• Korean Journal of Community Nutrition
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• v.16 no.6
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• pp.683-696
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• 2011

This study compared levels of health beliefs and health behavior practices according to lifestyle pattern among adults in Seoul. A self-administered survey questionnaire was collected from a total of 1,004 Seoul residents aged 30-59 years. The levels of perceived benefit, perceived barrier, and self-efficacy from health belief model and health behavior practices were measured across multiple health behavior areas including dietary behavior, drinking, smoking, exercise, functional food consumption, and weight control behavior. Factor analysis and subsequent cluster analysis based on 28 lifestyle questions divided the subjects into four lifestyles of society-, economy-, trend-, and health-oriented lifestyle. Some general characteristics were significantly different by lifestyles. The society-oriented lifestyle was significantly higher in proportions of men and overweight. The trend-oriented lifestyle was significantly younger and spent more monthly allowance. Health-oriented lifestyle was older. The levels of health belief variables and health behavior practices significantly differed by lifestyles. Overall the health-oriented lifestyle showed more desirable levels of health belief variables and health behavior practice in various health behavior areas compared to the other lifestyles, whereas the society-oriented lifestyle was found the other way. Health belief model variables including perceived benefit, perceived barrier, and self-efficacy were generally significant in predicting the levels of various health behavior practice, with somewhat differences by lifestyle pattern and health behavior type. The study findings suggest it may be useful to segment target subjects according to lifestyle pattern in planning and administering health education programs.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.162-175
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• 2018

Currently, electricity consumption and feedback mechanisms are being widely researched in Internet of Things (IoT) areas to realise power consumption monitoring and management through the remote control of appliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief network for electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring and control module is developed for automatically operating air conditioners with a gateway, which connects and controls the appliances through an embedded ZigBee solution. To collect electricity consumption data, a programmable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisation via the Internet and report the operational parameters and working states. The cloud platform manages the behaviour planning functions of the energy-saving strategies based on the power consumption features analysed by a deep belief network algorithm, which enables the automatic classification of the electricity utilisation situation. Besides increasing the user's comfort and improving the user's experience, the established feature models provide reliable information and effective control suggestions for power reduction by refining the air conditioner operation habits of each house. In addition, several data visualisation technologies are utilised to present the power consumption datasets intuitively.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.33-44
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• 2023

Entrepreneurial self-efficacy is an important variable that explains people's attitudes and behaviors toward start-ups. In this study, we focused on individual psychological characteristics variables such as luck in belief and positive cognitive bias that affect entrepreneurial self-efficacy. Among these variables, we paid particular attention to luck in belief. The belief that business success depends on luck is widespread, but scientific verification about it has not been much. The reason for the academic indifference is that luck is a kind of superstition, related to precognition or extrasensory perception, and randomly caused by the external environment. The study of luck began in earnest as a measure to measure luck as an individual characteristic variable such as personality was developed. The purpose of this study is to examine the existing studies on luck in belief and to examine the effect of this luck in belief on positive cognitive bias and entrepreneurial self-efficacy through empirical analysis. For empirical analysis, this study conducted an on-line survey of 400 ordinary people and conducted a structural equation model analysis using AMOS 21.0 to verify the hypothesis. As a result of hypothesis testing, all hypotheses that luck in belief would have a positive effect on positive cognitive bias(self-enhancement bias, illusion of control bias, unrealism optimistic bias) were adopted. The hypothesis that positive cognitive bias(self-enhancement bias, illusion of control bias, unrealistic optimism bias) will have a positive effect on entrepreneurial self-efficacy was also adopted. Additional analysis was conducted to examine the mediating role of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy, which showed that 'luck in belief→positive cognitive bias →entrepreneurial self-efficacy' were statistically significant. Through this, we confirmed the mediating effect of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy. In the conclusion, the implications and limitations of the study were presented based on the results of this study.

• Journal of dental hygiene science
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• v.15 no.4
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• pp.430-436
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• 2015

This study examined the correlation of educational experience with practical behavior in infection control. Subjects were 152 dental hygienists in Gwangju from September 15 to October 5, 2015. The ratio of dental hygienists educated on infection control was higher in those worked in dental care with 2~4 dentist for 2~5 years and lower in those worked in dental cared with 1 dentist for 2~5 years (p<0.05, p<0.001). The dental hygienists with or without educational experience in infection control exhibited the highest activity rate in hand wash and the lowest in face protection. Barrier in health belief, was lower with the need for education in infection control among the factors affecting on the activity in infection control. The activity was higher with susceptibility and cue to action (p<0.05). Based on the results, education program on infection control should be developed, and applied periodically and obligatorily for dentist and all staffs of dental care to remove susceptibility and barrier, and to enhance cue to action. This will result the effective control of infection by elevating the health belief.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.3-91
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• 2001

A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.106.1-106
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• 2002

$\textbullet$ Current status of reliability estimation techniques for robot systems $\textbullet$ Description of Bayesian Belief Nets(BBN) With an example $\textbullet$ Description of proposed reliability estimation method which combines all information necessary $\textbullet$ Application example of the method : the reactor inspection robot $\textbullet$ Results from the reliability estimation of reactor inspection robot $\textbullet$ Discussion on the proposed method (advantages and problems) $\textbullet$ Conclusion

• Asia pacific journal of information systems
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• v.12 no.2
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• pp.45-68
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• 2002

Technology adoption for information appliance, which is expected to grow rapidly in the near future, is different from other technologies in that it is mainly used in the home environment when the customers haven't experienced it before. This paper finds important variables from prior research about technology adoption and develops a measurement model that fits for the information appliance. Pretest and pilot studies for the model is conducted in order to guarantee content validity, reliability, convergent validity and discriminant validity. Finally, LISREL analysis is used for finding out the causality among variables and testing for model fitness. The results indicate that three factors that influence behavioral intention are attitude, subjective norm and perceived behavioral control. Attitude is influenced by attitudinal belief, which consists of perceived usefulness, trialability, result demonstrability, image and enjoyment. Perceived behavioral control is influenced by control belief that consists of rapid change in technology, cost and ease of use. This paper ends with implications and limitations of study results.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.347-357
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• 2021

Since the outbreak of Covid-19, many countries have tried to defense Covid-19 to protect their people and as an influential and reliable policy as of now, they have recommended vaccinating. Thus, this research explored what influences the intention to vaccinate against Covid-19 with three health locus of control from multi-dimension health locus of control (MHLC) and perceived susceptibility and severity from health belief model (HBM) through PLS path modeling. Consequently, chance locus of control (CHLC) influence indirectly intention to vaccinate against Covid-19 mediating with susceptibility perception. It implies that the more fatalistic people attitude toward Covid-19, the more susceptible they perceived to the disease, and then, the stronger intention to vaccinate they would have. Thus, the health promotion authorities should motivate to activate people's susceptibility perception toward the disease through utilizing a variety of policies and consider that the fatalistic tendency toward the disease of people could play an antecedent role in the process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.162-164
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• 2010

Terrestrial trunked radio (TETRA) standard specifies shortened Reed-Muller (RM) codes as forward error correction means for control signals. In this paper, we compare decoding algorithms for RM codes in TETRA, in terms of performance and complexity trade-off. Belief propagation and majority logic decoding algorithms are selected for comparison.