• The Journal of Korean Academy of Sensory Integration
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• v.15 no.1
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• pp.46-59
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• 2017

Objective : This study is to analyze the current trends of research and the subject and method of assessments used in praxis functions through a systematic review. Methods : Through the PubMed, Proquest, and Google database, research articles from January of 1985 through April of 2016 were searched. The keywords used for this search were "praxis AND (validity OR reliability) AND (assessment OR test) AND (preschooler OR child)". Additionally, the name for the assessments from the previous review studies of praxis function assessments was searched. In the end, 14 papers were chosen and 8 assessments that were used in these papers were analyzed. Results : Among the final 14 papers, 10 studies (71.4%) were level III (non-randomized one group) which was the largest number in this review, followed by 4 studies (28.6%) with level II (non-randomized two groups). There was no RCT study which is the level of evidence of the level I research. The results for the analysis of the subjects' age of the final 8 assessments that were chosen showed that most of the praxis function assessments were developed for children. There were 6 assessments of which their reliability and validity were verified and other 2 assessments of which their reliability and validity were not both verified. Conclusion : This study proposes the current trends of research of praxis function assessments. The study's significance is that it provides a research evidence when choosing and utilizing assessments for the children.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.311-316
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• 2017

The network analysis method has emerged as a new methodology for various disciplines, due to its ability to provide a representative knowledge network of references, co-authors and keywords. Bulletproof technology is an interdisciplinary field involving various disciplines, such as material mechanics, structural mechanics, and ballistics, so it is essential to keep up with the recent trends in technological research. In this research, the recent R&D trends in the field of bulletproof materials were analyzed using keyword based network analysis. From the results, the core keywords were identified as 'Composite', 'Model' and 'Head' using the scholar search engine, google scholar. The centrality analysis for the core keywords showed that bulletproof technology has developed in 3 different areas, viz. material, structure and effects. To the best of our knowledge, this is the first application of (network analysis?) to bulletproof technology. Moreover, we are also convinced that the results of this study will be useful for defense technology planning and determining the direction of R&D in the field of bulletproof technology.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.63-79
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• 2022

Recently, various studies have been conducted on stock price prediction using machine learning and deep learning techniques. Among these studies, the latest studies have attempted to predict stock prices using limit order books, which contain buy and sell order information of stocks. However, most of the studies using limit order books consider only the trend of limit order books over the most recent period of a specified length, and few studies consider both the medium and short term trends of limit order books. Therefore, in this paper, we propose a deep learning-based prediction model that predicts stock price more accurately by considering both the medium and short term trends of limit order books. Moreover, the proposed model considers news headlines during the same period to reflect the qualitative status of the company in the stock price prediction. The proposed model extracts the features of changes in limit order books with CNNs and the features of news headlines using Word2vec, and combines these information to predict whether a particular company's stock will rise or fall the next day. We conducted experiments to predict the daily stock price fluctuations of five stocks (Amazon, Apple, Facebook, Google, Tesla) with the proposed model using the real NASDAQ limit order book data and news headline data, and the proposed model improved the accuracy by up to 17.66%p and the average by 14.47%p on average. In addition, we conducted a simulated investment with the proposed model and earned a minimum of $492.46 and a maximum of $2,840.93 depending on the stock for 21 business days.

• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.1109-1133
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• 2013

In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.57-97
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• 2018

Big Data has spread rapidly in various industries since 2010. We analyzed the general characteristics of big data through time series analysis on the initial process of spreading big data and investigated the difference of diffusion characteristics in each industry. By analyzing papers, patents, news data, and Google Trend using Big Data as a keyword, we searched for data corresponding to the leading indicator, and confirmed that trends in news and Google Trend preceded the papers and patents by two years. We used Google Trend to compare the introduction period of domestic, US, Japan, and China and quantify the process of spreading the eight main industries in Korea through news data. Through this study, we present an empirical research method on how the general technology spreads in several industry sectors and we have figured out where the spreading speed difference of big data originated in each industry in Korea. The method presented here can be used to analyze the technology introduced from foreign countries in developing countries because it can be analyzed in diffusion process of other technologies besides big data and corresponds to the diffusion of technology keywords in a specific country. And, on the corporate side, this approach shows what path is effective when it comes to launching and spreading new technologies.

• Journal of Platform Technology
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• v.9 no.4
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• pp.10-31
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• 2021

The digital tax, recently referred to as the Google tax was finally agreed at the 31st General Assembly of the OECD (October 8, 2021) with full support by 136 countries and will take effect from 2023. The purpose of this study is to analyze the digital tax prepared by the OECD for global MNEs, and to suggest the impacts on the Korean industry and to present the Korean governmental countermeasures. As the first study, we analyzed the international agreement on digital tax. In results, we found that even if global MNEs do not set up a business operation in overseas countries, if sales and profits are generated, 25% of the excess profit is borne as tax (pillar 1), and when MNEs do business in all the countries, they are liable to at least a 15% tax (pillar 2). We think that countries around the world have prepared a minimum countermeasure to protect their companies in anticipation that global MNEs will easily encroach on their markets in the future. As the second study, in order to discover the reason why the MNEs are so strong, we investigated the trends of Google and B2B SaaS companies in details. In results, we discovered that the global MNEs establishes a digital platform partnership ecosystem that enables them to enter foreign markets easily and expand rapidly. In conclusion, as a countermeasure for the Republic of Korea, governmental policies were proposed at the corporate (startup nurturing), industry, and national level respectively.

• The Research Journal of the Costume Culture
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• v.23 no.6
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• pp.1097-1115
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• 2015

ICT in the IOT era is the core basis of modern society. This study investigated and analyzed the recent commercialization trends of smart fashion products internationally and domestically, to utilize them as the basis of data for developing user-friendly smart fashion products that can meet the needs of consumers. Keyword research using the most representative search engines, Google and Naver was conducted for searching for various wearable items commercialized actively since 2010. The final 78 products were classified by the physical area, and the key features and benefits were analyzed. Smart fashion products were classified as four physical types for the head and face, torso, arms and hands, and ankles and feet. Smart fashion products for each body part were developed in various ways, such as hats, glasses, lenses, virtual screens, earphones, headsets, clothing, watches, wrist bands, gloves, rings, wallets, bags, anklets, shoes, socks, and insoles. The main features were music playback, bluetooth, a camera based on NFC, virtual effects, health and safety protection through measuring heartbeat and momentum, and social network sharing of all kinds of information, based on inter-working with a smartphone. These functions represent the physical, social, and emotional interactions among users and their surroundings, as well as the users, themselves. The research results are expected to be used in future studies on planning user-friendly and marketable products through in-depth analysis of the design characteristics of smart fashion products as well as consumer responses.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.1-12
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• 2017

The purpose of this study is to contribute to research on dementia and policy making by reviewing research trends of dementia for 15 years and it was collected from 12,588 dementia - related research data for 15 years at Google 's scalar site. The results of this study confirm that the research on dementia, one of the most common geriatric diseases, is continuously increasing. Second, research on dementia is increasing due to social influences such as government support. Third, we suggested that dementia is changing from a viewpoint of diseases to be managed at the facility and treatment of severe dementia patients to a paradigm from the viewpoint of management of mild patients and community participation. Fourth, dementia seems to be shifting from a serious and negative awareness to a social atmosphere that is accepted as a slow but manageable disease. This is changing to a dementia-friendly social environment, which is making a very positive environmental change. This study contributes to the field research by presenting the trend of domestic research on dementia.

• Physical Therapy Korea
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• v.30 no.4
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• pp.261-267
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• 2023

Forward head posture (FHP) is a musculoskeletal disorder that causes neck pain. Several exercise interventions have been used in South Korea to improve craniovertebral angle (CVA) and relieve neck pain. There has been no domestic literature review study over the past 5 years that has investigated trends and effects of exercise intervention methods for CVA with neck pain. This domestic literature review aimed to evaluate the trends and effects of exercise interventions on CVA and neck pain in persons with FHP. A review of domestic literature published in Korean or English language between 2018 and 2022 was performed. Literature search was conducted on Google Scholar and Korea Citation Index by using the following keywords: "exercise," "exercise therapy," "exercise program," "forward head posture," and "neck pain." Ten studies were included in this review. All of the studies showed positive improvements after intervention programs that included exercises. Notably, four of these studies demonstrated significant differences in results between the experimental and control groups. Among the 10 studies, nine measured visual analogue scale or numerical rating scale scores and reported significant reductions in pain following interventions, including exercise programs. Five of these studies showed significant differences in results between the experimental and control groups. Furthermore, six studies that used neck disability index exhibited a significant decrease in symptoms after implementing intervention programs that included exercise, and significant differences in results were found between the experimental and control groups. This domestic literature review provides consistent evidence to support the application of various exercise intervention programs to improve CVA and relieve neck pain from FHP. Further studies are warranted to review the effects of various exercise interventions on FHP reported not only in domestic but also in international literature.