• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

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 Journal of Information Technology
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• v.8 no.3
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• pp.117-129
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• 2005

The topic of this study is a survey research about the economic recognition related to economic ethics and information literacy of students(6,779) extend from elementary school to university. First, for the ability to use computers, it is recognizing that 49.6% of students are normal, 38.6% are superior, and 12.8% are inferior. In part of class, it tends to recognize that it is the superior as the level of school is the lower excepting middle school students. Second, we can find great difference between male students and female students related to purpose of using internet, 79.8% of male students are using computer to play game or entertainment(1), search data or knowledge(2), chatting or massenger(3), 70.1% of female students are using internet to search data or knowledge(1), chatting or massenger(2) and meeting of similar taste. Third, it shows a tendency that the economic activity using internet or cell-phone increases faster as the level of schools is higher. In detail, they primarily use buying or settlement of products(63%), purchasing internet service(20.9%). Fourth, for using illegal CD, not only they didn't feel guilty in all levels of schools, excepting university students, it is showed that the trust of intellectual poverty right is weaker as the level of schools is higher. So, it is becoming serious problems. It seems a task which should be supplemented through economic education of schools in the future.

• Smart Media Journal
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• v.12 no.2
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• pp.42-55
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• 2023

The combination of blockchain (BC), artificial Intelligence (AI), quantum computing (QC), and the Internet of Things (IoT) can potentially transform various industries and domains, including healthcare, logistics, and finance. In this paper, we look at the trends and developments in integrating these emerging technologies and the potential benefits and challenges that come with them. We present a conceptual framework for integrating BC, AI, QC, and IoT and discuss the framework's key characteristics and challenges. We also look at the most recent cutting-edge research and developments in integrating these technologies, as well as the key challenges and opportunities that come with them. Our analysis highlights the potential benefits of integrating the technologies and looks to increased security, privacy, and efficiency to provide insights into the future of these technologies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.813-826
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• 2023

Organization members often use the Internet for non-work purposes during work hours, which is called cyberloafing. Certain types of cyberloafing (e.g., webhard, adult, and gambling sites access) can be a major cause of malware infection, which can ultimately generate significant damages to organizations. It therefore is important to examine the relationship between cyberloafing and cybersecurity risks of organizations. We analyzed log data from an internet filtering system of a financial institute and found that the more employees access to blacklist sites, the higher the possibility of malicious code infection. In other words, cyberloafing increases cybersecurity risks of organizations. We suggest that organizations need to monitor and control their members' internet use in an appropriate way.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.157-170
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• 2014

As the increase of transaction using mobile banking continues, threat to the mobile financial security is also increasing. Mobile banking service performs the financial transaction using the dedicate application which is made by financial corporation. It provides the same services as the internet banking service. Personal information such as credit card number, which is stored in the mobile banking application can be used to the additional attack caused by a malicious attack or the loss of the mobile devices. Therefore, in this paper, to cope with the mobile financial accident caused by personal information exposure, we suggest outlier detection method which can judge whether the transaction is conducted by the appropriate user or not. This detection method utilizes the user's input patterns and transaction patterns when a user uses the banking service on the mobile devices. User's input and transaction pattern data involves the information which can be used to discern a certain user. Thus, if these data are utilized appropriately, they can be the information to distinguish abnormal transaction from the transaction done by the appropriate user. In this paper, we collect the data of user's input patterns on a smart phone for the experiment. And we use the experiment data which domestic financial corporation uses to detect outlier as the data of transaction pattern. We verify that our proposal can detect the abnormal transaction efficiently, as a result of detection experiment based on the collected input and transaction pattern data.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.283-292
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• 2020

The implementation of physical or social distancing during the Covid-19 pandemic has an implication on the shifting of conventional to online business activities. This study aims to explore how financial support, perceived benefits, external pressure determine social media marketing as well as understanding the role of internet and e-business technology (IEBT) that occurs in this relationship. This study adopted a quantitative study with Structural Equation Modeling (SEM)-based variance Partial Least Square (PLS), which aims to enhance understanding of the relationship between variables. The surveyed population of this study came from 123 small- and medium-sized enterprise (SME) owners in East Java of Indonesia, using an online survey and selected with the convenience random sampling method. The findings of this study indicated that the perceived benefits and external pressure have a positive effect on the adoption of IEBT. However, financial support failed in explaining SMEs' adoption of IEBT. This study confirmed that the adoption of IEBT has successfully mediated the influence of financial support, perceived benefits, and external pressure on social media marketing. Despite the samples solely collected from East Java, this study is the first step in research related to the social media marketing in SMEs in Indonesia.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.493-517
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• 2008

The purpose of this research is to identify effect of communication strategy as effectively communication method which is decreasing Internet Web site users' perceived information privacy concerns as important factor affecting to positive behavior or behavioral intentions on long-term relational outcome perspectives. This study suggests alternatives concepts and causal relationship about information privacy issues. First, it addressed collaborative communication strategy (CCS) model of effective communication method for Web site's IPP to users. Second, it provided comparing and integrating streams of information privacy research on long-term relational outcomes perspective. Third, it assessed effectiveness of Web site's IPP on organization legitimacy ensured continuous survival of organization. A research model was proposed and subsequent hypotheses were empirically tested with partial least square (PLS) based on 684 responses from the users of 21 Internet Website among entirely finance, recruit, portal /e-store Web site. It was learned that CCS(as a communication method) and relationship quality(representing long-term relational outcomes)was positively associated with decreasing user's IPC more than privacy risk. Also, legitimacy to information privacy practice positively associated with willingness to information providing more than negative effect of IPC. Lastly, their association strength was partially moderated by the type of real information sensitivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.