The purpose of this study was to evaluate the effects of insole-equipped ankle-foot-orthoses (AFO) on gait. 10 healthy males who had no history of injury in the lower extremity participated in this study as the subjects. The foot of each subject was first scanned, and the insole fit to the plantar was made using BDI-PCO(Pedcad Gmbh, Germany). The subject then was made to walk on a treadmill under four experimental conditions: 1) normal walking, 2) walking wearing AFO, 3) walking wearing AFO equipped with the insole, 4) walking wearing pneumatic-ankle-foot-orthosis (pAFO) equipped with the insole. During walking, foot pressure data such as maximum force, contacting area, peak pressure, and mean pressure was collected using Pedar-X system (Novel Gmbh, Germany) and EMG activity of lower limb muscles such as gastrocnemius medial head, gastrocnemius lateral head, and soleus was recorded using MP150 EMG module (BIOPAC System Inc., USA). Collected data was then analyzed using paired t-test in order to investigate the effects of the insole. As a result of the analysis, when insole was equipped, overall contacting area was increased while both the highest peak pressure and the mean pressure were significantly decreased, and EMG activity of the lower limb muscles was decreased. On the contrary, the cases of wearing AFO showed the decreased contacting area and the increased pressures. Therefore, the AFO equipped with a proper insole fit well to the foot can help comfortable walking by spreading the pressure over the entire plantar.
Journal of the Korea Academia-Industrial cooperation Society
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v.15
no.5
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pp.2641-2654
/
2014
In the smart media environment, magazine industry has been experiencing a transition to ecosystem of value network, which includes high complexity and ambiguity. Using case study method, this article conducts research on digital convergence, the model of magazine ecosystem and adaptation strategy of global magazine companies. Research findings have it that the way of contents production of global magazines has been based on collaborative production system within communities, expert communities, creative users, media contents companies and magazine platform. The system shows different patterns and characteristics depending on magazine-driven platform, Platform-driven platform or user-driven platform. Collaboration system has been confirmed in various cases: Huffington Post and Zinio which collaborate with media contents companies, Amazon magazines and Bookish with magazine companies, Huffington Post and Wired with expert communities, and Flipboard with creative users and communities. Foreign magazine contents diverge into (paper, electronic, app and web magazine) as they start the lively trades of their contents on the magazine platform. In the area of contents uses, readers employ smart media technology effectively such as cloud computing, artificial intelligence and module individualization, making it possible for the virtuous cycle to remain in the relationship within communities, expert communities and creative users.
Journal of the Korea Academia-Industrial cooperation Society
/
v.18
no.4
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pp.536-543
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2017
This study developed a new methodology to evaluate the carbon storage using a Mobile Mapping System according to the life cycle of street trees. The system for calculating the carbon storage of a roadside tree using the MMS developed in this study consisted of a database, memory, processor, user interface, and communication module. The carbon storage was calculated for 261 trees in the Cheonan-Asan New Town (distance: 2.1 km, area: $283,698m^2$). The average biomass and carbon storage of Metasequoia glyptostroboides were highest at 34.5 kg and 17.3 kg C and Chionanthus retusa were lowest at 19.5 kg and 9.8 kg C, respectively. The total biomass and total carbon storage of Ginkgo biloba were highest at 5028.8 kg and 17.3 kg C and Chionanthus retusa were lowest at 780.7 kg and 390.3 kg C, respectively. Based on the roadside tree database, the amount of carbon storage in a given area was converted to Google format and visualized in 3D by GIS analysis.
Objective : This study aimed to investigate and compare the prevalence of depression and suicidality among the elderly in a rural city according to their residence type. Methods : Participants were 311 elderly people (109 male and 202 female) in Icheon City, whom trained researchers interviewed and examined Geriatric Depression Scale, Social Support Scale, Instrumental Activities of Daily Living, Activities of Daily Living, Quality of Life Scale, and Mini International Neuropsychiatric Interview (MINI), module C. Using these data, we analyzed participants' risk factors associated with depression and suicidality. Results : The prevalence of depression was 28.0%. The prevalence in the elderly living alone and those admitted to residential facilities was significantly higher than that among the elderly living with family. Suicidality frequency was 19.6%. The suicidality frequency among the elderly living alone and those admitted to facilities was significantly higher than that among the elderly living with family. The risk factors for depression were age, admission to a facility, and low economic status. The suicidality risk factors were living alone, admission to a facility, poor social support, and a history of headache. Conclusion : These results showed the prevalence of depression and frequency of suicidality among the elderly in such a city was quite high. The results of this study remind psychiatrists of the importance of early detection and therapeutic intervention for the elderly with a high risk of depression and suicidality.
Proceedings of the Korea Water Resources Association Conference
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2016.05a
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pp.260-260
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2016
Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.
Journal of the Korean Society of Propulsion Engineers
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v.4
no.4
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pp.87-97
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2000
A steady state performance simulation and diagnostics program for the turboprop engine (PT6A-62), which is the power plant of the first developed military basic trainer KT-1 in Republic of Korea, was developed. The developed steady state performance analysis program was evaluated with the performance data provided by the engine manufacturer and with analysis results of GASTURB program, which is well known for the performance simulation of gas turbines. Performance parameters were discussed to evaluate validity of the developed program at various cases such as altitude, flight velocity and part load variation. GPA(Gas Pass Analysis) allows engine performance deterioration to be identified at the module level in terms of reduction in component efficiencies and changes in mass flow. In order to find optimal instrument set to detect the physical faults such as fouling, erosion and corrosion, a gas path analysis approach is utilized. This study was performed in two cases for selection of optimal measurement parameters. One case was considered with the effect of instrument number by changing independent parameter number. The other case was performed with selection of independent parameter set. According to the analysis results, the optimal measurement parameters selected were eight dependent variables such as shaft horsepower, fuel flow rate, compressor exit pressure and temperature, compressor turbine inlet pressure and temperature and power turbine inlet pressure and temperature.
Kim, Minjun;Lee, Changgyu;Hwang, Suyeon;Ham, Jungsoo;Choi, Jinmu
Korean Journal of Remote Sensing
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v.37
no.5_3
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pp.1435-1446
/
2021
Wind and flood damage caused by typhoons causes a lot of damage to the Korean Peninsula every year. In order to minimize damage, a preliminary analysis of damage estimation and evacuation routes is required for rapid decision-making. This study attempted to develop an analysis module that can provide necessary information according to the disaster stage. For use in the preparation stage, A function to check past typhoon routes and past damage information similar to typhoon routes heading north, a function to extract isolated dangerous areas, and a function to extract reservoir collapse areas were developed. For use in the early stages of response and recovery, a function to extract the expected flooding range considering the current flooding depth, a function to analyze expected damage information on population, buildings, farmland, and a function to provide evacuation information were included. In addition, an automated web map creation method was proposed to express the analysis results. The analysis function was developed and modularized based on Python open source, and the web display function was implemented based on JavaScript. The tools developed in this study are expected to be efficiently used for rapid decision-making in the early stages of monitoring against storm and flood damage.
The purpose of this study was to investigate the effects of flipped learning through EBSmath on Students' 'rate and ratio' learning. By increasing demands for change in education, an innovative teaching and learning paradigm, 'Flipped Learning', has been presented and drawing attentions. In South Korea, Flipped Learning is also highly recognized for its effectiveness by many scholars and various media. However, this innovative learning model has limitations in application and expansion due to the excessive burden of class preparation of teachers. As remote learning becomes more active, it would be possible to overcome the limitations of Filliped learning by using the platform provided by the Korea Educational Broadcasting System (EBS). EBSmath is an online learning module that is designed to assist students' self-directed learning. Thus, EBSmath would reduce teachers' burden to prepare mathematics classes for the application of Flipped Learning; and led to students' better understanding of mathematical concepts and problem solving. In this study, the effect of Flipped Learning through EBSmath on learning 'rate and ratio' was investigated. In order to scrutinize the effects of flipped learning, students' achievement and mathematical disposition were examined and analyzed. Students' achievement, specifically, was divided into two subcategories: concept understanding and problem solving. As a result, Flipped learning through EBSmath had a positive effect on students' 'rate and ratio' problem solving. In addition, a statistically significant change was identified in the 'willingness', which is subdomain of students' mathematical disposition.
Korean Journal of Construction Engineering and Management
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v.20
no.2
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pp.3-12
/
2019
Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.
Journal of the Korea Academia-Industrial cooperation Society
/
v.20
no.4
/
pp.50-55
/
2019
Recently Ransomware attacks are continuously increasing, and new Ransomware, which is difficult to detect just with a basic vaccine, continuously has its upward trend. Various solutions for Ransomware have been developed and applied. However, due to the disadvantages and limitations of existing solutions, damage caused by Ransomware has not been reduced. Ransomware is attacking various platforms no matter what platform it is, such as Windows, Linux, servers, IoT devices, and block chains. However, most existing solutions for Ransomware are difficult to apply to various platforms, and there is a limit that they are dependent on only some specific platforms while operating. This study analyzes the problems of existing Ransomware detection solutions and proposes the onboard module based Ransomware detection system; after the system defines the function of necessary elements through analyzing requirements that can actually reduce the damage caused by the Ransomware from the viewpoint of users, it supports various OS without pre-installation and is able to restore data even after being infected. We checked the feasibility of each function of the proposed system through the analysis of the existing technology and verified the suitability of the proposed techniques to meet the user's requirements through the questionnaire survey of a total of 264 users of personal and corporate PC users. As a result of statistical analysis of the questionnaire results, it was found that the score of intent to introduce the system was at 6.3 or more which appeared to be good, and the score of intent to change from existing solution to the proposed system was at 6.0 which appeared to be very high.
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