• Journal of Digital Convergence
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• 제13권12호
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• pp.225-233
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• 2015

This study was conducted in an attempt to determine the factors that cause excessive daytime sleepiness among 927 subway station employees located in Seoul. Data were collected with a structured questionnaire through the web site and were analyzed using SPSS 20.0 statistical software. Results showed that marital status made a statistically significant difference in general characteristics, and hobby/leisure activities made a statistically significant difference in health-related characteristics. Workplace and satisfaction with the organization made a significant difference in job-related characteristics, and physical environment, job demand, job autonomy, relationship conflicts, organizational system, inappropriate compensation, and organizational culture made a statistically significant difference in job stress factors. Factors that affect excessive daytime sleepiness were hobby and leisure activities, satisfaction with the organization, physical environment, job demand, job autonomy, organizational system and organizational culture, showing a 20.5% explanatory power. This study proposes the operation of programs that can improve the physical environment, change the organizational system and increase satisfaction with the organizational culture among station employees in order that they can enjoy their hobby/leisure life and relieve job stress so that they can avoid excessive daytime sleepiness.

• Economic and Environmental Geology
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• 제36권3호
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• pp.243-255
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• 2003

The mathematical models for GIS-based spatial data integration have been developed for geological applications such as mineral potential mapping or landslide susceptibility analysis. Among various models, the effectiveness of fuzzy logic based integration of multiple sets of geological data is investigated and discussed. Unlike a traditional target-driven fuzzy integration approach, we propose a data-driven approach that is derived from statistical relationships between the integration target and related spatial geological data. The proposed approach consists of four analytical steps; data representation, fuzzy combination, defuzzification and validation. For data representation, the fuzzy membership functions based on the likelihood ratio functions are proposed. To integrate them, the fuzzy inference network is designed that can combine a variety of different fuzzy operators. Defuzzification is carried out to effectively visualize the relative possibility levels from the integrated results. Finally, a validation approach based on the spatial partitioning of integration targets is proposed to quantitatively compare various fuzzy integration maps and obtain a meaningful interpretation with respect to future events. The effectiveness and some suggestions of the schemes proposed here are illustrated by describing a case study for landslide susceptibility analysis. The case study demonstrates that the proposed schemes can effectively identify areas that are susceptible to landslides and ${\gamma}$ operator shows the better prediction power than the results using max and min operators from the validation procedure.

• Journal of Gifted/Talented Education
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• 제21권4호
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• pp.961-977
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• 2011

The purpose of this study was to investigate the relationship between learning motivation and task commitment and find sub factors of learning motivation that affect task commitment. For this study 30 science gifted student (4th and 5th grade in elementary school) participated. The survey instruments used for this study were Academic Motivation Scale and Task Commitment Scale. The statistical methods employed for data analysis were the correlation analysis and multiple regression analysis. The result of this study were as follows: First, the learning motivation and task commitment of science gifted students showed similar levels. But there was differences of strength each sub factors of learning motivation and task commitment. Second, there was a significant positive correlation between learning motivation and task commitment. Also, learning motivation has the explanatory power of predictive variable for the task commitment approximately 49.3%. Expecially learning motivation has significant positive correlation with responsibility and self-control that sub factors of task commitment. Among the sub factor of learning motivation, confidence has most correlations with sub factors of task commitment and significant impact on task commitment. This result indicate that we need to develop learning motivation to improve task commitment and especially develop learning motivation program to grow up confidence of science-gifted.

• Geophysics and Geophysical Exploration
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• 제13권3호
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• pp.249-255
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• 2010

Since the 1990's, a number of ULF geomagnetic disturbance associated with earthquake occurrences have actively been reported, and polarization analysis of geomagnetic fields becomes one of potential candidates to be capable of predicting short-term earthquake. This study develops the modified polarization analysis method based on the previous studies, and analyzes three-component geomagnetic fields obtained at Cheongyang geomagnetic observatory using the developed method. A daily polarization value (the ratio of spectral power of horizontal and vertical geomagnetic field) is calculated with a focus on the 0.01 Hz band, which is known to be the most sensitive to seismogenic ULF radiation. We analyze a total of 10 months of geomagnetic data obtained at Cheongyang observatory, and compare the polarization values with the Kp index and the earthquake occurred in the analysis period. The results show that there is little correlation between the temporal variations of polarization values and Kp index, but remarkable increases in polarization values are identified which are associated with two earthquakes. Comparison the polarization values obtained at Cheongyang and Kanoya observatory indicates that the increases of polarization values at Cheongyang might be due to not global geomagnetic induction but the locally occurred earthquakes. Furthermore, these features are clearly shown in normalized polarization values, which take account in the statistical characteristics of each geomagnetic field. On the basis of these results, polarization analysis can be used as promising tool for monitoring the earthquake-precursory phenomenon.

• The KIPS Transactions:PartB
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• 제11B권1호
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• pp.71-76
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• 2004

The recent ERP and CRM is mostly focused on the conventional function performances. However, the recent business environment has brought the change in market due to the rapid progress of internet and e-commerce. It is mostly becoming e-business and spreading out as development of the relationship with other cooperating companies, the rapid progress of the relationship with customers, and intensification competitive power through the development of business progress in the organization. CRM(custom relationship management) is a kind of the marketing progress which forms, manages, and intensifies the relationship between the customers and companies to manage the acquired customers and increase the worth of customers for the company. It needs the system base which analyzes the information of customers since it functions on the basis of various information about customers and is linked to the business category such as producing, marketing, and decision making. Since ERP is extending its function to SCM, CRM, and SEM(strategic Enterprise Management), the 21 century s ERP develop as the strategy tool of e-business and, as the mediation for this, will subdivide the functions of CRM effectively by the analogic study of data. Also, to accomplish classification work of the file which in existing becomes accomplished with possibility work with an automatic movement with the user will be able to accomplish a more efficiently work the agent which in order leads the machine studying law, it is one thing with system feature.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1641-1648
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• 2017

Many researchers had examined the validity of using the high-to-low ratio between two fixed frequency band amplitudes (H/L-FFB) from the surface electromyography of a face and body as the first spectral index to assess muscle fatigue. Despite these studies, the disadvantage of this index is the lack of a criterion for choosing the optimal border frequency. We tested the potential of using the high-to-low ratio between two signal spectral moments (H/L-SSM), without fixed border frequencies, to evaluate muscle fatigue and predict endurance time ($T_{end}$), which was determined when the subject was exhausted and could no longer follow the fixed contraction cycle. Ten healthy participants performed five sets of voluntary isotonic contractions until they could only produce 10% and 20% of their maximum voluntary contraction (MVC). The $T_{end}$ values for all participants were $138{\pm}35s$ at 10% MVC and $69{\pm}20s$ at 20% MVC. Changes in conventional spectral indices, such as the mean power frequency (MPF), Dimitrov spectral index (DSI), H/L-FFB, and H/L-SSM, were extracted from surface EMG signals and were monitored using the initial slope computed every 10% of $T_{end}$ as a statistical indicator and compared as a predictor of $T_{end}$. Significant correlations were found between $T_{end}$ and the initial H/L-SSM slope as computed over 30% of $T_{end}$. In conclusion, initial H/L-SSM slope can be used to describe changes in the spectral content of surface EMG signals and can be employed as a good predictor of $T_{end}$ compared to that of conventional spectral indices.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제21권7호
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• pp.656-666
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• 2020

This study was a descriptive research study for hemodialysis patients to survey the effects of social support and health literacy on treatment adherence. The subjects of this study were 140 hemodialysis patients aged over 40 years who had been receiving treatment for more 1 year in artificial kidney rooms at two general hospitals in Y city. The data were collected from November 1, 2019 to December 31, 2019 and were analyzed using descriptive statistics, t-tests, one-way ANOVA, Scheffe test, Pearson's correlation coefficients, and multiple regression with the SPSS/WIN 26.0 statistical program. The results of this study show that social support (family, friends, medical staff) and health literacy (functional, communication, critical) were positively correlated with treatment adherence. The variables affecting treatment adherence in hemodialysis patients were identified by social support and health literacy with 69.6% explanatory power. To improve the treatment adherence of hemodialysis patients, it is necessary to develop education programs to improve health literacy based on social support.

• The Journal of the Korea Contents Association
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• 제10권8호
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• pp.407-416
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• 2010

The purpose of this study was to examine the relationship among women's leisure dance participation, physical image and self-esteem. The subjects in this study were 300 female adults who were selected by cluster sampling from the population that consisted of women who were in their 20s to 50s. In the population, some women got leisure dance at fitness clubs, sport lovers' clubs and dance academies in Seoul and Gyeoggn Province as of 2009, and the others didn't. As for the reliability of the questionnaires used in the study, the Cronbach alpha coefficient of the questionnaires was above .70. The major statistical methods utilized in this study were Frequencies, reliability factor analysis, analysis covariate, regression analysis and path analysis. The findings of the study were as follows: First, the women who got leisuer dance evaluated their own physical image and self-esteem more favorably than the others who didn't. Second, the length of participation affected the body shape, satisfaction level and flexibility, and the intensity of participation impacted on the body shape and muscular power. Third, the length of participation had an impact on self-esteem, and the frequency of participation exerted a negative influence on that. Fourth, the degree of participation had a causal impact on physical image and self-esteem. In other words, the degree of getting leisure dance affected self-esteem in a firsthand manner and exerted a secondhand influence on that through physical image as well. The findings of the study suggested that physical image was one of major parameters to link participation in rhythmic exercise and self-esteem.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제21권5호
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• pp.312-319
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• 2020

This study examined the factors that affect the turnover intention of newly graduated nurses. The basic data was utilized for developing a personnel resource maintenance program for newly graduated nurses. New nurses working at a general hospital in City D were surveyed from May 2016 to April 2018. The questionnaires completed by 232 volunteers were analyzed using the IBM SPSS 21.0 program, and the descriptive statistical analyses included t-tests, ANOVA, Scheffe test, Pearson's correlation coefficient, and multiple regression analysis. Among the general characteristics of new nurses, their workload displayed significant differences in proactive behavior, organizational commitment, social support, and the turnover intention. There was a negative correlation between organizational commitment, employer support, peer support, and the turnover intention. The influential factors were organizational commitment and workload, and the explanatory power for turnover intention was 36.1%. Higher organizational commitment, along with appropriate workload, led to a lower turnover intention. Therefore, appropriate work allocation through work analysis is necessary to lower the nurses' turnover intention. Developing a program that can increase proactive behavior and implementing various intervention strategies can increase the participation of newly graduated nurses when establishing and implementing appropriate hospital policies.

• Korean Journal of Cognitive Science
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• 제21권2호
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• pp.309-338
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• 2010

In this paper, we studied the brain-computer interface (BCI). BCIs help severely disabled people to control external devices by analyzing their brain signals evoked from motor imageries. The findings in the field of neurophysiology revealed that the power of $\beta$(14-26 Hz) and $\mu$(8-12 Hz) rhythms decreases or increases in synchrony of the underlying neuronal populations in the sensorymotor cortex when people imagine the movement of their body parts. These are called Event-Related Desynchronization / Synchronization (ERD/ERS), respectively. We implemented a BCI-based mouse interface system which enabled subjects to control a computer mouse cursor into four different directions (e.g., up, down, left, and right) by analyzing brain signal patterns online. Tongue, foot, left-hand, and right-hand motor imageries were utilized to stimulate a human brain. We used a non-invasive EEG which records brain's spontaneous electrical activity over a short period of time by placing electrodes on the scalp. Because of the nature of the EEG signals, i.e., low amplitude and vulnerability to artifacts and noise, it is hard to analyze and classify brain signals measured by EEG directly. In order to overcome these obstacles, we applied statistical machine-learning techniques. We could achieve high performance in the classification of four motor imageries by employing Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) which transformed input EEG signals into a new coordinate system making the variances among different motor imagery signals maximized for easy classification. From the inspection of the topographies of the results, we could also confirm ERD/ERS appeared at different brain areas for different motor imageries showing the correspondence with the anatomical and neurophysiological knowledge.