• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.157-163
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• 2017

The binary and interpolation search algorithms are the most famous among search area algorithms, the former running in $O(log_2n)$ on average, and the latter in $O(log_2log_2n)$ on average and O(n) at worst. Also, the interpolation search use only the probability of key value location without priori information. This paper proposes another search algorithm, which I term a 'hybrid block and interpolation search'. This algorithm employs the block search, a method by which MSB index of a data is determined as a block, and the interpolation search to find the exact location of the key. The proposed algorithm reduces the search range with priori information and search the reduced range with uninformed situation. Experimental results show that the algorithm has a time complexity of $O(log_2log_2n_i)$, $n_i{\simeq}0.1n$ both on average and at worst through utilization of previously acquired information on the block search. The proposed algorithm has proved to be approximately 10 times faster than the interpolation search on average.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.2
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• pp.45-54
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• 2016

For the design of landscape, quantitative research is very important data for the designer. In this regard, this study analyzed the rhythm of the wall of Oksan Seowon, which horizontally ascends the slope, as the principles of design. This resulted in the deduction of the numerical proportion and progression, which became design motifs and proposed a design method, which can be applied in landscape rhythm design. The Oksan Seowon is a very valuable cultural heritage, where a very meticulous design principles were found as a result of the analysis of the slope rhythm, for which the proportion and scale were employed. A principle of proportion was found, where an asymmetric balance was formed by weighting the lower part of the slope, in accordance with the degree of the slope. Also, The scale of the height of the wall was based on the human scale. The aesthetic rhythmic design progression was derived from the area and the horizontal line rhythm of the walls. Also, They found out the Fibonacci series and golden ratio. The fact that cultural heritage was analyzed of aesthetic design principles by the very systematic quantitative method is of great significance. Moreover, derived motifs proposed examples of an application of analyzed rhythm progression to the landscape rhythm design. This research will be able to function as the frame and data for the design method of the landscape rhythm.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.