As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.
The government budget for promoting startup have been skyrocketed as catching up with increasing demands for high-tech startup by disruptive innovation resulted from rapid technology change. However, major trend of startup have still fallen on self-employed type of startup due to the lack of expertise and fund in spite of desperate government policy efforts. In reality, the access to high-tech startup has been very limited and too high huddle to would-be entrepreneur. This paper implement empirical analysis on the effects of entrepreneur competency and satisfaction level to government support, considering these as the KSF for the growth and success of high-tech startup, to the performance of the company. In particular, it focus on defining unique characteristics of high-tech startup through differential proving by the backgrounds of entrepreneur such as major, R&D experience, patent possession, CTO possession. This research carry out survey to 217 entrepreneurs in high-tech company in Daejon and Daegue at R&D Special Innopolis Zone. Research results are as follow. First, entrepreneurial achievement competencies, conceptualization competencies, network competencies and market recognition competencies positively affect the financial and non-financial performance and organizational and technical competencies, while organizational and technological competencies only positively impact on non-financial performance. Second, the satisfaction level of government support showed a positive moderating effect on entrepreneurial achievement competencies and financial performance, while no significant effect in other competencies. Third, positive differential effect by the technological background of entrepreneur such as Major, R&D experience, patent possession, CTO possession) have been confirmed. This paper deliver several significant implications and contributions, First, it propose classified and systematized entrepreneur competency through the domestic and foreign literature reviews. Second, it proves the need for the wider spread of team based startup culture rather then sole startup. Third, it also proves the important role of technological background of entrepreneur among the characteristics of high-tech startup.
The purpose of this study is to predict changing traffic environments and related economic effects by reflecting the changed KTDB and socio-economic indicators pertaining to Mulgeum station, a general railway stop, when it is confirmed as a KTX stop. To analyze the data of this study, socioeconomic indicators and the general status of transportation facility operations were investigated with reference to related statistical data, centered on the country overall and on Yangsan city in particular. In addition, we investigated and referenced the railroad facility construction plan and train operation plan, which are national high-level plans related to land development and transportation network construction. Currently, there are only ITX trains (4 times/day) and Mugunghwa trains (29 times/day) that stop at Mulgeum station in Yangsan, meaning that passengers cannot use KTX trains in the Yangsan area. In particular, the need for a KTX stop at Mulgeum station has been continuously raised because train users in the Yangsan area have inconvenient transportation in that they must travel 40 minutes to Ulsan station or 30 minutes to Gupo station to use the KTX. As a result of analyzing railroad transportation demand that will change in the future as the KTX stop at Mulgeum station is confirmed, the number of passengers boarding and arriving at Mulgeum station is predicted to be 1,674 passengers/day by 2025. In addition, the numbers of train passengers that are converted from Ulsan and Gupo stations due to the stop at Mulgeum station are predicted to be 594 passengers/day boarding and 562 passengers/day arriving by 2025. In the future, if Yangsan citizens use the KTX Mulgeum station, the access time to Mulgeum station can be shortened to 22 minutes from 65 minutes, and it is predicted that the inconvenience of transferring between railroads will be resolved, with the waiting time for transfers reduced by up to a maximum of 40 minutes. Therefore, the economic effect of creating a KTX stop at Mulgeum station was analyzed to be B/C=1.823 when general railroad operating costs are not taken into account and B/C=2.127 when general railroad operating costs are considered. In conclusion, when using KTX trains to visit the Seoul Metropolitan Area, it takes 2 hours and 43 minutes to use Mulgeum station without using Ulsan station or Gupo station, which is considered to be very effective for reducing travel times and improving the economic feasibility of this development; it is also expected that Yangsan city will be able to improve accessibility and mobility to the Seoul Metropolitan Area by breaking free from the disgrace of being a remote location given its link to KTX in the future.
Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.
This study conducted an exploratory study based on in-depth interviews to understand the characteristics and capabilities of female entrepreneurs to promote women entrepreneurship. Therefore, in this study, through in-depth interviews with eight female entrepreneurs, the main contents of entrepreneurial attitudes (need for independence, development desire, favorable conditions), start-up entry rate, start-up motivation, start-up activities and constraints were analyzed. As a result, first, it was found that the entrepreneurial attitude of female entrepreneurs has a strong motivation for successful management based on a feeling of self-satisfaction, has characteristics that prioritize independence and self-actualization, and favorable conditions for starting a business are important. Second, it was found that women's individual differences from men and social structural factors had no significant effect on the entry rate of women. Third, it was found that the most important entrepreneurship motivation for women is the spirit of challenge, self-satisfaction, and the desire to balance work and family. Fourth, female entrepreneurs showed little difference in perception between male and female entrepreneurs in terms of resource access, but there was some discrimination in the network. Fifth, the main industries of female entrepreneurs are small businesses, and there is a tendency to be concentrated in industries with low profit margins and low growth and sales. Finally, it was found that barriers to women's entrepreneurship still exist. Based on the results of this study, the following implications are suggested. First, this study is differentiated in that it mainly identified the characteristics of women's experiences and social environments while starting a business and running a business. Second, in the case of female entrepreneurs, there is a need to spread a positive awareness of women entrepreneurship by arguing that the barriers to entrepreneurship unique to women are not high and can be sufficiently overcome. Lastly, although opportunistic start-ups based on women's social experience or management ability in work life are important for women's entrepreneurship, government support policies are needed to promote professional technology start-ups.
As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.
The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.
The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70