• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.93-99
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• 2017

Necessity of adjustment in level of difficulty of national examination for radiological technologists is being brought up. However, objective reasons are required to make those arguments more valid. Therefore in this research, result of national examination for radiological technologists under present system was analyzed in more convergence perspective via statistical analysis. This will provide basic data which is applicable when system of national examination for radiological technologists undergo improvements. For this, statistical analysis such as descriptive statistics and correlation analysis was conducted using SPSS program. Results are as follow. First, ratio of successful applicants for radiological technologists was highly fluctuant relative to other national examinations like doctor, nurse, physical therapist, etc. Second, level of difficulty and discernment of national examination for radiological technologists were differentiated from other examinations like doctor, nurse, physical therapist. Third, the 43th examination for radiological technologists conducted in 2015 had the highest discernment as 0.41, despite of lowest level of difficulty as 89.2, for radiologic applications. The results of this research is expected to be used as basic data when system of national examination for radiological technologists undergo improvements, in accordance with increased supplying plan of work-forces in medical radiological technologists.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.471-479
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• 2019

The purpose of this study was to investigate the correlations between ADHD, depression, anxiety, suicide risk and suicide risk of university freshmen, and to investigate factors affecting suicide risk of university freshmen. As a result, the correlation between suicide risk and ADHD, depression, and anxiety were statistically significant. The correlation between suicide risk and ADHD (r=-.411) was moderately negative, while depression (r=-.594) and anxiety (r=-.563) were high negative correlations. According to the logistic regression analysis, the significant factors affecting suicide risk of college freshmen were ADHD, depression, and anxiety. In the abnormal group of variables, ADHD (OR=3.17; 95% CI 1.36-7.38), depression (OR=10.80; 95% CI 4.32-27.02) and anxiety (OR=3.39; 95% CI 1.55-7.41) were identified as influencing factors. As such, suicide risk groups of college freshmen are highly associated with ADHD, depression, and anxiety. Therefore, personal counseling and regular psychological tests of college freshmen will be provided to the high-risk suicide program to help students' psychological stability and adjustment to school life.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.111-117
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• 2016

The purpose of this study is to analyze the changes in turnover intention according to the level of Burn out and the mediating effect in fire officer. Higher levels of emotional labor and turnover intention resulted in higher levels of burn out(p<0.05). We used the logistic regression analysis to compare change of turnover intention according to the level of burn out. In logistic regression analysis, largest mediating factor were working days per week, the number of moving case per a day, physical condition, emotional labor and the odds(Likely to with high turnover intention) was down by 38.9% after adjustment for mediating factors. The results of this study indicate that emotional labor was negatively impact on burn out in fire officer. To reduce the burn out and the turnover intention, it is necessary to do more efforts to improve work environment (working days per week, the number of moving case per a day and emotional labor) and management personal factor(physical condition) for the fire office should be made to reduce such negative effects.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.1-6
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• 2020

The purpose of this study is to theoretically understand hope theory suggested by Snyder and confirm its utility in the school settings. We analyzed the survey data responded by general high school students to find clustering types of hope and mean difference of learning strategies by each type through ANOVA. Results are as follows. First, hope by cluster analysis resulted in four types. Second, hope and learning strategy showed statistically positive correlation. Especially two sub-variables of hope and meta-cognition had highest correlation. Researchers suggested the direction of a future study to investigate structural relation among hope profile, student achievement, adjustment, and etc.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.79-88
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• 1999

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the speed of adaptation and convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by square of the prediction error. The simulation results obtained using the new algorithm about noise canceller system and system identification are described. They are compared to the results obtained for other variable step size algorithm. function.

• The Journal of Industrial Distribution & Business
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• v.11 no.10
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• pp.17-25
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• 2020

Purpose: The purpose of this study is to narrow the target down to college students representing single-person households to identify the main attributes of their choice of Home Meal Replacement(HMR) and to look at the impact on satisfaction and repurchase intentions. Research design, data and methodology: An online survey was conducted for consumers who purchased HMR products at least once and a total of 264 questionnaires were used for demonstration analysis. The collected data have verified for validity and reliability between measurement variables through exploratory factor analysis and reliability analysis. Results: As a result, curiosity, economy, safety, and brand, which are HMR selection attributes that university students' value, have a significant impact on satisfaction, and satisfaction has a significant impact on the intention of repurchase, a variable of behavior. In addition, the adjustment effect of health value pursuit was significant only in safety attributes. Conclusions: This study divided the target group to examine what the HMR selection attributes of single-person college students are, the main consumer of HMR, and how selective attributes affect satisfaction and willingness to repurchase. In the process, we wanted to find out if there was a moderating effect on the health-oriented values in the dietary lifestyle.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.393-398
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• 2007

In this paper, we propose the development of Artificial Hippocampus Algorithm(AHA) which remodels a principle of brain of hippocampus. Hippocampus takes charge auto-associative memory and controlling functions of long-term or short-term memory strengthening. We organize auto-associative memory based 4 steps system (EC, DG CA3, and CA1) and improve speed of teaming by addition of modulator to long-term memory teaming. In hippocampus system, according to the 3 steps order, information applies statistical deviation on Dentate Gyrus region and is labeled to responsive pattern by adjustment of a good impression. In CA3 region, pattern is reorganized by auto-associative memory. In CA1 region, convergence of connection weight which is used long-term memory is learned fast a by neural network which is applied modulator. To measure performance of Artificial Hippocampus Algorithm, PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis) are applied to face images which are classified by pose, expression and picture quality. Next, we calculate feature vectors and learn by AHA. Finally, we confirm cognitive rate. The results of experiments, we can compare a proposed method of other methods, and we can confirm that the proposed method is superior to the existing method.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.223-230
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• 2009

For pulse trigger way and the energy injection rate according to PET ($Pause^{10-90}$ $Energy^{20-40}$ $Trigger^{1-7}$) function, indeed, human body condition, period of dormancy in this research about this back correctly adjustment possible and designed harmless micro carrying along style hair exclusion so that can design and manufacture and run special quality examination and Xenon flash lamp to crawl in human body. Because creating individual's skin model to do stable treatment by light transmission way by skin impedance and measure, must embody treatment special quality of most suitable that draw skin color, energy, wave length, approximately, transmission time, pulse delay etc. and want. Specially, saved standard of war treatment pulse modeling by skin impedance, and manufacture pulse modeling system of most suitable by skin subordinate, and embody suitable treatment pulse. Specially, embody as could do root of a hair exclusion being emitted in pulse form using multi wave length of 560nm, 590nm, 640nm, 755nm and embodied clinical data. If become research repletion furthermore little more, is seen that can approximate in commercialization.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.339-345
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• 2007

Video transcoding is a technique used to convert a compressed input video stream with an arbitrary format, size, and bitrate into a different attribute video stream different attributes to provide a efficient video streaming service for the customers is dispersed in the heterogeneous networks. Specifically, frames deletion occur in a transcoding scheme that exploits the adjustment of frame rate, and at this time, the loss in temporal relation among frames due to frame deletion is compensated for the prediction of motion estimation by reusing motion vectors in the would-be deleted frames. But the processing time for transcoding don't have an improvement as much as our expectation because transcoding is done only within the transcoder. So in this paper, we propose a new transcoding algorithm based on prediction period to improve transcoding-related processing time. For this, we also modify the existing encoder so as to adjust dynamically frame rate based on the prediction period and deletion period of frames. To check how the proposed algorithm works nicely, we implement a video streaming system with the new transcoder and encoder to which it is applied. The result of the performance test shows that the streaming system with proposed algorithm improve 60% above in processing time and also PSNR have a good performance while the quality of pictures is preserved.