• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7635-7647
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• 2015

The purpose of this study is modeling nursing competencies and reasoning out the core competencies, the ability for 20% of important actions for nursing jobs which can manage the rest 80% so that the competency-based nursing curriculum can be developed. A literature review of the vast studies regarding competencies was done to understand the concepts of competency-based curriculum, competency, and nursing competencies, identifying the relationships among each nursing competency categorized in accordance with those concepts. An exemplified concept map of core competencies for the competency-based nursing curriculum is suggested based on a thorough review of various competency modeling methodologies. The core competencies consist of base competency (theoretical/practical nursing knowledge and skills), practical competency (clinical judgment, patient education, communication, etc.), and personality competency (leadership, sense of responsibility, cooperation, etc.). The circular relationship among them can remain consistent through self-directed learning and critical thinking. Therefore, a nurse who have those core competencies is a knowledge worker, a self-directed learner, and also an effective, professional communicator. Further studies which solidify the concept of nursing competencies should be done, as well as the feedback procedures which evaluate the program outcomes and then reflect the evaluation results in the curriculum should be followed continuously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7801-7811
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• 2015

Nursing students do a variety of learning at the practice field during clinical practice. They can recognize the importance and effectiveness of nursing leader. The purpose of this study was to categorize the types by analyzing what are important aspects of nursing leader's role to make effective practice environment nursing students experienced from training course. This research was used Q methodology to understand how nursing students recognize deeply. Participants were involved 30 nursing students who have experienced nursing practices. Q samples included 36 statements gathered from interviews with students who experienced clinical practices and literatures regarding types of nursing leader's role. Furthermore, major factors were analyzed and categorized by using QUANL PC program. As a result of research, there are 4 types of nursing leader's role. The first type is "Maintaining justice and level-headed", the second type is "Creating environment for motivation", the third is "Respecting character and growing capacity up" and the fourth is "Relationship center through confidence". Through the research process, this study is about to make evidences by understanding role of nursing leader for effective environment of practice field.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.901-919
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• 2010

We have examined the perception and the knowledge of science-gifted students and general students in middle school level about high technology related to the science. The subjects of the investigation were 113 gifted students belonging to the universities' science-gifted education center in Busan or Ulsan, and 159 general students belonging to 2 middle schools in Busan. The survey was conducted with questionnaires on the perceptions concerning the high technology related to the science and the knowledge of a cellular phone without an antenna, and an LED(Light Emission Diode). The results of this survey concluded that the gifted students were more interested and aware of the high technology than the general students, these results are statistically significant. It has been found that there are significant differences between the gifted students and the general students in terms of the areas they want to learn, the source of information and the preferred learning method in advanced science and technology. Also, the gifted students were recognized to be better than general students in understanding an electromagnetic wave related to a cellular phone without an antenna, and a semiconductor connection with an LED.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.3
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• pp.17-27
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• 2010

This study aimed to identify the problems of college students in reading the literature and on the basis of the identified problems, to suggest the approaches to solve the problems. To this end, time required for reading passages, reading patterns, understanding, memory and reading habits and attitudes were analyzed with the freshmen in A university. In accordance with the analysis results, 58% of subjects was good and 42% was not sufficient on the basis of the averages in Scholastic Aptitude Test. Second, 77% of subjects had the good patterns but 23% showed certain problems in reading patterns. Third, 69% and 67% of subjects illustrated good results in the analysis on understanding and memory, respectively. However, 31% and 33% were evaluated as being on the general level or requiring efforts in the analysis on understanding and memory, respectively. Next, according to the analysis on reading habits and attitudes, 77% had no problems but 23% required improvement. For solving the problems identified through the analysis, it is recommended to develop the scientific and standardized evaluation tools for evaluating the reading ability of college students. Second, it is necessary to evaluate the reading ability, habit and attitude during the screening process for admission or after admission. Finally, it is required to operate the Fundamental Academic Ability Learning Center(tentative name) to improve the ability of students who show the insufficient results in evaluation.

• Journal of agriculture & life science
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• v.45 no.6
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• pp.213-226
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• 2011

This study was performed to investigate the effect of essential oils and ethanolic extracts of approximately 650 plant species on acetylcholine esterase (AChE) enzyme activity using Ellman's colorimetric method in 96-well microplates. The results showed that the ethanolic extracts from twig of Sophora subprostrata, twig of Phellodendron amurense, seed of Corylopsis coreana, and essential oil (EO) from Citrus paradisi, Cupressus sempervirens, Ocimum basilicum, Pinus sylvestris and Rosmarinus officinalis inhibited more than 80% of AChE activity. Among these, EO from Pinus sylvestris, C. sempervirens and C paradisi exhibited higher values of AChE inhibitory activity, which were 75, 84 and 99% at a concentration of 50 ug/ml, respectively. Finally, EO from C paradisi (grapefruit, GEO) showed the highest inhibitory activity towards AChE, which showed 91% of inhibition at a concentration of 20 ug/ml. We also examined the anti-dementia effects of GEO in mouse by passive avoidance test and Morris water maze test. The model mouse (male, ICR) of dementia (negative control) was induced by administration of scopolamine (1 mg/kg body weight). The latency time of sample group administrated with GEO (100 mg/kg, p.o.) increased significantly as compared with negative control on passive avoidance test. There were significant recovery from the scopolamine-induced deficits on learning and memory in water maze test through daily administrations with GEO (100 mg/kg, p.o.). From these results, we conclude that GEO treatment might enhance the cognitive function, suggesting that the EO of C. paradis may be a potential candidate for improvement of perceptive ability and dementia.

• Korean Journal of Comparative Education
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• v.27 no.1
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• pp.247-284
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• 2017

The purpose of this study is to analyze firm's motivation of participating and investing in apprenticeship in Germany and Korea, and to investigate institutional factors influencing firm's motivation. By comparing institutional factors of the two countries, it aims to drawing out policy implications for improving Korean apprenticeship. The main method for data collection was comprehensive literature review on international organizations, each countries' government and research institutes' policy materials, statistical data, research outputs and media resources related to each countries' apprenticeship. Considering whether firm's motivation for participating and investing in apprenticeship is production-oriented or investment-oriented, Germany is more inclined to investment motivation with firm's covering net cost during apprenticeship period. On the other hand, Korea is more inclined toward production orientation with firm's expectation of gaining net profit during the training period. Why is firm's training motivation different in these two countries? The author tried to find the reason from the difference of institutional factors of the countries by dividing institutional factors into 4 categories: context(tripartite relations, legal framework), input (flexibility of the system, government incentive), process(training contents, training duration, quality assurance), and output(completion/retention rate, apprentice's productivity). The key implication from the comparative analysis of institutional factors is that it is necessary to enforce companies to have "accountability" on the minimum critical elements, but also to ensure them to have "autonomy" on the rest of the elements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.40-46
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• 2019

The purpose of this study is to investigate the effect of positive psychological capital on re-employment attitudes of youth in their 20s dealing with an unemployment rate of more than 10%. The effect of positive psychological capital on attitudes for re-employment was analyzed by domain, and is based on variables of positive psychological capital composed of self-efficacy, hope, resilience, and optimism. As a result, hope (3.64) was the highest on the scale; however, resilience (at 3.37) was the lowest. In the analysis of positive psychological capital, the university graduate group (3.89) was the highest. But, the high school graduate group (3.25) was the lowest. In the results for re-employment attitude based on education level, the university graduate group (4.93) was the highest, but the high school graduate group (3.80) was lowest. The main variables influencing re-employment attitude were (in order): hope, optimism, self-efficacy, and resilience. These factors have an explanatory power for the four variables of around 25%. Overall, young adults (in their 20s) have higher levels of positive psychological capital because they have a higher education level. Also, higher educated re-employed applicants have higher positive psychological capital and attitudes for re-employment, compared to the other groups.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.165-172
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• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• The Journal of Bigdata
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• v.6 no.1
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• pp.51-62
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• 2021

In the field of medical artificial intelligence, there have been a lot of researches on disease prediction and classification algorithms that can help doctors judge, but relatively less interested in artificial intelligence that can help medical consumers acquire and judge information. The fact that more than 150,000 questions have been asked about which hospital to go over the past year in NAVER portal will be a testament to the need to provide medical information suitable for medical consumers. Therefore, in this study, we wanted to establish a classification model that classifies 8 medical subjects for symptom text directly described by patients which was collected from NAVER portal to help consumers choose appropriate medical subjects for their symptoms. In order to ensure the validity of the data involving patients' subject matter, we conducted similarity measurements between objective symptom text (typical symptoms by medical subjects organized by the Seoul Emergency Medical Information Center) and subjective symptoms (NAVER data). Similarity measurements demonstrated that if the two texts were symptoms of the same medical subject, they had relatively higher similarity than symptomatic texts from different medical subjects. Following the above procedure, the classification model was constructed using a ridge regression model for subjective symptom text that obtained validity, resulting in an accuracy of 0.73.