• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.949-960
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• 2003

Main memory database systems use the different implementation techniques to sturucture and organize the user dta and system catalogs, since traditional database systems are optimized for the characteristics of disk storage environment. We present, in this paper, the design considerations for our main memory database system $ALTIBASE^{TM}$ that is currently applied to the time-critical applications. We focus on the design issues of storage manager in $ALTIBASE^{TM}$. The major components are introduced, and features and characteristics of transaction management and recovery method are described. We also present the database replication mechanism and its conflict resolution mechanism for high availability and performance. In order to evaluate our transaction performance, we show various experimental reports as measured by the TPS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1607-1621
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• 2018

The financial industry, which guarantees a credible transaction and can not permit forgery of its transaction information, has hitherto adhered to a traditional centralized ledger management method. However, the blockchain technology has a decentralization which has been regarded as unsafe for the time being, and the more reliable transaction agreement and data integrity are guaranteed The world's financial industry and the IT world is causing the wave. Nevertheless, the inherent characteristics of the blockchain, such as the irreversibility of block information within a blockchain and the sharing of blocks between blockchain participants, can not avoid conflicts with the privacy laws. The purpose of this study is to investigate the problems related to deletion and the third party supply of personal information by focusing on these characteristics of the blockchain and to suggest the technical alternatives of the applicable blockchain and the improvement direction of the personal information protection law for using of blockchain technology.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.41-50
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• 2022

The primary purpose of this study is to identify various factors that affect farmland prices according to changes in the actual transaction price of farmland over the past decade, and to use this to derive policy implications for price stabilization. To this end, the farmland price model are constructed at the parcel level in the case area (Namwon-si, Jinju-si). The analysis method is based on the Hedonic price function, and the OLS and the quantile regression are used for the parcel level model. As a result of estimating the parcel level farmland price model in the case area, the larger the parcel area, the lower the farmland price, and the higher the farmland price outside the agricultural promotion area. It was found that there was a price difference according to the type of special purpose areas, and the location characteristics showed some differences across the cities. The farmland price models presented in this study are suitable for identifying the factors affecting farmland prices, and are expected to be highly utilized in that it is possible to construct flexible variables suitable for regional characteristics.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.276-279
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• 2003

무선랜 기술과 이동통신 기기의 비약적인 발전은 기존의 e-비즈니스를 넘어 모바일 비즈니스라는 새로운 사업 기회를 창출하였으며, 학계와 업계에 많은 관심을 불러 일으키고 있다. 기존의 모바일 비즈니스에 대한 연구는 모바일 비즈니스의 새로운 특성이나 서비스에 대한 다양한 관점을 보여주고 있으나, 제시된 특성인 결국 비즈니스 거래(Transaction)에 어떠한 변화를 가져왔는지를 체계적으로 설명하지는 못했을 뿐 아니라, 모바일 서비스의 일반적 특성이나 사례들이 모바일 비즈니스의 새로운 특성과 어떻게 연관되는지에 대한 고려를 하지 않았다. 따라서, 본 연구에서는 모바일 비즈니스가 비즈니스 거래(Transaction)에 영향을 끼친 기본 특성들을 효율설(Efficiency)과 효과성(Effectiveness) 측면에서 제시하고, 모바일 비즈니스에서 기존의 e-비즈니스에 비하여 새로이 가능케 된 기능들에는 어떠란 것들인 존재하는지를 알아보고, 이들과 특성과의 연관관계를 나타내었다. 그리고 모바일 비즈니스의 특성과 기능이 새로운 사업 기회의 측면에서 어떤 시사점을 갖는지 또한 제시하였다.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.101-111
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• 1999

The Web-based simulation was introduced for conducting simulation experiments in the Internet and the Web. Due to the use of the Java language, the Web-based simulation can have such characteristics as reusability, portability, and the capability of execution on the Web. Most of existing Web-based simulation tools have focused mainly on the development of the runtime simulation libraries and mechanisms on the Web. Thus, the model development work in such Web-based simulation tools still requires hand-written coding of model developers. This paper presents a visual model development environment for the Web-based simulation. The proposed environment provides a framework for model development and animation. To show the effectiveness of the proposed environment, we perform simulation experiments for transaction routing algorithms in a distributed transaction processing system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.226-233
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• 2005

Ubiquitous computing is a study area explained in a myriad of contexts and technological terms. So when you try to define it with simple words, it gets even more confusing. Payment. however, refers in nature to an act of money transfer from one entity to another, and it is obvious that a payment method will be valued as long as the transaction can be completed with safety no matter what technology was used. In the end, the key to U-payment is convenience and security in the transfer of financial information. The purpose of this paper is to find a desirable U-payment scheme by looking at the characteristics of seamlessness under the ubiquitous environments, Strong Personal Device, and peer-based if information transactions. We also propose U-SDT Protocol integrating critical technologies such as Radio Frequency Identification (RFID), Bluetooth, Personal Payment Device, Account Managing Application and Transaction ID as a way to make transactions between users seamless and secure better privacy protection.

• Journal of the Korean Home Economics Association
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• v.44 no.5 s.219
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• pp.79-87
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• 2006

The purpose of this study is to analyze whether service quality and perceived risk have an effect on purchase intention and satisfaction of the fashion merchandise in internet shopping malls. To this end, a survey was conducted from June 20 to July 30 in 2005, among married women aged in their 20s and 30s, on their purchase experience of fashion merchandise from internet shopping malls. The survey was conducted over the internet with 306 subjects. The statistical analysis methods were frequency analysis, reliability analysis, factor analysis, and multiple regression analysis. First, the service quality factors were determined to be reliability, responsibility, ease of transaction, order convenience, and site characteristics. Perceived risk factors were determined to be merchandise risk, information exposure risk, social psychological risk, and function risk. Second, service quality factors of responsibility, ease of transaction, order convenience, site characteristics and perceived risk factor of social psychological risk had an effect on internet purchase intention of the fashion merchandise. Greater site use convenience, lower price, simpler ordering, and lower social psychological risk were all positively correlated with higher internet purchase intention of fashion merchandise. Third, nice quality factors and social psychological risk had an effect on satisfaction degree in internet shopping.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.119-143
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• 2003

Trust has been identified as a key component in many e-Commerce studies. The purpose of this study is to find out which factors play a major role in building trust and how the built-up trust affect consumer's purchase intention in Internet used-car transactions. Based on the information asymmetry, TAM(Technology Acceptance Model), and the trust theory, our research model includes factors such as a buyer's propensity-to-trust, institutional characteristics(inspection and warranty policy), word-of-mouth referral, perceived size, and perceived benefits as independent variables. The model also includes trust as a mediate variable, intention to purchase as a dependent variable and perceived quality risk as a moderate variable. The research model is tested by analyzing 787 sample data gathered from Internet used-car transaction sites. The result shows that the trust has significant effects on the online purchase intention, and institutional characteristics has been identified as the most significant factor for the trust of Internet used-car sites. The independent factors influencing trust vary depending on the level of perceived quality risk. For users who perceive the quality risk low, the perceived benefits explain a little portion of the purchase intention. However, those who perceive quality risk high would purchase used-cars only when they have trust on the Internet sites, indicating that trust play an important role as a mediate variable. This study suggests that enhancing the trust in Internet used-car sites is important to increase online transactions.