• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.926-930
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• 2010

This paper is about a development framework, which is required to develop of security system is based on component. With applying of SDLC(system development life cycle) of information system, the application of information security products DLC is required at this point of time. In this paper, we review NIST requirement specification of development method, requirement criteria of SDLC in each stage, and major security guidelines of risk assessment. Also we are reviewed major security element of SDLC, and to aid understanding of security framework based on component, present the relationship fo security design and DFD in respect of spoofing for the outside entity based on threat tree STRIDE.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.879-882
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• 2021

The telemetry standard adopts SOQPSK-TG with excellent power and bandwidth efficiency as a modulation technique, and LDPC code with excellent performance as an error correction code. The SOQPSK-TG transmitter consists of a precoder and a CPM modulator. Rather than implementing each receiver separately, the reception performance is improved by combining the trellis and implementing it as a Viterbi decoder. In this paper, the reception performance of LDPC-encoded SOQPSK-TG was evaluated by replacing the Viterbi decoder with a max-log-map decoder capable of soft metric output. As a result of computer simulation in AWGN channel, there is an Eb/No performance gain of about more than 0.7~0.8dB compared to the conventional method.

• New & Renewable Energy
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• v.17 no.3
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• pp.8-15
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• 2021

In this study, we assessed the effect of vitamin components (such as biotin, thiamine-HCl, and folic acid) on microorganism microbial growth and ethanol production was examined to enhance increase the ethanol concentration in the Clostridium autoethanogenum culture process using syngas as a sole carbon source. Biotin and folic acid concentrations of 0.2, 2, 20, and 100 ㎍/L were used in the culture experiments at 0.2, 2, 20, and 100 ㎍/L concentrations. The maximum ethanol concentrations of 2.81 g/L and 3.12 g/L were obtained by adding at 0.2 ㎍/L biotin and folic acid, respectively. Moreover, Thiaminethiamine--HCl at concentrations of 0.5, 5, 50, and 250 ㎍/L were was examined evaluated to in the culture experiments. The maximum ethanol concentration of 2.84 g/L was observed at 0.5 ㎍/L of thiamine--HCl. As a resultThus, the optimized concentrations of biotin, thiamine--HCl, and folic acid were determined at 0.2, 0.5, and 0.2 ㎍/L, respectively, for enhancing increasing the ethanol production. In conclusion, the maximum ethanol production was obtained by adding the minimal concentration of vitamins in C. autoethanogenum culture.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.576-579
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• 2011

Wireless sensor network are widely all over different fields. Because of its distinguished characteristics, we must take account of the factor of energy consumed when designing routing protocol. Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors sends data from the CH (Cluster Head) and then to the BS (Base Station). BCDCP works well in a smallscale network however is not preferred in a large scale network since it uses much energy for long distance wireless communication. TBRP can be used for large scale network, but it weakness lies on the fact that the nodedry out of energy easily since it uses multi-hops transmission data to the Base Station. Here, we proposed a routing protocol. A Cluster Based Energy Efficient Tree Routing Protocol (CETRP) in Wireless Sensor Networks (WSNs) to prolong network life time through the balanced energy consumption. CETRP selects Cluster Head of cluster tree shape and uses maximum two hops data transmission to the Cluster Head in every level. We show CETRP outperforms BCDCP and TBRP with several experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.522-528
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• 2011

The iterative detection and decoding (IDD) has been shown to dramatically improve the bit error rate (BER) performance of the multiple-input multiple-output (MIMO) communication systems. However, these techniques require a high computational complexity since it is required to compute the soft decisions for each bit. In this paper, we show IDD comprised of sphere decoder with low-density parity check (LDPC) codes and present the tree search strategy, called a layer symbol search (LSS), to obtain soft decisions with a low computational complexity. In addition, an adaptive early termination is proposed to reduce the computational complexity during an iteration between an inner sphere decoder and an outer LDPC decoder. It is shown that the proposed approach can achieve the performance similar to an existing algorithm with 70% lower computational complexity compared to the conventional algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.451-464
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• 2016

Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).

• Stress
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• v.25 no.4
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• pp.239-245
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• 2017

Background: A quasi-experimental study with non-equivalent control groups was performed to determine an effect of aromatherapy foot bath on stress and autonomic nervous activity. Methods: To confirm the effect of aromatherapy foot bath, aromatherapy foot bath group was asked to have a bathing by dropping 0.5 cc in 18 L water after blending with a ratio of 6:3:1 with essential oil lavender, lemon, and tea tree and a foot bath group was asked for bathing only by water. Results: Aromatherapy foot bath group showed significant decrease in subjective stress score (t=3.465, p=0.001) and stress index (t=3.021, p=0.004) in addition to simultaneous increase in sympathetic nervous activity (t=-2.913, p=0.005). However, no significant stimulation of parasympathetic nervous system was observed (t=-1.831, p=0.072). Conclusions: As aromatherapy foot bath is a possible effective intervention for stress relief, it can be applied as an effective method to relieve the stress for healthy adults and patients.

• Journal of Pharmaceutical Investigation
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• v.29 no.4
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• pp.355-360
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• 1999

Triflusal is a new antithrombotic agent which inhibits both platelet cyclooxygenase and c-AMP phosphodiesterase activity. The purpose of the present study was to evaluate the bioequivalence of two triflusal capsules, $Disgren^{TM}$ (Myung-In Pharmaceutical Co., Ltd.) and $Tigriri^{TM}$ (Hana Pharmaceutical Co., Ltd.) according to the guidelines of Korea Food and Drug Administration (KFDA). Eighteen normal male volunteers, $22.94{\pm}1.83$ in age and $63.7l{\pm}10.43$ kg in body weight, were divided into two groups and a randomized $2{\times}2$ cross-over study was employed. After one capsule containing 300 mg of triflusal was orally administered, blood was taken at predetermined time intervals and the concentrations of triflusal in serum were determined using HPLC method with UV detector. Pharmacokinetic parameters such as $AUC_t$ $C_{max}$ and $T_{max}$ were calculated and ANOVA test was utilized for the statistical analysis of the parameters. The results showed that the differences in $AUC_t$ $C_{max}$ and $T_{max}$ between two capsules were -0.30%, 0.81 % and -3.03%, respectively when calculated against the $Disgren_{TM}$ capsule. The powers $(1-{\beta})$ for $AUC_t$ $C_{max}$ and $T_{max}$ were 98.29%,84.73% and 81.02%, respectively. Minimum detectable differences $({\Delta})$ at ${\alpha}=0.1$ and $1-{\beta}=0.8$ were all less than 20% (e.g., 12.91%, 18.46% and 19.65% for $AUC_t$ $C_{max}$ and $T_{max}$ respectively). The 90% confid,ence intervals were all within ${\pm}20%$(e.g., $-8.97{\sim}8.37$, $-11.58{\sim}13.22$ and $-16.23{\sim}10.17$ for $AUC_t$ $C_{max}$ and $T_{max}$, respectively). All of the above parameters ($1-{\beta}, {\Delta}$ and 90% confidence intervals) met the criteria of KFDA for bioequivalence, indicating that $Tigriri^{TM}$ capsule is bioequivalent to $Disgren^{TM}$ capsule.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.43 no.4
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• pp.357-364
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• 2017

The aim of this study is to investigate the effect of Hovenia dulcis (oriental raisin tree) extract on ganodermanondiol (GN) contents in Ganoderma lucidum (G. lucidum) mycelia. GN has a triterpenoid structure and is one of the major active components of G. lucidum. Furthermore, we previously proved its inhibitory effects on tyrosinase activity and melanin biosynthesis in B16F10 melanoma cells. In this study, we observed significantly increased GN contents in G. lucidum mycelial extracts supplemented with 15% (v/v) oriental raisin tree extract (ORTE) by HPLC analysis. In addition, melanogenesis was significantly inhibited by G. lucidum extract supplemented with 15% ORTE when compared to G. lucidum extract without ORTE supplementation. Furthermore, mycelial growth of G. lucidum was increased by ORTE supplementation in both solid and liquid cultivation. These results suggest that the oriental raisin tree is useful as natural ingredient for increasing GN biosynthesis as well as whitening effect of G. lucidum.