• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.637-644
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• 2004

This paper proposed and implemented the adaptive transmission middleware for video streaming, which is able to support the adaptive transmission of video data to the fluctuating changes of network environment in the packet-based network and the properties of transmitted video data. The adaptive transmission middleware is made up SR-RTP-based transfer module and TFRC(TCP Friendly Rate Control)-based transfer-rate control module. The SR-RTP-based transfer module supports RTP-based real-time transfer of video data and packet retransmission scheme retransmitting the high-priority packets selectively in the damaged video data to reduce the error induced by the packet loss. Sharing the transmission bandwidth of network with the TCP-based data transfer, the TFRC-based transfer-rate control module controls the transfer rate of video data according to the most allowable transmission bandwidth in the network, so that the transfer rate is controlled adaptively to the fluctuating changes of transmission bandwidth. This paper, for the experiment, applied the adaptive transmission middleware to video streaming in the external Internet environment, and analyzed the effective frame transfer rate and the degree of the streaming jitter to evaluate the performance of packet-loss recovery and adaptive transfer rate control. In the external Internet environment where the packet-loss rate is high a bit, the relatively high streaming performance was showed compared with the case that didn't apply the adaptive transmission middleware.

• The Journal of Korean Physical Therapy
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• v.15 no.3
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• pp.295-345
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• 2003

This study investigated activation of cerebral cortex in patients with hemiplegia that was caused by neural damage. Key-point control movement therapy of Bobath was performed for 9 weeks in 3 subjects with hemiplegia and fMRI was used to compare and analyze activated degree of cerebral cortex in these subjects. fMRI was conducted using the blood oxygen level-dependent(BOLD) technique at 3.0T MR scanner with a standard head coil. The motor activation task consisted of finger flexion-extension exercise in six cycles(one half-cycles = 8 scans = $3\;sec{\times}\;8\;=\;24\;sec$). Subjects performed this task according to visual stimulus that sign of right hand or left hand twinkled(500ms on, 500ms off). After mapping activation of cerebral motor cortex on hand motor function, below results were obtained. 1. Activation decreased in primary motor area, whereas it increased in supplementary motor area and visual association area(p<.001). 2. Activation was observed in bilateral medial frontal gyrus, middle frontal gyrus of left cerebrum, inferior frontal gyrus, inter-hemispheric, fusiform gyrus of right cerebrum, superior parietal lobule of parietal lobe and precuneus in subjedt 1, parahippocampal gyrus of limbic lobe and cingulate gyrus in subject 2, and inferior frontal gyrus of right frontal lobe, middle frontal gyrus, and inferior parietal lobule of left cerebrum in subject 3 (p<.001). 3. Activation cluster extended in declive of right cellebellum posterior lobe in subject 1, culmen of anterior lobe and declive of posterior lobe in subject 2, and dentate gyrus of anterior lobe, culmen and tuber of posterior lobe in subject 3 (p<.001). In conclusion, these data showed that Key-point control movement therapy of Bobath after stroke affect cerebral cortex activation by increasing efficiency of cortical networks. Therefore mapping of brain neural network activation is useful for plasticity and reorganization of cerebral cortex and cortico-spinal tract of motor recovery mechanisms after stroke.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12B
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• pp.1049-1057
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• 2006

Overlay Multicast is an effective method for efficient utilization of system resources and network bandwidth without using hardware customization. Unlike in IP multicast, multicast tree reconstruction is required when non-leaf node leaves or fails. In this paper, we propose a proactive approach to solve this defect by using a resource reservation of the out degrees. This allows children of non-leaf node to connect to its new parent node immediately when its parent node leaves or fails. In our proposal, a proactive route maintenance gives a fast recovery time and reduces a delay effect in the new route. The simulation results show that our proposal takes shorter period of time than the other algorithms to reconstruct a similar tree and that it is a more effective way to deal with a lot of nodes that have lost their parent nodes.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.82.2-82.2
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• 2017

Korea Microlensing Telescope Network (KMTNet) is one of powerful tools for investigating primordial objects in the inner solar system in that it covers a large area of the sky ($2{\times}2$ degree2) with a high observational cadence. The Deep Ecliptic Patrol of the Southern sky (DEEP-South) survey has been scanning the southern sky using KMTNet for non-bulge time (45 full nights per year) [1] since 2015 for examining color, albedo, rotation, and shape of the solar system bodies. Since 2017 January, we have launched a new collaborative group between Korea Astronomy and Space Science Institute (KASI) and Seoul National University (SNU) with support from KASI to reinforce mutual collaboration among these institutes and further to enhance human resources development by utilizing the KMTNet/DEEP-South data. In particular, we focus on the detection of comets and asteroids spontaneously scanned in the DEEP-South for (1) investigating the secular changes in comet's activities and (2) analyzing precovery and recovery images of objects in the NASA's NEOWISE survey region. In this presentation, we will describe our scientific objectives and current status on using KMTNet data, which includes updating the accuracy of the world coordinate system (WCS) information, finding algorithm of solar system bodies in the image, and doing non-sidereal photometry.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.11-18
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• 2017

The Objective of this Study is to Prove the Effectiveness of a Smart Water Management(SWM) Technology. The SWM Technology can Reduce the Production Cost using Internet of Thing(IoT) Technology that Utilizes Remote Metering of Consumer's Water usage and Reduce the Leakage of Supply Facilities. The SWM Demonstration Model Installed a Remote Water Leakage Sensor, Smart Metering and Micro Multi Sensor in Water Supply Facility, and Provided Real-Time Monitoring of the Operation Status. Consumers can be Provided the usage of Tap Water and the Water Puality through a Smart Phone Application. At this Time, we Surveyed Whether Consumers save the Tap Water or Drinking Directly using the Tap Water usage Information. Also, this Study is to Verify the Degree of Improvement of Water Supply Rates and Drinking Water Rate, and to Decrease Consumer's Complaints, Operating Costs, and Water Consumption by the SWM Technology. It is also Established a SWM Model Combined with the IoT Sensor at Supply Facilities, operator monitoring system and explored recovery solution detected events. It means the upbringing of the domestic water industry by developing the related technologies and spreading the SWM to advanced levels.

• Korean Journal of Social Welfare Studies
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• v.48 no.2
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• pp.173-201
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• 2017

This study examined the degree of socioeconomic deprivation in the areas of material hardship, health, housing, employment, and social network among people using debt relief programs. The sample, 209 individuals, was recruited from major agencies offering debt relief programs, including Seoul Bankruptcy Court, Credit Counseling and Recovery Service, and Seoul Welfare Foundation. Data were collected through in-person interviews in 2016. The sample was compared in terms of the level of deprivation with the general population and the low-income group, extracted from the Korea Welfare Panel Study. The debtors group demonstrated a substantially higher level of deprivation on all the dimensions examined. For example, the proportion of people who suffered from hunger was 37.8% in the debtors group compared to 6.7% in the low-income group. The proportion of people who had suicidal ideation in the last 12 months was 57.9% compared to 19.2% in the low-income group and 2.7% in the general population. The level of deprivation was different by chapter choice of consumer bankruptcy. Policy and practice implications of the results were discussed.

• Journal of Korean Society of Rural Planning
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• v.25 no.4
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• pp.13-26
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• 2019

The rural areas in South Korea have changed rapidly in the process of national land development. Rural landscapes have become discoloured, and their attractiveness has decreased as cities have expanded. But the attractiveness or multifunctional values of rural areas has become more important in contemporary society around the world. According to this social demand, the efforts of conserving the rural landscape are of high priority and the recovery of ruralism in the area is required. This study has tried to understand how the public image of ruralism in South Korea has been influenced by the news media. The study retrieved news articles using the web searching portal site from the six keywords, commonly used to refer to ruralism, including 'rural landscape', 'rural community', 'rural tourism', 'rural life', 'rural amenity', and 'rural environment'. News data from the six keywords were also collected respectively from within the year-period of 2004-05, 2007-08, 2012-13, and 2016-17. In the text mining analysis, the nouns with high Degree Centrality were figured out, and the changes by year-period were identified. Then, LDA topic analysis was performed for text datasets of six keywords. As a result, the study found that the news articles gave an informed focus on only a handful of issues such as 'poor rural living condition', 'regional or village improvement projects', 'rural tourism promotion projects', and 'other government support projects'. On the other hand, nouns related to virtues and values in the rural landscape were less shown in news articles. These results have become more apparent in recent years. In the topic analysis, 35 topics were identified. 'village development projects', 'rural tourism', and 'urban-rural exchange projects' were appeared repeatedly in several keywords. Among the topics, there are also topics closely related to ruralism such as 'rural landscape conservation', 'eco-friendly rural areas', 'local amenity resources', 'public interest values of agriculture', and 'rural life and communities'. The study presented an image map showing ruralism in South Korea using a network map between all topics and keywords. At the end of the study, implications for Korean rural area policy and research directions were discussed.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.