• Physical Therapy Korea
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• v.13 no.1
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• pp.54-60
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• 2006

This study aimed to compare movement patterns of shoulder joints between the right and left symmetry in stroke patients and control subjects. This study proposes use of the voluntary response index (VRI) calculated from quantitative analysis of surface electromyographic (sEMG) and motion data recorded during voluntary movement as a feeding task. The VRI is comprised of two numeric values, one derived from the total muscle activity recorded for the voluntary motor task (magnitude), and the other from the sEMG distribution across the recorded muscles with the similarity index (SI). Five stroke patients and five age-matched healthy controls were recruited. Feeding motion was performed using the provided spoon five times with rests taken on a chair in between tasks. EMG data were digitized and analyzed on the basis of the root mean square (RMS) envelope of activity. The average amplitude of responses was calculated. Responsiveness and clinically meaningful levels of discrimination between stroke patients and control for EMG magnitude and SI were determined. The similarity index of the results from two successive examinations of both sides apart for stroke patients and control subjects were .86 and .95 in motion analysis and .84 and .99 in electromyographic analysis. The SI of sEMG data and motion data was significantly correlated in stroke patients. The data suggest that SI is a sensitive program for comparing and analyzing the symmetry of muscle activity and motion in both sides. This analysis method has a clinical value in grading muscular activity and movement impairment after brain injury.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.8-13
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• 2017

Nuclear power plant (NPP) constructions are large scale projects that are executed for several years, and schedule control utilizing various schedules is a critically important factor. Recently Korea independently developed the Advanced Power Reactor (APR) 1400 and is building nuclear facilities applying this new reactor type. The construction of Shin-Kori NPP (SKN) Unit 3, which adopted the APR1400, was completed and commercial operation has begun, while, SKN 4, Shin-Hanul NPP (SHN) Units 1&2, and SKN 5&6 are currently under construction. Prior to the development of the APR1400, Korea built 24 reactors and accumulated the schedule data of various reactor types which provided the foundation for schedule reduction to be possible. However, as there is no schedule development and review system established based on the standard schedule data (standard activities, durations, etc.) by reactor type, the process for developing the schedule for new builds is low in efficiency consuming much time and manpower. Also all construction data has been accumulated based on schedule activities. But because the connectivity of activities between projects is low, it is difficult to utilize such accumulated data (causes for schedule delay, causes for design changes, etc.) in new build projects. Due to such reasons, issues continue to arise in the process of developing standard schedule activities and a standard schedule for nuclear power plant construction. In order to develop a standard schedule for NPP construction, i) the development of an NPP standard schedule activity list, ii) development of the connection logic of NPP standard schedule activities, iii) development of NPP standard schedule activity resources and duration, and iv) integration of schedule data need to be performed. In this paper, an analysis was made on the coherence of schedule activity descriptions of existing NPPs by applying the probabilistic methodology on activities with low connectivity due to the utilization of the numbering system of four APR1400 reactors (SHN 1&2 and SKN 3&4).This study also describes the method for developing a standard schedule activity list and connectivity measures by extracting same and/or similar schedule activities.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.455-465
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• 2020

The purpose of this study was to investigate the relationship between physical activity and health-related quality of life of adults using the 7th National Health and Nutrition Survey. The study was conducted with 11,211 adults, and the health-related quality of life was defined using the EuroQol group's EQ-5D and physical activity using GPAQ. Data analysis was performed using the SAS 9.4 program, the general characteristics and degree of physical activity of the subject, Chi-square for KEQ-5D index, and Logistic Regression Analysis for the relationship between physical activity and quality of life. As a result of the study, the general characteristics of the subjects were marital status, educational status, occupation, smoking, alcohol consumption, economic status, stress, chronic disease, chronic disease treatment, physical activity due to leisure and physical activity due to occupation, depending on gender. There was a difference (p<0.05). As for the quality of life related to physical activity and health, the quality of life was significantly lower by 37% in the 'minimum physical activity group' of occupational physical activity (p<0.05). The results of this study are expected to be provided as basic data for physical activity-related health policy establishment and physical activity programs.

• International Journal of Safety
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• v.10 no.1
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• pp.5-9
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• 2011

Two popular activity coefficient models, Wilson and NRTL equations have been used to correlate the published flash point data on the n-propanol + propionic acid and n-butanol + propionic acid systems through the optimization method. The results of these correlation were compared with the results calculated by Raoult's law. The optimization method were found to be better than those based on the Raoult's law. The optimization method based on the Wilson equation described the published data more effectively than was the case when the optimization method was based upon the NRTL equation.

• The Journal of Industrial Distribution & Business
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• v.8 no.3
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• pp.11-18
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• 2017

Purpose - This study aims to analyze the effects of the social support on the economic activities from the Korean Chinese residing in Korea. Particularly, this paper focuses on the consequence of the economic activity intention according to the three kinds of social support. Research design, data, and methodology - For the statistics process of data collected by this survey, SPSS 19 statistics package program was used through data-coding and data-cleaning processes to analyze the data in this study. Results - This hypothesis was selected partially. As a result of investigating hypotheses in detail, Hypothesis 1-2 was significant as shown in the significance level 0.1, and when the emotional support was regarded important, the will of economic activities was also higher. Hypothesis 1-2 was found to be meaningful with the significance level of 0.05, and when the social support was regarded important, the will of economic activities was also higher. Lastly, Hypothesis 1-3 was found to not be statistically significant. Conclusions - The results of this study are expected to be used as basic data for vitalization of the Korean Chinese' economic activities and governmental support for it, and to be a guideline in preparing successful strategies for expansion of the Korean Chinese' economic activities in the future by applying these results.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.291-300
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• 2014

In this study, we investigated the activity data and basic data of the surface of the water within the ship to be operated by lakes and rivers inland. In this study previously, there was no survey activity data of Ferry and Cruise ship in Korea. In order to ensure the basic data and development of measures to reduce efficiently by local governments, these studies should be performed. Therefore, in the present study was survey the activity data such as cruising time and engine load factor and the specifications of the vessels. As a result, by analyzing the cruising pattern according to the area and the purpose of the cruise, to calculate the emissions of greenhouse gases.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

• Smart Media Journal
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• v.6 no.3
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• pp.83-88
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• 2017

The data analysis system using Big-data is worthy to be used in various fields such as politics, traffic, natural disaster, shopping, customer management, medical care, and weather information. Particularly, the analysis of the momentum of an individual using an acceleration signal collected from a wearable device has already been widely used. However, since the data used in such a system stores only the data necessary for measuring the individual activity, it does not provide various analysis results other than the exercise amount of the individual. In this paper, I propose a system that analyzes collective behavior pattern and activity based on the acceleration signal that can be collected from personal smartphones for 24 hours a day and stored in big data. I also propose a system that sends acceleration signals and receives analysis results using standard messaging to use on various smart devices.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.6-20
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• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• Natural Product Sciences
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• v.22 no.4
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• pp.270-274
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• 2016

Green tea, the leaves of Camellia sinsneis (Theaceae), is generally acknowledged as the most consumed beverage with multiple pharmacological functions including antioxidant activity. This study was performed to analyze the effect of extraction conditions of green tea on its antioxidant effects using DPPH assay. Three extraction factors such as extraction solvent (EtOH, 0 - 100%), extraction time (3 - 15 min) and extraction temperature ($10-70^{\circ}C$) were analyzed and optimized extraction condition for antioxidant activity of green tea extract (GTE) was determined using response surface methodology with three-level-three-factor Box-Behnken design (BBD). Regression analysis showed a good fit of data and the optimal conditions of extraction were found to be 57.7% EtOH, 15 min and $70^{\circ}C$. Under this condition, antioxidant activity of experimental data was 88.4% which was almost fit to the ideal value of 88.6%. As epigallocatechin gallate (EGCG) is known for the major ingredient for antioxidant activity of green tea, we investigated the effect of EGCG on antioxidant activity of GTE. EGCG showed antioxidant activity with the $IC_{50}$ value of $4.2{\mu}g/ml$ and a positive correlation was observed between EGCG content and the antioxidant activity of GTE with $R^2=0.7134$. Interestingly, however, GTE with 50 - 70% antioxidant activity contain less than $1.0{\mu}g/ml$ of EGCG, which is much lower than $IC_{50}$ value of EGCG. Therefore, we suppose that EGCG together with other constituents contribute to antioxidant activity of GTE. Taken together, these results suggest that green tea is more beneficial than EGCG alone for antioxidant ability and optimal extraction condition of green tea will be useful for the development of food and pharmaceutical applications