• Journal of Adhesion and Interface
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• v.22 no.1
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• pp.1-7
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• 2021

The importance of high capacity energy storage devices has recently emerged for stable power supply through renewable energy generation. From this point of view, the Na-air battery (NAB), which is a next-generation secondary battery, is receiving huge attention because it can realize a high capacity through abundant and inexpensive raw materials. In this study, activated carbon-based catalysts for hybrid type Na-air batteries were prepared and their characteristics were compared and analysed. In particular, from the viewpoint of resource recycling, activated carbon (Orange-C) was prepared using discarded orange peel, and performance was compared with Vulcan carbon, which is widely used. In addition, a Pt/C catalyst (homemade-Pt/C, HM-Pt/C) was synthesized using a modified polyol method to check whether the prepared activated carbon can be used as a supported catalyst, and a commercial Pt/C catalyst (Commercial Pt/C) and electrochemical performance were compared. The prepared Orange-C exhibited a typical H3 type BET isotherm, which is evidence that micropore and mesopore exist. In addition, in the case of HM-Pt/C, it was confirmed through TEM analysis that Pt particles were evenly distributed on the activated carbon supported catalyst. In particular, the HM-Pt/C-based NAB showed the smallest voltage gap (0.224V) and good voltage efficiency (92.34%) in the 1st galvanostatic charge-discharge test. In addition, the cycle performance test conducted for 20 cycles showed the most stable performance.

• 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.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.89-100
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• 2021

The National Cyber Capability Assessment(NCCA) could be used as meaningful information for improving national cyber security policy because it provides information on the elements necessary for strengthening national cyber capabilities and the level of each country. However, there were few studies on improving cyber capabilities using the NCCA result in Korea. Therefore, we analyzed the result of National Cyber Power Index(NCPI) conducted by Belfer Center of Harvard Univ. by applying modified-IPA method to derive cybersecurity policy agendas for Korea. As a result, the need to set agendas on surveillance and offensive cyber capability and improve the effectiveness of policy implementation for intelligence and defense was drawn. Moreover, we suggested need for in-depth study of each policy agenda deduced from preceding research data as a future tasks. And it is expected to increase practical use of NCCA for domestic policy analysis by developing and using our own NCCA model which considered analysis framework proposed in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.687-695
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• 2021

With the recent occurrence of large-scale earthquakes in Korea, the importance of seismic design has greatly increased. Seismic design standards stipulate that dynamic time history analysis be performed for important or special structures. In the seismic analysis and design of such structures, determining a rational design input seismic wave is a very important factor in ensuring the reliability of the analysis and design. In the seismic design standards, rational design seismic waves must reflect the characteristics of the area (fault) and satisfy the design response spectrum for each seismic performance level. This requirement can be partially satisfied by modifying the actual seismic wave measured in the area (fault) according to the design response spectrum. In this study, a method of correcting and generating seismic wave time histories according to the design response spectrum based on actual measured seismic waves using the harmonic wavelet transform was proposed. To examine the applicability of the proposed technique, the technique was applied to earthquakes of magnitude 5.8 and 5.4, respectively, that occurred in Gyeongju (2016) and Pohang (2017), and the seismic wave time histories corresponding to the design response spectrum were modified and generated.

• Membrane Journal
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• v.19 no.4
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• pp.341-347
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• 2009

Nanohybrid based on environmentally friendly and biodegradable polymer, poly propylene carbonate (PPC) and cloisite 20B (PPC/C-20B) have been synthesized by solution blending method and their morphology, thermal and water absorption properties have been evaluated. The structure of PPC/C-20B nanohybrid was confirmed by X-ray diffraction (XRD). The thermal property of PPC and PPC/C-20B nanohybrid were investigated by thermal gravimetric analysis (TGA) and differential scanning calorimetric (DSC). The experimental results demonstrated that nanohybrid showed the highest thermal stability in TGA and DSC. TGA tests revealed that the thermal decomposition temperature ($T_{d50%}$) of the nanohybrid increased significantly, being $23^{\circ}C$ higher than that of pure PPC while DSC measurements indicated that the introduction of 5 mass% of clay increased the glass transition temperature from 21 to $30^{\circ}C$. Further the water absorption capacity of the PPC was significantly decreased by the incorporation of clay. Water absorption cause degradation of the coating by the moistures and affect the physical and mechanical performance. This result indicates that organic modifiers have effect on thermal and water absorption capacity of PPC and are of importance for the practical process and application of PPC.

• Journal of muscle and joint health
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• v.7 no.1
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• pp.102-130
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• 2000

The aims of this study were to understand and to predict the determinant factors affecting the exercise behaviors and physical fitness by testing the Ponder's health promotion model, and to help the patients with rheumatoid arthritis and osteoarthritis perform the continuous exercise program, and to help them maximize the physical effect such as muscle strength. endurance, and fuctional status and mental effects including self efficacy and quality of life, and improve the physical and mental wellbeing, and to provide a basis for the nursing intervention strategies. We analyzed the clinical records of 208 patients with rheumatoid arthritis and degenerative arthritis who visited the outpatient clinics at H university hospital in Seoul between October 5, 1999 and October 24, 1999. Data were composed of self reported questionnaire and good of fitness score which were obtained by pedalling the ergometer of bicycle for 9 minutes. SPSS Win 8.0 and Window LISREL 8.12a were used for statistical analysis. 24 Of 54 hypothetical paths were supported in modified model, which was considered as a proper model with improved fit index. The physical fitness was directly influenced by exercise participation behavior and education level, and indirectly by physical fitness, while fatigue, physical disability, pastexercise behavior, life-style, self-efficacy, which explained 20% of physical fitness. The exercise participation were directly influenced by perceived benefits and self-efficacy, and indirectly influenced by life-style, fatigue and physical disability, and directly and indirectly by past exercise behavior, which explained 53% of exercise participation. Exercise score were directly affected by perceived health status, perceived benefits, self efficacy, and past exercise behavior, and were indirectly affected by fatigue, physical disability, and life-style, which explained 50%. Perceived health status were directly influeced by level of education, depression, sleep disorder, and physical disability, which explained 34% of perceived health status. Perceived benefit was directly influenced by fatigue, sleep disorder, physical disability, and life-style, which explained 45%. Perceived barriers was directly influenced by fatigue, sleep disorder, and lifestyle, which explained 9%. Self- efficacy was directly influenced by fatigue, physical disability, past exercise behavior, and level of education, which explained 61%. In conclusion, important variables for physical fitness were exercise participation and level of education, and variables affecting exercise participation were perceived self-efficacy, benefits, and past exercise behavior. Perceived self-efficacy of exercise was a significant predictor of exercise participation. Life-style, fatigue, and physical disability showed direct effects on perceived benefit, perceived barriers, and self-efficacy, and indirect effects on exercise behavior. Therefore, disease related factor should be minimized for physical performance and well being in nursing intervention for patients with rheumatoid arthritis, and plans to promote and continue exercise should be soaked to reduce disability. In addition, Exercise program should be planned and performed by the exact evaluation of exercise according to the ability of the patients and the contents to improve the importance of exercise and self efficacy in self control program, dedicated educational program should be involved.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.95-112
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• 2012

The research evaluated the effects of the improvements in scientific inquiry for elementary school students and focused on the development and application of the explicit and reflective learning strategy through observation and classification. The explicit and reflective learning strategy was modified and completed with the review of the experts after the development of the draft based on the theoretical approach. The students were evaluated for their academic achievements in scientific inquiry skills before and after taking the course. The results were as follows: First, the steps of the developed learning strategy (1) to motivate, (2) to explore reflectively, (3) to guide explicitly, (4) to inquire explicitly, and (5) to verify reflectively were set to reflect the verification. Second, the results of applying the developed model to the lessons based on the quantitative analysis was effective for observation and classification skills in the quest for improved performance of the whole (the sum of observation and classification, inquiry skills) and the observed features, but there was no effect on classification. Also, the lessons applied the developed teaching strategy and showed effectiveness in improving academic achievement. Particularly in analyzing the relationship between the academic achievement and exploration capabilities, in order to improve academic achievement, the importance of improving inquiry skills was found. Third, the qualitative analysis of teaching and learning strategy developed by applying the lessons of this teacher guide and small group activities through the explicit and reflective observation and classification of the student learning activities showed the significant improvement of ability of the scientific inquiry skills. In addition to the improvement in the abilities of the classification showed after the formation of the most basic observation skills of the scientific inquiry.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.27-55
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• 2008

Due to the increasing and intensifying competition in the Internet shopping market, it has been recognized as very important to develop an effective policy and strategy for acquiring loyal customers. For this reason, web site designers need to know if a new Internet shopping mall(ISM) will be accepted. Researchers have been working on identifying factors for explaining and predicting user acceptance of an ISM. Some studies, however, revealed inconsistent findings on the antecedents of user acceptance of a website. Lack of consideration for individual differences in user ability is believed to be one of the key reasons for the mixed findings. The elaboration likelihood model (ELM) and several studies have suggested that individual differences in ability plays an moderating role on the relationship between the antecedents and user acceptance. Despite the critical role of user ability, little research has examined the role of user ability in the Internet shopping mall context. The purpose of this study is to develop a user acceptance model that consider the moderating role of user ability in the context of Internet shopping. This study was initiated to see the ability of the technology acceptance model(TAM) to explain the acceptance of a specific ISM. According to TAM. which is one of the most influential models for explaining user acceptance of IT, an intention to use IT is determined by usefulness and ease of use. Given that interaction between user and website takes place through web interface, the decisions to accept and continue using an ISM depend on these beliefs. However, TAM neglects to consider the fact that many users would not stick to an ISM until they trust it although they may think it useful and easy to use. The importance of trust for user acceptance of ISM has been raised by the relational views. The relational view emphasizes the trust-building process between the user and ISM, and user's trust on the website is a major determinant of user acceptance. The proposed model extends and integrates the TAM and relational views on user acceptance of ISM by incorporating usefulness, ease of use, and trust. User acceptance is defined as a user's intention to reuse a specific ISM. And user ability is introduced into the model as moderating variable. Here, the user ability is defined as a degree of experiences, knowledge and skills regarding Internet shopping sites. The research model proposes that the ease of use, usefulness and trust of ISM are key determinants of user acceptance. In addition, this paper hypothesizes that the effects of the antecedents(i.e., ease of use, usefulness, and trust) on user acceptance may differ among users. In particular, this paper proposes a moderating effect of a user's ability on the relationship between antecedents with user's intention to reuse. The research model with eleven hypotheses was derived and tested through a survey that involved 470 university students. For each research variable, this paper used measurement items recognized for reliability and widely used in previous research. We slightly modified some items proper to the research context. The reliability and validity of the research variables were tested using the Crobnach's alpha and internal consistency reliability (ICR) values, standard factor loadings of the confirmative factor analysis, and average variance extracted (AVE) values. A LISREL method was used to test the suitability of the research model and its relating six hypotheses. Key findings of the results are summarized in the following. First, TAM's two constructs, ease of use and usefulness directly affect user acceptance. In addition, ease of use indirectly influences user acceptance by affecting trust. This implies that users tend to trust a shopping site and visit repeatedly when they perceive a specific ISM easy to use. Accordingly, designing a shopping site that allows users to navigate with heuristic and minimal clicks for finding information and products within the site is important for improving the site's trust and acceptance. Usefulness, however, was not found to influence trust. Second, among the three belief constructs(ease of use, usefulness, and trust), trust was empirically supported as the most important determinants of user acceptance. This implies that users require trustworthiness from an Internet shopping site to be repeat visitors of an ISM. Providing a sense of safety and eliminating the anxiety of online shoppers in relation to privacy, security, delivery, and product returns are critically important conditions for acquiring repeat visitors. Hence, in addition to usefulness and ease of use as in TAM, trust should be a fundamental determinants of user acceptance in the context of internet shopping. Third, the user's ability on using an Internet shopping site played a moderating role. For users with low ability, ease of use was found to be a more important factors in deciding to reuse the shopping mall, whereas usefulness and trust had more effects on users with high ability. Applying the EML theory to these findings, we can suggest that experienced and knowledgeable ISM users tend to elaborate on such usefulness aspects as efficient and effective shopping performance and trust factors as ability, benevolence, integrity, and predictability of a shopping site before they become repeat visitors of the site. In contrast, novice users tend to rely on the low elaborating features, such as the perceived ease of use. The existence of moderating effects suggests the fact that different individuals evaluate an ISM from different perspectives. The expert users are more interested in the outcome of the visit(usefulness) and trustworthiness(trust) than those novice visitors. The latter evaluate the ISM in a more superficial manner focusing on the novelty of the site and on other instrumental beliefs(ease of use). This is consistent with the insights proposed by the Heuristic-Systematic model. According to the Heuristic-Systematic model. a users act on the principle of minimum effort. Thus, the user considers an ISM heuristically, focusing on those aspects that are easy to process and evaluate(ease of use). When the user has sufficient experience and skills, the user will change to systematic processing, where they will evaluate more complex aspects of the site(its usefulness and trustworthiness). This implies that an ISM has to provide a minimum level of ease of use to make it possible for a user to evaluate its usefulness and trustworthiness. Ease of use is a necessary but not sufficient condition for the acceptance and use of an ISM. Overall, the empirical results generally support the proposed model and identify the moderating effect of the effects of user ability. More detailed interpretations and implications of the findings are discussed. The limitations of this study are also discussed to provide directions for future research.