• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.216-223
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• 2019

This study was conducted to identify the effects of patient safety competency on patient safety management practice by nursing students and provide basic data for the development of the program to improve patient safety management practice. Participants were 293 fourth year nursing students who had clinical practice as student nurses for more than one year. Data were collected from April 26 to May 9, 2018. Collected data were analyzed for frequency, percentage, mean, standard deviation, t-test, ANOVA, Pearson' s correlation coefficient, and multiple regression with SPSS/WIN 24.0 computer program. Nursing students' patient safety competency was an average $2.90{\pm}0.38$ points (patient safety knowledge $2.68{\pm}0.65$; patient safety skills $3.26{\pm}0.56$; patient safety attitudes $2.75{\pm}0.40$). The average core of management practices to patient safety recorded $4.13{\pm}0.57$ points. In terms of the correlation among subjects' patient safety knowledge, skills, attitudes and patient safety management practices, significant correlation existed between skills and management practices (r=.337, p<.001), attitudes and management practices (r=-.150, p =.010), knowledge and management practices (r=.171, p=.003). Regression analysis revealed that 15.7% of the variance in patient safety management practice by nursing students could be explained by patient safety skills (${\beta}=.307$, p<.001), patient safety accident experience of Fire (${\beta}=-.127$, p=.026), patient safety attitudes (${\beta}=-.121$, p=.026), and patient safety accident experience of patient education (${\beta}=-.119$, p=.034). Additional studies to determine the various factors affecting patient safety management practice of nursing students and to develop educational program for increasing patient safety management practice should be conducted.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.61-68
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• 2018

In this paper, we propose a method of character detection by analyzing image enhancement and character type to detect characters in natural images that can be acquired in everyday life. The proposed method emphasizes the boundaries of the object part using the unsharp mask in order to improve the detection rate of the area to be recognized as a character in a natural image. By using the boundary of the enhanced object, the character candidate region of the image is detected using Maximal Stable Extermal Regions (MSER). In order to detect the region to be judged as a real character in the detected character candidate region, the shape of each region is analyzed and the non-character region other than the region having the character characteristic is removed to increase the detection rate of the actual character region. In order to compare the objective test of this paper, we compare the detection rate and the accuracy of the character region with the existing methods. Experimental results show that the proposed method improves the detection rate and accuracy of the character region over the existing character detection method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.139-148
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• 2019

Fostering science-gifted individuals are very important for the future of the nation, and it is especially important to cultivate information-gifted individuals in the age of the fourth industry. There is no standardized curriculum for each gifted education center of the University. Therefore, in this study, we analyzed how effective the curriculum developed on the basis of computing thinking is to affect the characteristics of the information-gifted individuals. The curriculum developed on the components of computing thinking was applied to the information-gifted students of K University. In order to verify the effectiveness of the curriculum, we developed a creative personality test and an intrinsic motivation test, and conducted tests before and after the training. We compared pre-post test results by t-test with R program. The creative personality test consisted of 36 items with 6 factors: risk-taking, self - acceptance, curiosity, humor, dominance, and autonomy. The intrinsic motivation test consisted of 20 items with 5 items: curiosity and interest oriented tendency, challenging learning task preference orientation, independent judgment dependency propensity, independent mastery propensity, and internal criterion propensity. The effect of the curriculum on the creative personality of the experimental group was significant (0.009, 0.05). The significance level of the intrinsic motivation was 0.056 and was not significant at the 0.05 level of significance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.186-188
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• 2014

In recent years, domestic as well as LTE wireless network of Wi-Fi and most used. In addition, mobile-intensive services that used mainly in our society makes it easier, SNS, application (APP), and file downloads. As such, the amount of data requested, while living at the time of mobile users will want to be safe from the earliest. And the wireless network communications mortality (3G, 4G (LTE), LTE-A) and Wi-Fi (802.11 n-2.4 G H z z H a c-5, 802.11 G), and users are mainly used in the death 4G (LTE), communication Wi-Fi, 802.11 n-2.4 GHz are used most frequently. As above, use the wireless network in order to safely and quickly developed the technology of the Li-Fi. Li-Fi light (visible light) technology to communicate with, and Wi-Fi (802.11 n-2.4 G z H) 100 times faster, LTE-A 66 times faster. However, the current Li-Fi to commercialise the big issue exists. In this paper, there are a lot of existing problems in the commercialization of Li-Fi being used in Wi-Fi, and a comparative analysis.

• Korean Journal of Biological Psychiatry
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• v.26 no.1
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• pp.22-31
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• 2019

Objectives Previous studies have revealed inconsistent results on amygdala volume in adult bipolar disorder (BD) patients compared to healthy controls (HC). Since the amygdala encompasses multiple subregions, the subtle volume changes in each amygdala nucleus might have not been fully reflected in the measure of the total amygdala volume, causing discrepant results. Thus, we aimed to investigate volume changes in each amygdala subregion and their association with subtypes of BD, lithium use and clinical status of BD. Methods Fifty-five BD patients and 55 HC underwent T1-weighted structural magnetic resonance imaging. We analyzed volumes of the whole amygdala and each amygdala subregion, including the anterior amygdaloid area, cortico-amygdaloid transition area, basal, lateral, accessory basal, central, cortical, medial and paralaminar nuclei using the atlas in the FreeSurfer. The volume difference was analyzed using a one-way analysis of covariance with individual volumes as dependent variables, and age, sex, and total intracranial volume as covariates. Results The volumes of whole right amygdala and subregions including basal nucleus, accessory basal nucleus, anterior amygdaloid area, and cortico-amygdaloid transition area in the right amygdala of BD patients were significantly smaller for the HC group. No significant volume difference between bipolar I disorder and bipolar II disorder was found after the Bonferroni correction. The trend of larger volume in medial nucleus with lithium treatment was not significant after the Bonferroni correction. No significant correlation between illness duration and amygdala volume, and insignificant negative correlation were found between right central nucleus volume and depression severity. Conclusions Significant volume decrements of the whole amygdala, basal nucleus, accessory basal nucleus, anterior amygdaloid area, and cortico-amygdaloid transition area were found in the right hemisphere in adult BD patients, compared to HC group. We postulate that such volume changes are associated with altered functional activity and connectivity of amygdala nuclei in BD.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.127-138
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• 2019

The data response speed is a critical issue of cloud services because it directly related to the user experience. As such, the in-memory database is widely adopted in many cloud-based applications for achieving fast data response. However, the current implementation of the in-memory database is mostly based on the linked list-based hash table which cannot guarantee the constant data response time. Thus, cuckoo hashing was introduced as an alternative solution, however, there is a disadvantage that only half of the allocated memory can be used for storing data. Subsequently, bucketized cuckoo hashing (BCH) improved the performance of cuckoo hashing in terms of memory efficiency but still cannot overcome the limitation that the insert overhead. In this paper, we propose a data management solution called Wall Cuckoo which aims to improve not only the insert performance but also lookup performance of BCH. The key idea of Wall Cuckoo is that separates the data among a bucket according to the different hash function be used. By doing so, the searching range among the bucket is narrowed down, thereby the amount of slot accesses required for the data lookup can be reduced. At the same time, the insert performance will be improved because the insert is following up the operation of the lookup. According to analysis, the expected value of slot access required for our Wall Cuckoo is less than that of BCH. We conducted experiments to show that Wall Cuckoo outperforms the BCH and Sorting Cuckoo in terms of the amount of slot access in lookup and insert operations and in different load factor (i.e., 10%-95%).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.144-151
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• 2019

The purpose of this study was to investigated of the pre service teacher's information availability and concern and perception of coding education for young children. The subjects were 230 pre service teacher attending a A college micro politan city Questionnaires. The collected data were analyzed by ANOVA and Pearson's correlation coefficient analysis with SPSS Program. The results were as follows: First, the pre service teacher's information availability was smart phone usage levels that the most of all and the next was computer usage levels. Concern of coding education for young children that consequence concern was the highest and the next that collaboration concern, personal concern, information concern, refocusing concern, management concern. The other side unconcerned was most of least. Perception of coding education for young children that necessity perception, content perception, environmental perception was the over of mean. But operational perception was the low. Second, The information awareness, smart phone usage levels as each domain of information ability, usefulness of use was positively associated with Personal concern. But the information ability were negatively correlated with management concern. The information awareness was associated with necessity of coding education. The useful and ease of use of education were positively associated with content coding education.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.153-158
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• 2019

The purpose of this study is to compare and analyse the differences between a customized small finger made by 3D printing technology, a real small finger, and the other made from plaster of an orthotic company. The areas and the volumes of each cross-section were measured by Computer tomography(CT) and a 3D scanner and analysis of variance was performed to find out the differences of each shape. The areas of the point of 15.69mm, Distal Interphalangel Joints, were measured 30 times respectively using the caliper toll function of Picture Archiving Communication System(PASC) program. The volumes were measured by Configure Units of Meshmixer Program. There was no significant difference in the areas between three of them and there was 0.2 mm gap in the volume, which was more than the significance probability. Therefore, the result of this study shows the availability of finger orthoses made by 3D printing technology in the medical field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.