• Korea Journal of Hospital Management
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• v.12 no.1
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• pp.51-74
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• 2007

This study applied Data Envelopment Analysis to a set of Korean Public Corporation Medical Centers and Japanese Municipal Hospitals to compare their relative human resource efficiencies. Based on the data provided on the inputs and outputs, the analysis showed Japanese municipal hospitals were relatively efficient than Korean hospitals. The result of analysing BCC model shows 5 hospitals in Japan and 7 in Korea with an efficiency rating of less than 1 as considered relatively inefficient. For the inefficient hospitals the manner in which inefficient hospitals may be made efficient were indicated by the managerial strategies based on dual variables. A subsequent analysis of Wilcoxon rank-sum test revealed that the medical revenue per medical expense, labor cost per value added revenue were statistically significant between efficient and inefficient Korean hospitals and medical revenue per medical expense, labor cost per value added revenue, bed occupancy rate, average length of stay, rate of personnel expenses per medical revenue were statistically significant between efficient and inefficient Japanese hospitals.

• Journal of IKEEE
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• v.23 no.1
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• pp.112-119
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• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.7-17
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• 2001

The purpose of this paper is to develop automatic incident detection algorithm using image based detector in freeway management system. This algorithm was developed by using neutral network for high speed roadway and by using speed and occupancy variable for low speed roadway. The image detector system with the developed automatic incident detection algorithm can detect multi-lane as well as several detect areas for each lane. To evaluate this system, field tests to measure the detecting rate of incidents were performed with other systems which have APID and DES algorithm at high speed roadway(freeway) and low speed roadway(national arterial). As the results of field test, it found that the detect rate of this system was highest rate comparing to other two systems.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.3
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• pp.14-24
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• 2007

The purpose of this study was to investigate how the landscape characteristics and the physical factors of landscape would affect the preference for the Gapcheon in Daejeon Metropolitan City. The Gapcheon was divided in three sections of the outskirts, Expopark areas, and residential complexes. After selecting seven landscape points where the sections could be expressed best, photographs were taken both in the upstream and downstream direction. The questionnaire used to evaluate the river's landscape included 20 items of adverbs that described the form of the river and one item to rate the overall preference. By analyzing the 14 pictures taken, the occupancy rates of the landscape elements in terms of the sky, river, vegetation of the river, mountain, and artificial structures. Image factor analysis was conducted for each of the sections in order to analyze the landscape characteristics of the Gapcheon, and then regression analysis was conducted in order to analyze the relationships among the physical factors influencing the preference of the landscapes. The results were as follows : Factors that compose the visual characters of urban river were classified be the aesthetic factor, the emotional factor and the situation factor. These 3 factors showed a 65.8% total variance. The river landscape with the biggest preference was the one from the Daedeok Grand Bridge as the occupancy area of the mountain, sky, and river was large and distributed evenly and the vegetation of the river was in a good harmony with the surroundings. After carrying out regression analysis to examine the relationships between the visual preference of Gapcheon and the physical factors of landscape(the sky, river, vegetation of the river, mountain, and artificial structure), the following regressions model was made : PRE=5.906+0.017(river)-0.053(artificial structure)-0.060(vegetation of the river) (R-square=0.48).

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.369-380
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• 1996

Inductive Loop Detector(ILD) has been commonly used in collecting traffic data such as occupancy time and non-occupancy time. From the data, the traffic volume and type of passing vehicle is calculated. To provide reliable data for traffic control and plan, accuracy is required in type recognition which can be utilized to determine split of traffic signal and to provide forecasting data of queue-length for over-saturation control. In this research, a new recognition model issuggested for recognizing typeof vehicle from thecollected data obtained through ILD systems. Two clustering methods, based on statistical algorithms, and one neural network clustering method were employed to test the reliability and occuracy for the methods. In a series of experiments, it was found that the new model can greatly enhance the reliability and accuracy of type recongition rate, much higher than conventional approa-ches. The model modifies the neural network clustering method and enhances the recongition accuracy by iteratively applying the algorithm until no more unclustered data remains.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.63-70
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• 2010

In IEEE 802.11e system providing differentiated services, there exist some problems as follows; collision probability increase due to the increase in the number of nodes by employing CSMA/CA transmission mode, transmission speed declining tendency towards the worst of it, which is caused by different transmission mode and decrease of TCP transmission rate as the result of the link occupancy by UDP when TCP shares the link with UDP by the TCP’s flow control characteristic. In this thesis, the initial minimum and maximum CW are set differently according to the number of connected nodes in the network to avoid collisions and TXOP is adjusted according to the channel state, in which ACs with low priority but better channel state will get gradually more chances to transmit leading to optimal channel capacity. Also, by allowing higher priority for ACK frames which control the TCP transmission, the flow control becomes better because that reduces the channel occupancy by UDP flow, and by this, fair transmission is obtained from the result of the more fair transmission and active resource allocation.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.19-26
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• 2002

The purpose of this paper is to study the fundamental characteristics of bicycle flows. Several experiments were conducted to obtain the characteristics of bicycle flows, speed variation along a curve radius, bicycle driver's travelling territory and saturation flow rate at signalized intersection. Bicycle facilities are categorized into uninterrupted and interrupted, the capacity of uninterrupted is approximately 5000bic/h, and that of the interrupted (at signalized intersection) is approximately 3000bic/h, when a curve radius is over 20m, bicycle speed is not increasing. Bicycle driver's travelling territory is used to occupancy area, it is the same concept as pedestrian's. Bicycle occupancy area is to be divided into circulation zone, comfort zone. and collision zone. Circulation zone is over 2.21$\times$4.1m and collision zone is less than 0.96$\times$2.47m. Comfort zone is defined as intermediate state between two zones.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.29-39
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• 2015

Currently, level of service(LOS) analysis methods for pedestrian sidewalks are provided in Korean Highway Capacity Manual(KHCM, 2013). However, conventional methods provided in the KHCM produce most of pedestrian sidewalks' LOS as level A, indicating that existing analysis methods are unable to reflect realistic pedestrian sidewalks' LOS. The objectives of this research are to identify the suitability of current LOS criteria and to propose improved LOS evaluation criteria and methods with pedestrian volume data carried out for 10,000 sites in 2009. This research proposes new criteria by using the qualitative definition of LOS proposed by Fruin and Hall, new standard Korean human scale and new criteria of pedestrian occupancy space. Application results of new criteria show that more realistic results can be achieved than the existing methods. It is expected that applying the newly developed criteria and methods can make planning, design and construction of pedestrian sidewalks more realistic and various.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• Journal of KIISE
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• v.42 no.12
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• pp.1600-1610
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• 2015

While today's networks have been shown to exhibit HBDP (High Bandwidth Delay Product) characteristics, the legacy TCP increases the size of the congestion window slowly and decreases the size of the congestion window drastically such that it is not suitable for HBDP Networks. In order to solve this problem with the legacy TCP, many congestion control TCP mechanisms have been proposed. C-TCP (Compound-TCP) is a hybrid TCP which is a synergy of delay-based and loss-based approaches. C-TCP adapts the decreasing rate of the delay window without considering the congestion level, leading to degradation of performance. In this paper, we propose a new scheme to improve the performance of C-TCP. By controlling the increasing and decreasing rates according to the congestion level of the network, our proposed scheme can improve the bandwidth occupancy and fairness of C-TCP. Through performance evaluation, we show that our proposed scheme offers better performance in HBDP networks as compared to the legacy C-TCP.