• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.250-260
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• 2022

Mobile Banking Applications (MBAPs) is one of the recent fads in mobile trading applications (Apps). MBAPs permit users to execute exchanges of money and many more whenever it might suit them; however, the primary issue for mobile banking Apps is usability. Hardly any investigation analyzes usability issues dependent on user's age, gender, exchanging accomplices, or experience. The purpose of this study is to determine the degree of usability issues, and experience of mobile banking users. The survey employs a quantitative method and performs user experiment on 240 participants with six different tasks on the application's interface. The post experiment survey is done with concerning participants. On the other hand, banking experts and Information Technology (IT) expert's group is also involved after the experiment. Expert's opinions about existing mobile banking Apps and suggestions for improving usability of MBAPs are collected through physical means (like questionnaire and interview) and online means like Google form. After that comparison of the opinions of users and experts about MBAPs is performed. The experimentation measures the tasks usability of various mobile banking apps with respect to its effectiveness, efficiency, trustfulness, learnability, memorability and satisfaction. The usability testing was led at different Universities and the outcomes acquired show that there are privacy and trust issues with their mobile banking apps. There is also a gap between users and experts which should be minimized by applying customized usability models, modes concept like other application software and also by adding complete features of banking in MBAPs. It will benefit mobile banking apps users, developers and usability engineers by providing user-friendly which are up to the mark of user's requirements.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.274-284
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• 2022

By explaining the essence of corporate governance as well as disclosure and transparency, the study examined the guarantees of applying disclosure and transparency to firms listed on the Saudi stock exchange. The research also addressed the disclosure and transparency duties of firms listed on the Saudi stock exchange. Finance to prepare a prospectus, as the Capital Market Authority's regulations required that the prospectus includes information that enables the investor in securities to make his investment decision based on real foundations based on the issuing company's financial position and to ensure that companies fulfill that disclosure in the prospectus. Firms who fail to disclose are required by law to do so, and the Capital Market Authority's laws mandate companies listed on the financial market to regularly report fundamental events linked to the issuer or the securities issued by it. The Capital Market Authority must make it available to the public dealing with the business issuing the securities, and The Capital Market Authority's Law and Regulations have imposed fines on corporations that do not comply with disclosure and make the Board of Director's report available. The research focused on activities that the legislator deemed to be a breach of the obligation of openness, such as the danger of many measures aimed at ensuring the impartiality and transparency of trading in the Saudi financial market, as well as the absence of conflicts of interest. The research also addressed the sanctions imposed on The source for failing to meet the obligation of disclosure and openness, as well as the mechanisms of compensating persons harmed by the failure to meet that responsibility.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.43-58
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• 2014

As the use of trading systems has increased rapidly, many researchers have become interested in developing effective stock market prediction models using artificial intelligence techniques. Stock market prediction involves multifaceted interactions between market-controlling factors and unknown random processes. A successful stock prediction model achieves the most accurate result from minimum input data with the least complex model. In this research, we develop a combination model of ${\pi}$-fuzzy logic and support vector machine (SVM) models, using a genetic algorithm to optimize the parameters of the SVM and ${\pi}$-fuzzy functions, as well as feature subset selection to improve the performance of stock market prediction. To evaluate the performance of our proposed model, we compare the performance of our model to other comparative models, including the logistic regression, multiple discriminant analysis, classification and regression tree, artificial neural network, SVM, and fuzzy SVM models, with the same data. The results show that our model outperforms all other comparative models in prediction accuracy as well as return on investment.

• Journal of the Korea Society of Computer and Information
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• v.3 no.3
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• pp.139-150
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• 1998

Due to development of science and telecommunication with wide-spread computer supply, it could be done through computer automatically instead of manpower-work for paper transportation & paper approval. It is developed to so-called Factory Automation. Further, it is developed to Office Automation. Trading companies & concerned trade authorities are interested in Trade Automation that such technique is applied to trade work. Generally, Trade Automation means to realize paperless trade by exchanging electronic papers through inter-computers after concerned trade operators transformed various papers to electronic papers that computer could read. In case Trade Automation fix in the trade business, it is expected one of innovations among traditional paper work of trade business, namely without going import-export authorities, Customs office, Banks. Shipping companies, Marine insurance companies on hand-carrying papers, it could be fast, simple, correct to finish every trade procedures such as commercial business, foreign currency, customs clearance, transportations, insurance. terms of payment, etc., with Electronic Data Interchange through computer facilities. Especially, telecommunication for trade form could be helpful to proceed trade paper with one-run-method Further we can anticipate 6 effects for Trade Automation as belows : First, as explained just above articles, with completion for Trade Automation, every trade procedures can be done by computer. so, time to work can be diminished. namely. logistics cost including accessory costs for trade procedures can be saved much. Second, viewing to private enterprise, effect of Office Automation can be maximized and rapid, correct exchange for various trade informations could raise efficiency of enterprise management establishing rational production, storage, transportation and could raise competition improving standard for consumers's service. Third, establishing Trade Automation systems makes it easier piling-up of harbor cargo by pre-transmission of electronic paper & trade informations make it possible to finish customs clearance in advance and can be dispatched upon cargo arrival. Fourth, most of concerned trade authorities such as import-export approval office. financial authorities, transport & insurance companies concentrated in Metropolitan area(Seoul, In -Cheon, Kyung-Ki). Therefore, in case Trade Automation could be realized. it is possible to proceed trade business instantly in every country area by computer facilities. Also. it contribute well-balanced development for suburb. region area by suburb dispersion of trading companies. Fifth, on the way to Trade Automation establishment & its enlargement process. producing enormous demand for over-all telecommunication such as hardware. software. network makes opportunity to progress telecommunication industry & concerned industries. Finally. Trade Automation accelerate change of employment structure leading unnecessary labors on the industries of office & logistics to manufacturing area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.97-114
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• 2018

The East Asian region, an important part of Korea's imports and exports, is expected to grow further driven by the geographical, political, economic, social, and cultural complementarity. With the recent increase in imports and exports, the port trade volume between Korea and East Asian countries is also growing. However, due to various factors, such as economic size, growth rate, port infrastructure level, and geographical location of these countries, the volume of traffic with these ports is fluctuating. Despite much research on the volatility of port trade volume and changes in port network, this study tries to supplement the gap in a more detailed study of ports in Korea and East Asia since these kinds of studies are limited. The purpose of this study is to analyze the trend of distribution routes of export container cargo among ports in Korea and to present policy and practical implications of Korean trading companies, shipping companies, logistics companies, and port authorities. This study analyzes the variability of the trade volume between Korea's major ports and Daedong. Results show that Shanghai, Ningbo, Ho Chi Minh, and Haiphong were the most important factors in terms of size and volume increase. In terms of ports, the Busan port is the port responsible for trades with Yantai, Weihai, Hakata, Kobe, Ho Chi Minh, and Haiphong; Incheon port deals with Lianyungang, Tianjin, Osaka, Kobe, Ho Chi Minh, Haiphong; Gwangyang port trades with Tianjinxingang, Weihai, Yokohama, Mihn and Tanjong, and Ulsan port is strategically important for the Yantai, Lianyungang, Nagoya, Kobe, Ho Chi Minh and Portkelang ports. Therefore, the Korean government, port authorities, and shipping and logistics companies need to strengthen logistic network cooperation with these ports and actively promote investments in them.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.2
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• pp.147-165
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• 2020

The aim of this study is to find out Korean electronic industries' production network in Hanoi Red River Delta, Vietnam and its change based on customer-following overseas expansion. In-depth interviews with Korean subcontractors were conducted to examine the characteristics of customer-following overseas expansion of Korean subcontractors. Korean subcontracting corporations in electronic industries have expanded into Vietnam as the suppliers to Korean transnational corporations. Since 1990s, Korean corporations have invested into Vietnam but since late 2000s its industrial and geographical concentration has been shifted from textile and clothing industries in Southern Vietnam to electronics in Northern Vietnam. The customer-following overseas expansion of the subcontractors has emerged in three aspects: physical proximity, asymmetrical inter-firm relations and organizational embeddedness. During the process of customer-following overseas expansion, Korean electronic industry production network was transplanted into Vietnam and partially modified. This is because the company's hierarchy and difficulties in changing its trading relationship have affected the process of advancing into overseas markets. Korean transnational corporations seek to establish a stable suppliers through expansion accompanying with its subcontractors, and providing financial and non-financial support to its subcontractors.