• Journal of computational fluids engineering
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• v.12 no.3
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• pp.62-68
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• 2007

A conceptual thermal design is performed for the optical payload system of a geostationary satellite. The optical payload considered in this paper is GOCI(Geostationary Ocean Color Imager) of COMS of Korea. The radiative thermal control system is employed in order to expect a small thermal gradient in the telescope structure of GOCl. Two design margins are applied to the dedicated radiator dimensioning, and three kinds of configuration to the heater power sizing. A Monte-Carlo ray tracing method and a network analysis method are utilized to calculate radiative couplings and thermal responses respectively. At the level of conceptual design, sizing thresholds are presented for the radiator and heater on the purpose of determining the mass and power budget of the spacecraft.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.886-888
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• 2013

An edge includes information of objects such as magnitude, orientation, and location. Conventional edge detection methods to detect those edge are methods using Sobel, Prewitt, Roberts, Laplacian operator. Existing methods use fixed weighted mask to detect edges, and their edge detection characteristics are insufficient. Therefore, to remedy weakness of conventional methods, in this paper, an edge detection algorithm using weight with standard deviation and thresholds is proposed.

• Journal of Korean Physical Therapy Science
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• v.2 no.2
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• pp.465-479
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• 1995

We randomly assigned 61 healthy subjects(male 14, female 47) to compare the experimental pain threshold and skin temperature between high mode TENS and burst mode TENS. In this study, 61 subjects were divided into three groups ; high mode TENS(n=20), burst mode TENS (n=20), and control group(n=21). Experimental pain thresholds and skin temperatures were measured before, immediately after cessation of stimulation, and at 30 minutes post stimulation. Stimulation was applied to the dorsal surface of the forearm(L14, LI10). Pain thresholds were measured by chronaxie meter. Skin temperature were measured by electrical digital thermometer. The results are as follows ; 1. There were no statistical difference in the pain threshold and skin temperature at before TENS stimulation among the three groups(p>0.05). 2. The pain threshold and skin temperature in burst mode TENS group was significantly higher and longer effect than that in high mode TENS group and control group(p<0.01). 3. The pain threshold in burst mode TENS group decreased to prestimulation levels by 30 minutes poststimulation. 4. The skin temperature in burst mode TENS group decreased to prestimulation levels by 20 minutes poststimulation. 5. The skin temperature was significantly difference among three group at immediately after, and at 30 minutes poststimulation and the skin temperature in burst mode TENS group was significantely higher than that in two groups(p<0.001). 6. The increasing rate of pain threshold in high mode TENS group after immediately cassation of stimulation was 24.3%(p<0.001). 7. The increasing rate of pain threshold in burst mode TENS group after immediately cessation of stimulation was 93.5% (p<0.001).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2156-2170
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• 2020

This paper presents a fire detection algorithm with a minimal false detection rate, intended for a thermal imaging surveillance environment, whose properties vary depending on temporal conditions of day or night and environmental changes. This algorithm was designed to minimize the false detection alarm rate while ensuring a high detection rate, as required in fire detection applications. It was necessary to reduce false fire detections due to non-flame elements occurring when existing fixed threshold-based fire detection methods were applied. To this end, adaptive flame thresholds that varied depending on the characteristics of input images, as well as the center of gravity of the heat-source and hot-source regions, were analyzed in an attempt to minimize such non-flame elements in the phase of selecting flame candidate blocks. Also, to remove any false detection elements caused by camera shaking, one of the most frequently raised issues at outdoor sites, preliminary decision thresholds were adaptively set to the motion pixel ratio of input images to maximize the accuracy of the preliminary decision. Finally, in addition to the preliminary decision results, the texture correlation and intensity of the flame candidate blocks were averaged for a specific period of time and tested for their conformity with the fire decision conditions before making the final decision. To verify the fire detection performance of the proposed algorithm, a total of ten test videos were subjected to computer simulation. As a result, the fire detection accuracy of the proposed algorithm was determined to be 94.24%, with minimum false detection, demonstrating its improved performance and practicality compared to previous fixed threshold-based algorithms.

• The Korean Journal of Pesticide Science
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• v.20 no.2
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• pp.145-151
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• 2016

This study was carried out to develop the economic thresholds for powdery mildew on eggplant. To investigate the relationship between powdery mildew incidence degree and yield, experimental plots with ten treatments as the initial disease degree were established. Disease severity exhibited negative and significant correlation with fruit weight and number of fruit. There existed close correlation between rate of diseased leaf area and yields in the greenhouse (control with fungicide Y = -36.5X+2938.5 $R^2=0.91$ $r=-0.913^*$, no fungicide: Y = -29.57X+2574.4 $R^2=0.73$ $r=-0.858^*$). There existed close correlation between rate of diseased leaf area and yield loss in the greenhouse (Y = 1.27X-2.4 $R^2=0.88$ $r=0.91^*$). The economic thresholds for powdery mildew on eggplant was below 14.7% rate of diseased leaf area per plant in the greenhouse.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.25-33
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• 1997

The end-to-end rate-based control mechanism is used for the flow control of the ABR service to allow much more flexibility in ATM switching system. To accommodate the ABR service effciently many algorithms such as EFCI, EPRCA, ERICA, and CAPC2 have been proposed for the switch algorithm. ABR cells and related RM cells are received at the ATM switch fabric transparently without any processing. And then cells received from the traffic source are queued in the ABR buffer of switching system. The ABR buffer usually has some thresholds for easy congestion control signal transmission. Whatever we use, therefore, these can be many ABR traffic control algorithms to implement the ABR transfer capability. The genertion of congestion indicate signal for ABR control algorithms is determined by ABR buffer satus. And ABR buffer status is determined by ABR cells transfer ratio in ATM switch fabrics. In this paper, we presented the functional structures for control of the ABR traffic capability, proposed the readout scheduling, cell slot allocation of output link and the buffer allocation model for effective ABR traffic guranteeing with considering CBR/VBR traffics in ATM switch. Since the proposed readout scheduling scheme can provide more avaliable space to ABR buffer than existing readout scheduling scheme, generation rate of a SEND signal, that is, BCN signal in destination node can be increased for ABR call connection. Therefore, the proposed scheme, in this paper, can be appropriate as algorithm for effective ABR traffic service on output link of ATM switching node.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.176-181
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• 2002

In this paper, we consider the optimal control of detection threshold to minimize the conditional expectation of mean-square state estimation error for a probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the suboptimal detection threshold in a closed-form. This results are very useful for real- time implementation.

• The Journal of Information Technology
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• v.1 no.2
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• pp.65-79
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• 1998

In this thesis, a buffer alloction and management algorithm is proposed in order to satisfy the QoS of CBR/VBR traffics incomming to ATM networks. Proposed traffic menagement algorithm is based on the route seperation mechanism that allocates buffers acoording to traffic characterics, and sets threshold to allocated buffers. We developed a cell scheduling algorithm and evaluated cell delay and loss probability characteristics according to incomming traffic classes. The cell scheduling algorithm uses buffer size thresholds to control overload traffic flow.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.968-973
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• 2000

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.2
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• pp.103-113
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• 2013

We analyze the queueing model for leaky bucket (LB) scheme with dynamic arrivals and token rates. In other words, in our LB scheme the arrivals and token rates are changed according to the buffer occupancy. In telecommunication networks, the LB scheme has been used as a policing function to prevent congestion. By considering bursty and correlated properties of input traffic, the arrivals are assumed to follow a Markov-modulated Poisson process (MMPP). We derive the distribution of system state, and obtain the loss probability and the mean waiting time. The analysis is done by using the embedded Markov chain and supplementary variable method. We also present some numerical examples to show the effect of our proposed model.