• Transactions of the Korean hydrogen and new energy society
• /
• v.29 no.6
• /
• pp.559-569
• /
• 2018

Catalytic supports made of carbon have many advantages, such as high coking resistance, tailorable pore and surface structures, and ease of recycling of waste catalysts. Moreover, they do not require pre-reduction. In this study, ash-free coal (AFC) was obtained by the thermal extraction of carbonaceous components from raw coal and its performance as a carbon catalytic support was compared with that of well-known activated carbon (AC). Nickel was dispersed on the carbon supports and the resulting catalysts were applied to the steam reforming of toluene (SRT), a model compound of biomass tar. Interestingly, nickel catalysts dispersed on AFC, which has a very small surface area (${\sim}0.13m^2/g$), showed higher activity than those dispersed on AC, which has a large surface area ($1,173A/cm^2$). X-ray diffraction (XRD) analysis showed that the particle size of nickel deposited on AFC was smaller than that deposited on AC, with the average values on AFC ${\approx}11nm$ and on AC ${\approx}23nm$. This proved that heteroatomic functional groups in AFC, such as carboxyls, can provide ion-exchange or adsorption sites for the nano-scale dispersion of nickel. In addition, the pore structure, surface morphology, chemical composition, and chemical state of the prepared catalysts were analyzed using Brunauer-Emmett-Taylor (BET) analysis, transmission electron microscopy (TEM), scanning electron microscopy (SEM), x-ray diffraction (XRD), Fourier-transform infrared (FT-IR) spectroscopy, and temperature-programmed reduction (TPR).

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.2
• /
• pp.41-56
• /
• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.275-284
• /
• 2021

Survival analysis was used to analyze whether there is a difference in the effect of leverage on corporate failure according to the firm size. A total of 25,250 (year-company) companies listed on the Korea Stock Exchange and KOSDAQ market from 1999 to 2019 were analyzed. First, the increase in leverage generally acts as a factor that increases the possibility of corporate failure. On the other hand, the increase in the trade payable ratio lowered the possibility of failure of the company. The increase in corporate trade payable was perceived as a factor in reducing the possibility of corporate failure because it was considered the active development of business activities or active use of interest-free debt rather than leading to an increase in corporate risk. Second, a higher leverage ratio and trade payable ratio in large firms lowered the possibility of corporate failure. In the SMEs, all types of leverage increases are a factor that increases corporate failure. Overall, the effect of leverage on corporate failure differs according to the size of the company.

• International Area Studies Review
• /
• v.20 no.1
• /
• pp.105-125
• /
• 2016

The expansionary monetary policy was practiced after 2001 in Japan to treat the deflation spiral, and reduced only the nominal interest rates and domestic household demand. One of the most serious factors for this failure was the change of private sector's expectancy. This paper has studied the effect of Japanese monetary policy in 21c., with empirical research based on a renewed macroeconomic model and the VAR. The empirical analysis shows that the effect of monetary policy on the national income during 2001.01-2015.03 is weaker than that of 1985.01-1994.04. Money volume has a diminutive effect on the growth of GDP within a short term after 2001. The change in the expectations of the private sectors might have been the cause of ineffectiveness of the expansive monetary policy. Economic agents learned from the past Japanese financial crisis that an expansive monetary policy increased the inflation rate and caused the 'bubbles to burst' afterwards. The VAR analysis says that the effectiveness of monetary policy on the economic depression declined over the past 20 years and the expansion of money volume has no influence on exchange rate and net export. This means that the expansive monetary policy lost its effect on net export and national income steadily. Monetary policy makers have to recognize this fact, and to consider another anti-cycle political instrument, i.e. the fiscal policy with government debt.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.1
• /
• pp.143-152
• /
• 2021

The extremely isolated uninhabited island at the end of the West Sea in South Korea called "The Gyeokryeolbi Yeoldo" has recently begun to be managed by the government under the influence of public opinion demanding the island to be strictly protected. The island was created 70 million years ago by volcanic activities. So it is older than the birth history of Jeju Island, which is estimated to have been born about a million years ago. This study has focused on providing the basis for imagetelling and storytelling of the Gyeokryeolbi Yeoldo, known for its important value by exploring the cultural resources of the island. For the research, the ethnography including in-depth local interview and on-site investigation have been applied for 3 years from February 2018 to December 2020 in Taean, Chungnam Province, where the island is located. To analyze the cultural resources of this island, the resource classification model has been designed and used, which is modified from Valentine (2001) and Chi-ho Nam (2007). As a result, the "tangible cultural resources (TCR)" including various remains found on the island were mainly symbols of cultural bridge in the history of Korea-China exchange, and the spiritual land of life-saving. Also "intangible cultural resources (ICR)" extracted from the island were focused on the images of life protection, safety, bravery, and romance. Based on this study, the core concept of identity to be applied when refurbishing the island with a prominent cultural placeness( "sense of place") can be proposed as "a cultural ecological island centered on the Circular Yellow Sea that ruminates memories of love."

• Asia Marketing Journal
• /
• v.15 no.4
• /
• pp.1-32
• /
• 2014

The purpose of this paper is to investigate upon a diversification strategy through market creation of CJ Group, which has contributed in positioning of the firm as one of the leading conglomerates in South Korea. With such objective, the background of CJ Group, followed by its business diversification strategies were explored, with reference to several case studies. The history of CJ Group began with establishment of CheilJedang Industrial Corporation in 1953, as the first domestic sugar producer and exporter of South Korea. The corporation gradually expanded its business ever since at both national and global level, to include the fields of food production, pharmaceutical, biotechnology, and life chemicals. Later, CheilJedang (CJ) Group was established as an affiliate of CheilJedang Industrial Corporation. With such independence, extension of business has been witnessed across the industries of media, entertainment, finance, information technology and distribution. Thus, the current CJ Group pursues to define itself as a progressive global living culture company with four major business categories from food and food service, biotechnology, entertainment and media, and logistics. Despite its success in today's market, CJ Group underwent hardships in its business diversification in 1990s due to indiscreet management, along with the Asian financial crisis. Here, many firms overcame the financial difficulties by taking advantage of the exchange rate for overseas expansion. Though, CJ Group tried to differentiate itself by focusing on the domestic market by creating something out of nothing. Hence, CJ Group takes a unique position among many cases of business diversification and their categorization. In an effort to identify and classify the types of growth experienced by the top 30 companies in South Korea, the firms were categorized into four groups according to their diversification strategies adapted after the Asian financial crisis. Based on the mode and time of entry, corporations were identified either as the 'Explorer', 'Invader', 'Venture Capitalist', or 'Assimilator'. Here, the majority of the firms showed the qualities of Invader, entering mature markets through large-scaled mergers and acquisitions. However, CJ Group was the only firm that was categorized as an Explorer, for its focus on the newly emerging service sector in culture-contents industry. This diversification strategy through market creation is worth examining, due to its contribution in generating simultaneous growth between the market and the company itself. Diverse brands of CJ Group have been referred to as case studies in this regard, from 'Hatban', 'Cine de Chef', 'VIPS' to 'CJ GLS'. These four businesses, each to represent processed food, film, restaurant service, and logistics industries respectively, show CJ Group's effectiveness in creating a whole new category of goods and services that are innovative. In fact, such businesses not only contributed in advancement of consumers' wellbeing, but toward generating additional value and employment. It is true that the diversification strategy of CJ Group requires long-term capital investment with high risk, compared to the other strategies mentioned in the paper. However, this model does create high employment and additional values that are positive to both the society and the firm itself. Therefore, the paper comes to a conclusion that the diversification strategy through market creation conveys the most positive impact relative to the others.

• Journal of Industrial Convergence
• /
• v.21 no.9
• /
• pp.41-48
• /
• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.29 no.1
• /
• pp.1-13
• /
• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.

• Information Systems Review
• /
• v.14 no.3
• /
• pp.75-97
• /
• 2012

Fostering trusting belief in financial transactions is a challenging task in Internet banking services. Authenticated Certificate had been regarded as an effective method to guarantee the trusting belief for online transactions. However, previous research claimed that this method has some loopholes for such abusers as hackers, who intend to attack the financial accounts of innocent transactors in Internet. Two types of methods have been suggested as alternatives for securing user identification and activity in online financial services. Control transparency uses information over the transaction process to verify and to control the transactions. Outcome feedback, which refers to the specific information about exchange outcomes, provides information over final transaction results. By using these two methods, financial service providers can send signals to involved parties about the robustness of their security mechanisms. These two methods-control transparency and outcome feedback-have been widely used in the IS field to enhance the quality of IS services. In this research, we intend to verify that these two methods can also be used to reduce risks and to increase the security protections in online banking services. The purpose of this paper is to empirically test the effects of the control transparency and the outcome feedback on the risk perceptions in Internet banking services. Our assumption is that these two methods-control transparency and outcome feedback-can reduce perceived risks involved with online financial transactions, while increasing perceived trust over financial service providers. These changes in user attitudes can increase the level of user satisfactions, which may lead to the increased user loyalty as well as users' willingness to pay for the financial transactions. Previous research in IS suggested that the increased level of transparency on the process and the result of transactions can enhance the information quality and decision quality of IS users. Transparency helps IS users to acquire the information needed to control the transaction counterpart and thus to complete transaction successfully. It is also argued that transparency can reduce the perceived transaction risks in IS usage. Many IS researchers also argued that the trust can be generated by the institutional mechanisms. Trusting belief refers to the truster's belief for the trustee to have attributes for being beneficial to the truster. Institution-based trust plays an important role to enhance the probability of achieving a successful outcome. When a transactor regards the conditions crucial for the transaction success, he or she considers the condition providers as trustful, and thus eventually trust the others involved with such condition providers. In this process, transparency helps the transactor complete the transaction successfully. Through the investigation of these studies, we expect that the control transparency and outcome feedback can reduce the risk perception on transaction and enhance the trust with the service provider. Based on a theoretical framework of transparency and institution-based trust, we propose and test a research model by evaluating research hypotheses. We have conducted a laboratory experiment in order to validate our research model. Since the transparency artifact(control transparency and outcome feedback) is not yet adopted in online banking services, the general survey method could not be employed to verify our research model. We collected data from 138 experiment subjects who had experiences with online banking services. PLS is used to analyze the experiment data. The measurement model confirms that our data set has appropriate convergent and discriminant validity. The results of testing the structural model indicate that control transparency significantly enhances the trust and significantly reduces the risk perception of online banking users. The result also suggested that the outcome feedback significantly enhances the trust of users. We have found that the reduced risk and the increased trust level significantly improve the level of service satisfaction. The increased satisfaction finally leads to the increased loyalty and willingness to pay for the financial services.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.143-156
• /
• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.