5
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• pp.1115-1131
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• 2016

In this paper we develop useful relations which estimate the difference between the solutions of nonlinear impulsive differential systems with different initial values. Then we obtain the converse h-stability theorem of Massera's type for the nonlinear impulsive systems by employing the $t_{\infty}$-similarity of the associated impulsive variational systems and relations.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.05a
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• pp.185-193
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• 2000

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.67
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• pp.11-18
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• 2001

The efficiency and robustness of the scale estimator based on the Gini's mean difference are well known in Nam et al.(2000). In this paper we propose use of robust control limits based on the Gini's mean difference for the control of the process deviation. To compare the performances of the proposed control chart with the existing R-chart or S-chart, some Monte Carlo simulations are performed. The simulation results show that the use of the Gini's mean difference in construction of the control limits has good performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.122-128
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• 1998

This paper presents compression of image sequences based on the classification of interframe difference image blocks. classification process consists of image activity classification and energy distribution classification. In the activity classification, interframe difference image blocks are classified into activity blocks and non-activity blocks using the edge detection. In the distribution classification, activity blocks are further classified into vertical blocks, horizontal blocks, and small activity blocks using the AC energy distribution features. The RBFN, trained with numerical classification results, successfully classifies difference image blocks according to image details. Image sequence compressing based on the classification of interframe difference image blocks using the RBFN shows better compression results and less training time than the classical sorting method and the MLP network.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.42-47
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• 2011

Small hydropower resources for five major river systems have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for small hydropower(SHP) plants is established. Monthly inflow data measured at Andong dam were analyzed. The predicted results from the developed models in this study show that the data were in good agreement with measured results of long term inflow at Andong dam. It was found that the models developed in this study can be used to predict the available potential and technical potential of SHP sites effectively. Based on the models developed in this study, the hydrologic performance for small hydropower sites located in river systems have been analyzed. The results show that the hydrologic performance characteristics of SHP sites had some difference between the river systems. Especially, the specific design flow and specific output of SHP sites located on North Han river and Nakdong river systems had large difference compared with other river systems.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.621-628
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• 1997

This study aimed to quantify the impact of crossbreeding at farm level, in mixed farm systems in Gujarat. Households with crossbred cattle did not differ from households without crossbreds in terms of farm resources, crop gross margins and off-farm income. The use of crossbred animals did increase livestock gross margins by 64% and household income by 22%. The three agro-ecological zones included in this study differed considerably according to farm system and household income. However, in all three zones, households with crossbreds had higher livestock gross margins than households without crossbreds. There was no real difference in work load and labour division between households with and without crossbreds. There was also no difference in the use of bullocks for draught purposes between the two types of households. In particular buffaloes are being replaced by crossbred cattle. There was a large variation in farm income, largely because of land area. The milk offake per average cow and the number of buffaloes also related positively to farm income in both types of households. Crossbreeding has proved technically and financially viable in different Gujarat mixed farming systems. It can be concluded that crossbreeding is an important development option for landless farmers.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.447-454
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• 2010

This paper presents multiple fuzzy prediction systems based on an Interval type-2 TSK fuzzy Logic System so that the uncertainty and the hidden characteristics of nonlinear data can be reflected more effectively to improve prediction quality. In proposed method, multiple fuzzy systems are adopted to handle the nonlinear characteristics of data, and each of multiple system is constructed by using interval type-2 TSK fuzzy logic because it can deal with the uncertainty and the characteristics of data better than type-1 TSK fuzzy logic and other methods. For input of each system, the first-order difference transformation method are used because the difference data generated from it can provide more stable statistical information to each system than the original data. Finally, computer simulations are performed to show the effectiveness of the proposed method for two typical time series examples.