• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.35-44
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• 2022

The V_S30 map is used as a key variable for site amplification in the ShakeMap, which predicts ground motion at any site. However, no V_S30 map considering Korean geology and geomorphology has been developed yet. To develop a proxy-based V_S30 map, we used 1,101 V_S profiles obtained from a geophysical survey and collected proxy layers of geological and topographical information for the Korean Peninsula. Then, V_S30 prediction models were developed using linear regression analysis for each geological age considering the distribution of V_S30. As a result, models depending on geomorphology were suggested per each geologic group, including Quaternary, Fill, Ocean, Mesozoic group and Precambrian. Resolution of map is doubled from that of V_S30 map by U.S. Geological Survey (USGS). Standard deviation of residual in natural log of proxy-based V_S30 map is 0.233, whereas standard deviation of slope-based USGS V_S30 map is 0.387. Therefore, the proxy-based V_S30 map developed in this study is expected to have less uncertainty and to contribute to predicting more accurately the ground motion amplitude.

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2011.04a
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• pp.116-119
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• 2011

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2007.11a
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• pp.163.2-163.2
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• 2007

• Proceedings of the Korea Water Resources Association Conference
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• 1995.05a
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• pp.461-466
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• 1995

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.185-196
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• 2011

Exercise programs for elderly users are operated by each department and facility, but it is not enough to visualize exercise prescription and effect followed by elderly users physical conditions. The purpose of this study is to suggest exercise prescription for elderly users with a visual path map. A visual path map is to visually present types of users classified according to physical strength conditions, the process of exercise prescription, and effects of exercise. Exercise prescription is divided into four stages: analysis of physical conditions, exercise prescription by the visual path map, smart exercise prescription, and exercise for elderly users. The first stage, analysis of physical conditions is to classify physical conditions by each type by mechanically learning elderly users' physical test values. The second stage, exercise prescription by the visual path map, is to present exercise prescription suitable for elderly users' physical conditions. The third stage, smart exercise prescription, is to offer exercise prescription of the day when exercise is carried out using elderly users' smart phones in consideration of their situations. The fourth stage, exercise for elderly users, is to provide information by their smart phones when they exercise. In conclusion, this study will be able to induce elderly users to do continuous exercise by motivating them.

• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.97-106
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• 2018

Objective : The purpose of this study was to investigate the effects of reminiscence therapy using mind map to improve cognitive function, depression index, quality of life for old woman with dementia. Method : The study were 14 patients who were diagnosed with a woman suspected of dementia. They were randomly assigned to Study group(N=7) and control group(N=7). All patients received only to Study groups. reminiscence therapy using mind map was composed to 10 sessions, 40 minutes per sessions, 2 times a week, for 5 weeks. For result analysis, descriptive statistic, Wilcoxon signed rank test, and Mann-Whitney U test were used. The evaluation tools were Mini-Mental State Examination Korean Version (MMSE-K), Korean Version of Beck Depression Inventory (K-BDI), Korean Version of the World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). Result : There was a significant difference in cognitive function, depression index, and quality of life in the within group after intervention, and there was a significant difference in cognitive function in the between group comparison. Conclusion : According to the results of study, an easing effect was confirmed regarding reminiscence therapy using mind map for an old woman with dementia. using reminiscence therapy using mind map when applied to the improvement of cognitive function, depression index, quality of life.

• Speech Sciences
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• v.9 no.4
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• pp.59-75
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• 2002

Aerodynamic analysis study was performed on 14 normal subjects (2 males, 12 females) with nonsense syllables composed of Korean bilabial stops (/p, p', $p^{h}$) and their preceding and/or following vowels, /i, a, u/. That is, [pi, p'i, $p^{h}i$, pa, p'a, $p^{h}a$, pu, p'u, $p^{h}u$, ipi, apa, upu, $ip^{h}i$, $ap^{h}a$, $up^{h}u$, ip'i, ap'a, up'u]. All measures were taken and analysed using Aerophone II voice function analyzer and included peak air pressure, mean air pressure, maximum flow rate, volume, mean SPL and phonatory SPL. A t-test and one-way ANOVA were employed for analysis. A post-hoc analysis was performed with Scheffe and Bonferroni. The results were as follows: First, MSPL. and MAP of /p, p', $p^{h}$/ were significantly different in different positions (initial and medial position). In addition, different vowel environment also produced significantly different aerodynamic characteristics those consonants. Especially the lax consonant /p/ was significantly different /i, a, u/ vowel environments. The tense consonant /p'/ was significantly different only /i/ vowel environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.671-674
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• 2007

USN (Ubuquitous Sensor Network) identifies that networks are able to gather information from various kinds of sensors with RF. In the USN, it is important that sensor nodes deliver stable data by overcoming limited transmission distance and by setting optimum routes. In this paper, we propose a method to overcome the limited distance of sensor nodes using Wireless Mesh Networks. With this method, environmental monitoring system for u-farm support stable data transmission by applying MAP of Wireless Mesh Networks.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2229-2236
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• 2021

In nuclear-related facilities, such as nuclear power plants, research reactors, accelerators, and nuclear waste storage sites, radiation detection, and mapping are required to prevent radiation overexposure. Sensor network systems consisting of radiation sensor interfaces and wxireless communication units have become promising tools that can be used for data collection of radiation detection that can in turn be used to draw a radiation map. During data collection, malfunctions in some of the sensors can occasionally occur due to radiation effects, physical damage, network defects, sensor loss, or other reasons. This paper proposes a reproduction strategy for radiation maps using a U-net model to compensate for the loss of radiation detection data. To perform machine learning and verification, 1,561 simulations and 417 measured data of a sensor network were performed. The reproduction results show an accuracy of over 90%. The proposed strategy can offer an effective method that can be used to resolve the data loss problem for conventional sensor network systems and will specifically contribute to making initial responses with preserved data and without the high cost of radiation leak accidents at nuclear facilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.