• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.215-229
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• 2024

The purpose of this study was to explore various factors that affect the organizational commitment of health teachers' behavioral characteristics and explain the causal relationship between each factor. As an exploratory study, the subjects were about 500 people working as health teachers. A survey was conducted, and 190 responses were collected. Descriptive statistics were analyzed using SPSS, and the measurement model and hypotheses were tested using structural equation modeling. As a result of the analysis, the behavioral characteristics of health teachers were found to have a positive effect on their self-efficacy, and the behavioral characteristics and self-efficacy were found to have a positive effect on emotional commitment. In addition, health teachers' self-efficacy has a positive effect on emotional commitment, which means that rather than their behavioral characteristics having a direct effect on emotional commitment, their behavioral characteristics indirectly affect emotional commitment through a mediator called self-efficacy. It shows that it has an impact. In particular, it was confirmed that the school nurse's level of awareness of the importance of the task affected self-efficacy and emotional commitment. The implication of this study is that it explained the phenomenon of transfer of their behavioral characteristics to organizational commitment by empirically revealing that the competency, or behavioral characteristics, of health teachers are a factor affecting organizational commitment through self-efficacy. The goal is to empirically demonstrate that awareness of task importance, a job characteristic, affects self-efficacy and organizational commitment. The results of the study are expected to be able to suggest directions for capacity building and operation of health teachers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.87-101
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• 2024

This study aims to provide insights for the efficient utilization of resources by analyzing the entrepreneurship support efficiency of Korean universities. To identify the factors influencing the number of entrepreneurs, which is the primary goal of university entrepreneurship support, a multiple regression analysis was conducted, identifying five effective independent variables. Using these five identified independent variables as input variables and the number of entrepreneurs as the output variable, the DEA method was used to analyze the efficiency of entrepreneurship support for each university as of 2023. The analysis of 150 four-year universities in Korea showed that nine universities exhibited complete efficiency in both CCR and BCC models. Among the remaining 141 universities that showed inefficiency, the cause was scale for five universities, technology for two universities, and both scale and technology for 134 universities. Regarding the returns to scale, nine universities exhibited CRS, 79 exhibited IRS, and 62 exhibited DRS. Additionally, reference groups that could serve as benchmarks for improving the efficiency of inefficient universities were identified, and target values(projections) for each variable to achieve efficiency were also presented. Despite the limitations of the DEA model, this study helps each university identify the causes of inefficiency in their entrepreneurship support and derive specific improvements to enhance efficiency. This facilitates more efficient resource management and can positively impact the ultimate goals of university entrepreneurship support, such as regional economic development and job creation.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.80-81
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• 2012

Recently, one of the critical issues in the etching processes of the nanoscale devices is to achieve ultra-high aspect ratio contact (UHARC) profile without anomalous behaviors such as sidewall bowing, and twisting profile. To achieve this goal, the fluorocarbon plasmas with major advantage of the sidewall passivation have been used commonly with numerous additives to obtain the ideal etch profiles. However, they still suffer from formidable challenges such as tight limits of sidewall bowing and controlling the randomly distorted features in nanoscale etching profile. Furthermore, the absence of the available plasma simulation tools has made it difficult to develop revolutionary technologies to overcome these process limitations, including novel plasma chemistries, and plasma sources. As an effort to address these issues, we performed a fluorocarbon surface kinetic modeling based on the experimental plasma diagnostic data for silicon dioxide etching process under inductively coupled C4F6/Ar/O2 plasmas. For this work, the SiO2 etch rates were investigated with bulk plasma diagnostics tools such as Langmuir probe, cutoff probe and Quadruple Mass Spectrometer (QMS). The surface chemistries of the etched samples were measured by X-ray Photoelectron Spectrometer. To measure plasma parameters, the self-cleaned RF Langmuir probe was used for polymer deposition environment on the probe tip and double-checked by the cutoff probe which was known to be a precise plasma diagnostic tool for the electron density measurement. In addition, neutral and ion fluxes from bulk plasma were monitored with appearance methods using QMS signal. Based on these experimental data, we proposed a phenomenological, and realistic two-layer surface reaction model of SiO2 etch process under the overlying polymer passivation layer, considering material balance of deposition and etching through steady-state fluorocarbon layer. The predicted surface reaction modeling results showed good agreement with the experimental data. With the above studies of plasma surface reaction, we have developed a 3D topography simulator using the multi-layer level set algorithm and new memory saving technique, which is suitable in 3D UHARC etch simulation. Ballistic transports of neutral and ion species inside feature profile was considered by deterministic and Monte Carlo methods, respectively. In case of ultra-high aspect ratio contact hole etching, it is already well-known that the huge computational burden is required for realistic consideration of these ballistic transports. To address this issue, the related computational codes were efficiently parallelized for GPU (Graphic Processing Unit) computing, so that the total computation time could be improved more than few hundred times compared to the serial version. Finally, the 3D topography simulator was integrated with ballistic transport module and etch reaction model. Realistic etch-profile simulations with consideration of the sidewall polymer passivation layer were demonstrated.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.51-60
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• 2003

In the radical char]go of the business environments that the existing facilities can not guarantee the business-frosts anymore, enterprises have been importing ERP system. In Korea, Sam-sung Electronics did it for the first tin in the latter half of 1994 and other enterprises succeeded. Currently, government and public enterprises as well as most of the large enterprises are employing ERP system to sharpen the competitiveness and to win the business transparency. On the other hand, it is harder for small and medium enterprises shaded by the large enterprises to be well-equipped with information system such as ERP, because they have already suffered from chronic financial difficulties and shortage of many resources. Most of all, they prefer the short-term project that does not need much tine for them to make decisions and to carry out fully. Grounded on the above factors, in this work, I suggest the suitable ERP model for the small and medium enterprises and the successful importing process of ERP, which is derived from the previous researches made by other masters' thesis. If necessary information and human resources are interchanged pertinently between local education institute and small and medium enterprise, the latter could not only deal with the confronted difficulties successfully inside and outside but attain the goal of being proficient in up-to-minute high technology. Besides, giving the students the opportunity of researching into the practice of the business they have not ever known, local universities could help their students accumulate knowledges and acquire ideas which could not be achieved in pure academic studies. When the above-mentioned procedure is over, the students might get the intellectual faculty to ponder on the future more concretely and enter a profession more carefully. In the result, we would raise up the percentage of the employment among the graduates. And active participation of university professors is the last important factor that assists the small and medium enterprises for introducing ERP system successfully. Their scholarly attainments play an important role in strengthening local economy and make the business competitiveness balanced between the capital and the local economy.

• Journal of Korean Home Economics Education Association
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• v.32 no.2
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• pp.59-76
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• 2020

The purpose of this study was to develop and evaluate the teaching/learning process plan of 'housing culture and practical space use' for home economics in middle school according to the problem based learning(PBL) model. The plan consisting of 4-lessons has been developed and implemented following the steps of ADDIE model. Various activity materials (4 scenarios, 6 individual activity sheets, 10 reading texts, and 5 working resources) and visual materials (4 sets of ppt and 4 moving pictures) as well as questionnaire were developed for the 4-session lessons. The plans were implemented to a single class of 21 junior students at H middle school in rural area, Kyeongnam, from 1^st to 12^th of April, 2019. Students highly enjoyed and were satisfied with the whole 4-lessons in aspects such as understanding of the contents, adequacy of materials and activities, and usefulness in one's own daily life. Additionally, they have more actively participated in the lessons than usual and even interested in learning more of such lessons. Students also reported that they highly accomplished the goal of each lesson as well as overall objectives. They showed interest in the major part of PBL lesson such as scenario and group activities. And they engaged themselves in drawing the share housing space plan with '5D planner' web program which they described as the best part of the lessons. The teaching/learning process plan developed in this study may be used as a theme of maker education, which is emerging these days. It can be concluded that the PBL teaching/learning process plans for 'housing values and practical space use' would contribute to improving students' attitude on living with others and ability to manage one's individual life.

• Clean Technology
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• v.23 no.3
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• pp.286-293
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• 2017

The goal of this paper was to improve the performance of the adsorbent to remove $H_2S$. Pellet type adsorbents were prepared by using four kinds of materials ($Fe_2O_3$, $Ca(OH)_2$, Activated carbon, $Al(OH)_2)$ for use as a basic carrier. As the results of $H_2S$ adsorption tests, $Fe_2O_3$ and Activated Carbon improved the adsorption performance of $H_2S$ by 1.5 ~ 2 times, and $Ca(OH)_2$ and $Al(OH)_2$ showed no effect on $H_2S$ adsorption performance. Four basic materials were as carriers, and 5 wt% of KI, KOH and $K_2CO_3$ were added on the carriers, respectively. As the results of $H_2S$ adsorption tests, adsorbent containing $K_2CO_3$ showed the best performance. As a result of $H_2S$ adsorption test with varying $K_2CO_3$ content from 5 to 30 wt%, it was confirmed that adsorption performance was increased up to 20 wt% of $K_2CO_3$ and adsorption performance decreased to 30 wt%. The $H_2S$ adsorption performance was modeled by using Thomas model with varying $K_2CO_3$ contents and the results were used for the adsorption tower design. It was shown that the experimental values and the simulated values were in good agreement with the contents range of $K_2CO_3$ up to 20 wt%. Based on these results, it is expected that not only the adsorption performance of $H_2S$ adsorbent is improved but also life time of the adsorbent is increased.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.25-39
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• 2015

$CO_2$ geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing $CO_2$ safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of $CO_2$ storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the $CO_2$ sequestration initiative. More detailed characterization of the geological storage and the simulation of $CO_2$ migration might be an essential for the CCS demonstration.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.25-51
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• 2008

Researchers have been continuously interested in the adoption of information technology (IT) since it is of great importance to the information systems success and it is also an important stage to the success. Adoption alone, however, does not ensure information systems success because it does not necessarily lead to achieving organizational or individual objectives. When an organization or an individual decide to adopt certain information technologies, they have objectives to accomplish by using those technologies. Adoption itself is not the ultimate goal. The period after adoption is when users continue to use IT and intended objectives can be accomplished. Therefore, continued IT use in the post-adoption period accounts more for the accomplishment of the objectives and thus information systems success. Previous studies also suggest that continued IT use in the post-adoption period is one of the important factors to improve long-term productivity. Despite the importance there are few empirical studies focusing on the user behavior of continued IT use in the post-adoption period. User behavior in the post-adoption period is different from that in the pre-adoption period. According to the technology acceptance model, which explains well about the IT adoption, users decide to adopt IT assessing the usefulness and the ease of use. After adoption, users are exposed to new experiences and they shape new beliefs different from the thoughts they had before. Users come to make decisions based on their experiences of IT use whether they will continue to use it or not. Most theories about the user behaviors in the pre-adoption period are limited in describing them after adoption since they do not consider user's experiences of using the adopted IT and the beliefs formed by those experiences. Therefore, in this study, we explore user's experiences and beliefs in the post-adoption period and examine how they affect user's intention to continue to use IT. Through deep literature reviews on the construction of subjective beliefs by experiences, we draw three meaningful constructs which theoretically have great impacts on the continued use of IT: perceived habit, confirmation, and computer self-efficacy. Then, we examine the role of the subjective beliefs on the cognitive/affective attitudes and intention to continue to use that IT. We set up a research model and conducted survey research. Since IT use implies interactions among a user, IT, and a task, we carefully selected the sample of users using same/similar IT to perform same/similar tasks, to exclude unwanted influences of other factors than subjective beliefs on the IT use. We also considered that the sample of users were able to make decisions to continue to use IT volitionally or at least quasi-volitionally. For each construct, we used measurement items recognized for reliability and widely used in the previous research. We slightly modified some items proper to the research context and a pilot test was carried out for forty users of a portal service in a university. We performed a full-scale survey after verifying the reliability of the measurement. The results show that the intention to continue to use IT is strongly influenced by cognitive/affective attitudes, perceived habits, and computer self-efficacy. Confirmation affects the intention to continue indirectly through cognitive/affective attitudes. All the constructs representing the subjective beliefs built by the experiences of IT use have direct and/or indirect impacts on the intention of users. The results also show that the attitudes in the post-adoption period are formed, at least partly, by the experiences of IT use and newly shaped beliefs after adoption. The findings suggest that subjective beliefs built by the experiences have deep impacts on the continued use. The results of the study signify that while experiencing IT in the post-adoption period users form new beliefs, attitudes, and intentions which may be different from those of the pre-adoption period. The results of this study partly demonstrate that the beliefs shaped by the behaviors, those are the experiences of IT use, influence users' attitudes and intention. The results also suggest that behaviors (experiences) also change attitudes while attitudes shape behaviors. If we combine the findings of this study with the results of the previous research on IT adoption, we can propose a cycle of IT adoption and use where behavior shapes attitude, the attitude forms new behavior, and that behavior shapes new attitude. Different from the previous research, the study focused on the user experience after IT adoption and empirically demonstrated the strong influence of the subjective beliefs formed in the post-adoption period on the continued use. This partly confirms the differences between attitudes in the pre-adoption and in the post-adoption period. Users continuously change their attitudes and intentions while experiencing (using) IT. Therefore, to make users adopt IT and to make them use IT after adoption is a different problem. To encourage users to use IT after adoption, experiential variables such as perceived habit, confirmation, and computer self-efficacy should be managed properly.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.3
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• pp.26-45
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• 2019

Objective : The purpose of this study is to develop educational goals, training content, and training methods for the intervention course of the Korean Academy of Sensory Integration (KASI) and to conduct competency-based intervention courses based on the competency model for sensory integration intervention. Methods : This study was conducted on work therapists who participated in the 2019 intervention course of KASI. In the first phase, educational needs were analyzed to set goals for the interventional course. In the second phase, a meeting of researchers drafted the intervention course education program and the methods of education, and the intervention course was conducted. In the third phase, the changes in educational satisfaction and performance level pre- and post-intervention course for each competency index were investigated. Results : The educational goals of "learning and applying the clinical reasoning process of sensory integration intervention" and "intervention by applying the principle of sensory integration intervention" were set after reflecting on the results of the analysis of the educational requirements. The length of the competency-based intervention course was 42 hours. The average education satisfaction level of participants in the arbitration process was 4.48±0.73, and the average education satisfaction level of the supervisor was 3.92±0.71. In both groups, the most satisfying curriculums were the data-driven decision-making process and the intervention goal-setting lecture. But the satisfaction level of was the lowest. Before and after the intervention course, there were significant changes in the performance of the two behavioral indicators of the analytic skills in the expertise competency cluster of the competency model. Conclusion : This study is meaningful in that it conducted a survey of educational needs, the development and implementation of an educational curriculum, and an education satisfaction survey through systematic courses necessary for education development.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.