• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.91-95
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• 2002

Electronic commerce over the Internet is predicted to grow at an ever-increasing rate over the next few years, with on-line sales already heading for several billion. Many companies are using this new sales channel, and a few retailers now have established major on-line sales sites. There have been some successes, particularly in technology, business-to-business and niche markets. This paper has been produced to summarise the basics of electronic commerce system, covering on-line catalogues and on-line purchasing. Electronic commerce systems consists of the authoring tools and web applications, the electronic payment technology, and the security and transaction processing.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1067-1076
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• 2003

Database sharing system (DSS) refers to a system for high performance transaction processing. In DSS, the processing nodes are locally coupled via a high speed network and share a common database at the disk level. Each node has a local memory and a separate copy of operating system. To reduce the number of disk accesses, the node caches database pages in its local memory buffer. In this paper, we propose a dynamic transaction routing algorithm to balance the load of each node in the DSS. The proposed algorithm is novel in the sense that it can support node-specific locality of reference by utilizing the primary copy authority assigned to each node; hence, it can achieve better cache hit ratios and thus fewer disk I/Os. Furthermore, the proposed algorithm avoids a specific node being overloaded by considering the current workload of each node. To evaluate the performance of the proposed algorithm, we develop a simulation model of the DSS, and then analyze the simulation results. The results show that the proposed algorithm outperforms the existing algorithms in the transaction processing rate. Especially the proposed algorithm shows better performance when the number of concurrently executed transactions is high and the data page access patterns of the transactions are not equally distributed.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.484-493
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• 2001

As real-time database systems are extended to the distributed computing environment, the need to apply the existing real-time concurrency control schemes to the distributed computing environment has been made. In this paper we propose an efficient concurrency control scheme for distributed real-time database system. Our proposed scheme guarantees a transaction to commit at its maximum, reduces the restart of a transaction that is on the prepared commit phase, and minimizes the time of the lock holding. This is because it raises the priority of the transaction that is on the prepared commit phase in the distributed real-time computing environment. In addition, it reduces the waiting time of a transaction that owns borrowed data and improves the performance of the system, as a result of lending the data that the transaction with the raised priority holds. We compare the proposed scheme with DO2PL_PA(Distributed Optimistic Two-Phase Locking) and MIRROR(Managing Isolation in Replicated Real-time Object Repositories) protocol in terms of the arrival rate of transactions, the size of transactions, the write probability of transactions, and the replication degree of data in a firm-deadline real-time database system based on two-phase commit protocol. It is shown through the performance evaluation that our scheme outperforms the existing schemes.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1064-1073
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• 2002

In this paper, we design and implement the Wireless Transaction Protocol (WTP) proposed by the Wireless Application Protocol (WAP) forum using a protocol development tool, SDL Development Tool (SDT). And we conduct a comparative performance evaluation of the WTP implementation with other three implementations that are based on different implementation models respectively: the server model, the coroutine model, and the activity-thread model. To implement WTP, we first use Unified Modeling Language (UML) for analyzing the protocol requirement and defining the protocol engine architecture. Next, we use Software Development Language (SDL) to design the protocol engine in details and then generate the WTP implementation automatically with the aid of SDT The code size of the WTP implementation generated by SDT is 62% larger than the other three implementations. However, its throughput and system response time for transaction processing is almost equal to the other three implementations when the number of concurrent clients is less than 3,000. If more than 5,000 concurrent clients tries, the transaction success rate abruptly decreases to 10% and system response time increases to 1,500㎳, due to the increased protocol processing time. But, it comes from the fact that the load overwhelms the capacity of the PC resource used in this experimentation.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.1-11
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• 2021

Purpose: The franchise system started by Singer Sewing Machine in the US is acting as a national economic growth engine in terms of job creation and economic growth. In China, the franchise system was introduced in the mid-1980s. And since joining the WTO, it has grown by 5-6% every year. However, compared to the growth rate of franchises, studies on shared growth between the chain headquarters and franchisees were insufficient. Accordingly, recent studies related to shared growth between the chain headquarters and franchisees have been active in China. The purpose of this study is to examine the knowledge transfer system between the knowledge creation, knowledge sharing, and the use of knowledge by franchise chain headquarters in China. In addition, the relationship between franchise satisfaction and performance is identified. Research design, data, and methodology: The data were collected from franchise stores in Sichuan, China, and were conducted with the help of ○○ Incubation, a Sichuan Province-certified incubator. From November 2020 to January 2021, 350 copies of the questionnaire were distributed in China, and 264 copies were returned. Of these, 44 copies with insincere answers and response errors were excluded, and 222 copies were used for analysis. The data were analyzed with SPSS 22.0 and AMOS 22.0 statistical packages. Result: The results of this study are as follows. First, knowledge creation has been shown to have a statistically significant impact on knowledge sharing and knowledge utilization. In particular, the effectiveness of knowledge creation was higher in knowledge sharing than in knowledge utilization. And we can see that knowledge sharing also has a statistically significant e ffect on knowledge utilization. Second, knowledge sharing was not significant for transaction satisfaction and business performance, and knowledge utilization was significant for transaction satisfaction and business performance. These results can be said to mean less interdependence of the Chinese franchise system. Finally, transaction satisfaction was statistically significant to business performance. The purpose of this study was to examine the importance of knowledge management to secure long-term competitive advantage for Chinese franchises. This study shows that knowledge sharing is important for long-term franchise growth. And we can see that there is a lack of knowledge sharing methods in the case of franchises in China. I n addition, it was found that the growth of Chinese franchises requires systematization of communication, information sharing measures and timing, help from chain headquarters, and mutual responsibility awareness.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.12
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• pp.57-64
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• 2008

In this paper, we propose a system-level simulator for the performance analysis of a Solid-State Disk (SSD) in PC environment by using TLM (Transaction Level Modeling) method. Our method provides quantitative analysis for a variety of architectural choices of PC system as well as SSD. Also, it drastically reduces the analysis time compared to the conventional RTL (Register Transfer Level) modeling method. To show the effectiveness of the proposed simulator, we performed several explorations of PC architecture as well as SSD. More specifically, we measured the performance impact of the hit rate of a cache buffer which temporarily stores the data from PC. Also, we analyzed the performance variation of SSD for various NAND Flash memories which show different response time with our simulator. These experimental results show that our simulator can be effectively utilized for the architecture exploration of SSD as well as PC.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.151-157
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• 2022

In this paper, the performance of various blockchain consensus algorithms was compared and analyzed as a method to increase the transaction cost and processing time during NFT transactions and to increase the transaction stability requirements that occur during smart contract execution. Network reliability and TPS are evaluation items for performance comparison. TPS and the stability of the Consensus algorithm are presented for three evaluation items. In order to establish a standardized expression for each evaluation item, the reliability of the node and the success rate of the smart contract were considered as variables in the calculation formula, and the performance of the consensus algorithm of the three groups, PoW/PoS, Paxos/Raft and PBFT, was compared under the same conditions. / analyzed. As a result of the performance evaluation, the network reliability of the three groups was similar, and in the case of the remaining two evaluation items, it was analyzed that the PBFT consensus algorithm was superior to other consensus algorithms. Through the performance evaluation equations and results of this study, it was analyzed that when the PBFT consensus processing process is reflected in the consensus process, the network reliability can be guaranteed and the stability and economic efficiency of the consensus algorithm can be increased.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.400-405
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• 2001

This paper addresses an effective approach of training neural networks classifiers for credit card fraud detection. The proposed approach uses evolutionary programming to trails the neural networks classifiers based on maximization of the detection rate of fraudulent usages on some ranges of the rejection rate, loot minimization of mean square error(MSE) that Is a common criterion for neural networks learning. This approach enables us to get classifier of satisfactory performance and to offer a directive method of handling various conditions and performance measures that are required for real fraud detection applications in the classifier training step. The experimental results on "real"credit card transaction data indicate that the proposed classifiers produces classifiers of high quality in terms of a relative profit as well as detection rate and efficiency.

• International Commerce and Information Review
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• v.10 no.1
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• pp.315-327
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• 2008

According to the Bank Profitabilities Statistics of OECD members, Our domestic banks applying commissions for both exchange and selling/buying foreign currencies are evaluated as much higher than those of other countries banks. The theory indicates an analysis results and comparison in between banks over the world. Our domestic bank assert that, in general, the aggregated banking commission income is lower than those of other countries by comparing in the field of non-interests profits. Viewing by another analysis in details, some commission rate applying to domestic services are far below than cost basis, but other commission rate applying to foreign currency transaction services is abnormally higher. Such unfair rate should be lowered to the similar level to other banks in the world and also the actual cost should be reasonably reevaluated in the reasonable manner. One more thing, The writer suggest that domestic banks should spend efforts to increase their income by improving and diversifying with the various type of new commissions applied to domestic market, such as multi-functional financial services, expanding ATM services, electronic settling technique etc under today's rapidly changing and opening world financial market.