Base isolation, one of the popular seismic protection approaches proven to be effective in practical applications, has been widely applied worldwide during the past few decades. As the techniques mature, it has been recognised that, the biggest issue faced in base isolation technique is the challenge of great base displacement demand, which leads to the potential of overturning of the structure, instability and permanent damage of the isolators. Meanwhile, drain, ventilation and regular maintenance at the base isolation level are quite difficult and rather time- and fund- consuming, especially in the highly populated areas. To address these challenges, a number of efforts have been dedicated to propose new isolation systems, including segmental building, additional storey isolation (ASI) and mid-storey isolation system, etc. However, such techniques have their own flaws, among which whipping effect is the most obvious one. Moreover, due to their inherent passive nature, all these techniques, including traditional base isolation system, show incapability to cope with the unpredictable and diverse nature of earthquakes. The solution for the aforementioned challenge is to develop an innovative vibration isolation system to realise variable structural stiffness to maximise the adaptability and controllability of the system. Recently, advances on the development of an adaptive magneto-rheological elastomer (MRE) vibration isolator has enlightened the development of adaptive base isolation systems due to its ability to alter stiffness by changing applied electrical current. In this study, an innovative semi-active storey isolation system inserting such novel MRE isolators between each floor is proposed. The stiffness of each level in the proposed isolation system can thus be changed according to characteristics of the MRE isolators. Non-dominated sorting genetic algorithm type II (NSGA-II) with dynamic crowding distance (DCD) is utilised for the optimisation of the parameters at isolation level in the system. Extensive comparative simulation studies have been conducted using 5-storey benchmark model to evaluate the performance of the proposed isolation system under different earthquake excitations. Simulation results compare the seismic responses of bare building, building with passive controlled MRE base isolation system, building with passive-controlled MRE storey isolation system and building with optimised storey isolation system.
Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.
Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.
The FAT (File Allocation Table) compatible file system has been widely used in mobile devices and memory cards because of its data exchangeability among numerous platforms recognizing the FAT file system. By the way. modern embedded systems have tough demands for instant power failure recovery and superior performance for multimedia applications. The key issue is how to achieve the goals of superior write performance and instant booting capability while controlling compatibility issues. To achieve the goals while controlling compatibility issues. we devised a temporary meta-data journaling scheme for a FAT compatible file system. Benchmark results of the scheme implemented in a FAT compatible file system shows that it really improves write performance of the FAT file system by converting small random write for meta-data update to a large sequential write in journaling area. Also, it provides natural way to implement the instant booting capability. Nevertheless, the file system compatibility is temporarily compromised by the scheme because it stores updated meta-data in the temporary journaling area rather than to their original locations. However, the compatibility can be fully recovered at any time by journal-flushing that copies meta-data in journaling area to their original locations. Generally, the journal-flushing is done before un-mounting a memory card so that it can be used in other mobile devices which recognized FAT file system but not the temporary meta-data journaling scheme.
Journal of the Institute of Electronics Engineers of Korea SD
/
v.43
no.2
s.344
/
pp.42-50
/
2006
Owing to the development of semiconductor processing technology, high density complex circuits can be integrated in a System-on-Chip (SoC). However, increasing energy consumption becomes one of the most important limiting factors. Power estimation at the early stage of design is essential, since design changes at lower levels may significantly lengthen the design period and increase the cost. In this paper, logic level circuits ire levelized and several levels are selected to build power model tables for efficient power estimation. The proposed techniques are applied to a set of ISCAS'85 benchmark circuits to illustrate their effectiveness. Experimental results show that significant improvement in estimation accuracy and slight improvement in efficiency are achieved when compared to those of a well-known existing method. The average estimation error has been reduced from $9.49\%\;to\;3.84\%$.
Journal of the Korean Society of Marine Environment & Safety
/
v.24
no.1
/
pp.18-28
/
2018
As the Korean navy's capabilities increase, it becomes increasingly necessary to develop sufficient navigational capabilities and train proficient seafarers. However, in terms of securing personnel resources, seafarers will need to be utilized more effectively due to the population decline of recent years. This paper reviews the use of civilian maritime personnel to research potential resources and uses the U.S. military sealift command as a benchmark. As a result, it has been found that it is possible to increase naval combat capability through the establishment of like a military sealift command organization to operate defense civilian support vessels. In addition, it is possible to train civilian seafarers by utilizing the current national education system through existing maritime universities. Furthermore, taking these actions will allow the ROK navy to operate its onboard ship reserve service and designated international ship system more efficiently.
Due to the diverse utilization of multimedia, interests are increasing towards processing (saving, editing, searching, etc) three dimensional object data. This paper proposes and realizes a retrieval system for three dimensional objects using reflective symmetry. For the retrieval method, a reflective symmetric axis with a projector is used. The symmetric plane is calculated by the reflection symmetry, and the depth buffer is calculated for the symmetric plane. Then, by applying the Fourier Transform to the depth buffer, the feature vector for the object is generated and retrieved. For the sample of inquiry, the model of similar symmetry was extracted using the benchmark data from Konstantz University. Considering that most of the objects have symmetrical characteristics, the proposed method of retrieving three dimensional objects using a reflective symmetric surface is an outstanding retrieval system.
Recently, many researches have shown that even photosynthetic light-harvesting pigment-protein complexes can have quantum coherence in their excitonic energy transfer at cryogenic and physiological temperatures. Because the protein supplies such noisy environment around pigments that conventional wisdom expects very short lived quantum coherence, elucidating the mechanism and searching for an applicability of the coherence have become an interesting topic in both experiment and theory. We have previously studied the quantum coherence of a phycocyanin 645 complex in a marine algae harvesting light system, using Poisson mapping bracket equation (PBME). PBME is one of the applicable methods for solving quantum-classical Liouville equation, for following the dynamics of such pigment-protein complexes. However, it may suffer from many defects mostly from mapping quantum degrees of freedom into classical ones. To make improvements against such defects, benchmarking targets with more accurately described dynamics is highly needed. Here, we fall back to reduced hierarchical equation of motion (HEOM), for such a purpose. Even though HEOM is known to applicable only to simplified system that is coupled to a set of harmonic oscillators, it can provide ultimate accuracy within the regime of quantum-classical description, thus providing perfect benchmark targets for certain systems. We compare the evolution of the density matrix of pigment excited states by HEOM against the PBME results at physiological temperature, and observe more sophisticated changes of density matrix elements from HEOM. In PBME, the population of states with intermediate energies display only monotonically increasing behaviors. Most importantly, PBME suffers a serious issue of wrong population in the long time limit, likely generated by the zero-point energy leaking problem. Future prospects for developments are briefly discussed as a concluding remark.
Journal of the Korea Institute of Information and Communication Engineering
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v.14
no.1
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pp.138-144
/
2010
Tachyon primary system which introduces recently is a high performance supercomputer that composed with AMD Barcelona nodes. In this paper, we will verify the performance and parallel scalability of TachyonIn by using multi-zone NAS Parallel Benchmark(NPB) which is one of a program with hybrid parallel method. To test performance of hybrid parallel execution, B and C classes of BT-MZ in NPB version 3.3 were used. And the parallel scalability test has finished with Tachyon's 1024 processes. It is the first time in Korea to get a result of hybrid parallel computing calculation using more than 1024 processes. Hybrid parallel method in high performance computing system with multi-core technology like Tachyon describes that it can be very efficient and useful parallel performance benchmarks.
Ratyal, Naeem;Taj, Imtiaz;Bajwa, Usama;Sajid, Muhammad
KSII Transactions on Internet and Information Systems (TIIS)
/
v.12
no.10
/
pp.4903-4929
/
2018
In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.
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