• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Korean journal of applied entomology
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• v.14 no.3 s.24
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• pp.97-109
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• 1975

In an attempt to develop an effective integrated system of controlling blast disease of rice caused by Pyricularia oryzae Cav., the possibility of minimizing the disease incidence by proper application of fertilizers has been investigated. Thus the effect of silicate, nitrogen, phosphorus and potassium fertilizers on the development of blast disease as well as the correlation between the rice varieties an4 strains of P. oryzae were studied. The experiments were made in 1971 and 1973 by artificial inoculation and under natural development of the blast disease on rice plants. The results obtained are summarized as follows. 1. Application of silicate fertilizer resulted in the increase of silicate as well as total sugar and potassium content but decrease of total nitrogen and phosphorus in tile leaf blades of rice plants. 2. The ratios of total C/total N. $ SiO_2/total$ N, and $K_2O/total$ N in leaf blades of rice plants increased by the application of silicate fertilizers. There was high level of negative correlation between the ratios mentioned above and the incidence of rice blast disease. 3. Application of silicate fertilizer reduced the incidence of rice blast disease. 4. The over dressing of nitrogen fertilizer resulted in the increase of total nitrogen and decrease of silicate and total sugar content in leaf blades, thus disposing the rice plants more susceptible to blast disease. 5. Over dressing of phosphorus fertilizer resulted in the increase of both total nitrogen and Phosphorus, and decrease of silicate content in the leaf blades inducing the rice plants to become more susceptible to blast disease. 6. Increased dressing of potash resulted in the increase of silicate content and $K_2O/total$ N ratio but decrease of total nitrogen content in leaf blades. When potassium content is low in the leaf blades of rice plants, the additional dressing of potash to rice plant contributed to the increase of resistance to blast disease. However, there was no significant correlation between additional potassium application and the resistance to blast disease when the potassium content is already high in the leaf blades. 7. When four rice varieties were artificially inoculated with three strains of P. oryzae, the incidence of blast disease was most severe on Pungok, least severe on Jinheung and moderate on Pungkwang and Paltal varieties. 8. Disease incidence was most severe on the second leaf from top and less sever on top and there leaf regardless of the fertilizer application when 5-6 leaf stage rice seedlings of four rice varieties were artificially inoculated with three strains of P. oryzae. 9. The pathogenicity of three strains of P. oryzae was in the order of $P_1,\;P_2,\;and\;P_3$ in their virulence when inoculated to Jinheung, Paltal, Pungkwang varieties but not with Pungok. The interaction between strains of P. oryzae and rice varieties was significant.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5
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• pp.80-92
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• 2010

The purpose of this study was to analyze drainage facilities in mountainous urban neigbborhood parks--Baebongsan Park and Ogeum Park--in Seoul. Based on an analysis of existing drainage facilities, the volume of storm water runoff (VSW), the runoff rate of open channels(ROC), and the detention capacity of open charmels(DCOC) by each drainage watershed, the coefficient of runoff rate(CROC) as evaluated to be relevant between VSW and ROC and the coefficient of the detention capacity of open channe1s(CDCOC) as evaluated with DCOC compared to VSW were estimated and analyzed by parks and by watersheds. The results are as follows: 1. The total drainage area of Baebongsan Park was 34.13ha including surface runoff area(15.05ha; 44.09%), open channel area(l4.60ha; 42.78%), and natural waterway area(4.48ha; 13.13%). The total drainage area of Ogeum Park was 20.39ha including open channel area (10.14ha; 49.73%), ridge-side gutter area(7.17ha; 35.16%), surface runoff area (2.52ha; 12.36%), and natural waterway area (0.56ha; 2.75%). In Baebongsan Park, the portion of surface runoff was comparatively higher while the portion of artificial drainage area was higber in Ogeum Park. 2. In Baebongsan Park drainage districts were largely divided: VSW was $7.28m^3/s$ in total(average $0.23m^3/s$). Comparatively, tbe VSW in Ogeum Park, including smaller drainage districts, was $4.37m^3/s$ in total(average $0.12m^3/s$). 3. The ROC of Baebmgsan Park was $11.58m^3/s$ in total(average $0.77m^3/s$) and the CROC was 5.26, while in Ogeum Park, the ROC was $15.40m^3/s$(average $0.34m^3/s$) and tbe CROC was 8.87 higher than that of Baebongsan Because the size and slope of the open channel in Baebongsan Park was higher, the average ROC was larger, while tbe CROC of Ogeum Park was higher than that of Baebongsan Park, for the VSW in Ogeum Park was comparatively lower. 4. The DCOC in Baebongsan Park was $554.54m^3$ and the average of CDCOC was 179.83. That of Ogeum Park was $717.74m^3$ and the average of the CDCOC was 339.69, meaning that the DCOC of Ogeum Park was so much higber that drainage facilities in Ogeum Park were built intensively. This study was focused m the capacity of the drainage facilities in mountainous urban neighborhood parks by using the CROC to evaluate relevance between VSW and ROC and the CDCOC to evaluate the DCOC as compared with VSW. The devised methodology and coefficient for evaluating drainage facilities in mountainous urban neighborhood parks may he universally applicable through additional study. Further study m sustainable urban drainage systems for retaining rainwater in a reservoir and for enhancing ecological value is required in the near future.

• Journal of Animal Science and Technology
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• v.46 no.2
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• pp.261-272
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• 2004

This study was conducted to investigate indices affecting composts maturity for swine manure compost produced in a commercial composting facility with air-forced from the bottom. The composting was made of swine manure mixed with puffing rice hull(6: 4) and turned by escalating agitator twice a day. Composting samples were collected periodically during a 45-d composting cycle at that system, showing that indices of Ammonium-N to Nitrate-N ratio were sensitive indicators of composting quality. Pile temperature maintained more than 62$^{\circ}C$ and water contents decreased about 20% for 25days of composting. A great variety and high numbers of aerobic thermophilic heterotropic microbes playing critical roles in stability of composts have been examined in the final composts, sbowing that they were detected $10^8$ to $10^{10}$ $CFUg^{-1}$ in mesophilic bacteria, $10^3$ - $10^4$ in fungi and $10^6$ - $10^8$ in actinomycetes, respectively. The results of this study for detennining a factor affecting compost stability evaluations based on composting steps were as follows; 1. Ammonium-N concentrations were highest at the beginning of composting, reaching approximately 421mg/kg. However Ammonium-N concentrations were lower during curing, reaching approximately l04mg/kg just after 45 day. The ratio between $NH_4-N$ and $NO_3-N$ was above II at the beginning of composting and less than 2 at the final step(45 day). 2. Seed germination Index was dependent upon the compost phytotoxicity and its nutrition. The phytotocity caused the GI to low during the period of active composting(till 25 days of composting time) depending on the value of the undiluted. After 25 days of composting time, the GI was dependent upon compost nutrition. The Gennination index of the final step was calculated at over 80 without regard to treatments. 3. E4: E6 ratio in humic acid of composts was correlatively decreased from 8.86 to 6.76 during the period of active composting. After 25 days of composting time, the E4: E6 was consistently decreased from 6.76 to 4.67($r^2$ of total composting period was 0.95). 4. Water soluble carbon had a tendency to increase from 0.54% to 0.78%during the period of active composting. After 25 days of composting time, it was consistently decreased from 0.78% to 0.42%. Water soluble nitrogen increased from 0.22% to 0.32% during the period of 15 days after initial composting while decreased from 0.32% to 0.21% after 15days of composting. In consequence, the correlation coefficient($r^2$) between water soluble carbon and water soluble nitrogen was 0.12 during the period of active composting mule was 0.50 after 25 days of composting time

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.142-171
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• 2019

The dragon is an imaginary animal that appears in the legends and myths of the Orient and the West. While dragons have mostly been portrayed as aggressive and as bad omens in the West, in the Orient, as they symbolize the emperor or have an auspicious meaning, dragons signify a positive meaning. In addition, as the dragon symbolizes the emperor and its type has been diversified considering it as a divine object that controls water, people have tried to express it as a figure. The records related to dragons in the Goryeo dynasty appeared with diverse topics in 'History of Goryeo' and are generally contents related to founding myths, rituals for rain, and Shinii (神異), etc. The founding myth emphasizes the legality of the Goryeo dynasty through the dragon, and this influenced the formation of the dragon's descendants. In addition, the ability to control water, which is a characteristic of the dragon, was symbolized as an earth dragon related to the rainmaking ritual, i.e., wishing for rain during times of drought. Since the dragon was the symbol of the royal family, the use of the dragon by common people was strictly restricted. Furthermore, the association of a bronze dragon mirror with the royal family is hard to be excluded. The type and quantity of bronze double dragon mirrors discovered to have existed during the Goryeo dynasty is great, and the production and the distribution of bronze mirrors with double dragons seem to have been more active compared to other bronze mirrors, as bronze mirrors with double dragons produced during Goryeo and bronze mirrors originating in China were mixed. Therefore, in this article, the characteristics of diverse bronze mirrors from the 10th century to the 14th century in China were examined. It seems that the master craftsmen who produced bronze mirrors with double dragons during the Goryeo dynasty were influenced by Chinese composition patterns when making the mirrors. Because there were many cases where a bronze mirror's country of origin could not easily be determined, in order to identify the differences between bronze double dragon mirrors produced during the Goryeo dynasty and bronze mirrors produced in China, meticulous analysis was required. Thus, to ascertain that Goryeo mirrors were not imitations of bronze mirrors with double dragons originating in China but produced independently, the mirrors were examined using the bronze double dragon mirror type classification system existing in our country. Bronze mirrors with double dragons are classified into three types: Type I, which has the style of the Yao dynasty, includes the greatest proportion; however, despite there being only a small quantity for comparison, Types II and III were selected for the analysis of the bronze mirrors with double dragons made in Goryeo because they have unique composition patterns. As mentioned above, distinguishing bronze mirrors made during Goryeo from bronze mirrors made in China is challenging because Goryeo bronze mirrors were made under the influence of China. Among them, since the manufacturing place of the bronze mirrors with double dragons found at the nine-story stone pagoda in Woljeongsa Temple in Pyeongchang is questionable and the composition pattern of the bronze mirror is hard to find on bronze mirrors with double dragons made in China, the manufacturing place of those bronze mirrors were examined. These bronze mirrors with double dragons were considered as bronze mirrors with double dragons made during the Goryeo dynasty adopting the Yao dynasty style composition pattern as aspects of the composition pattern belonged to Type I, and the detailed combination of patterns is hard to find in mirrors produced in China.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Korean Journal of Heritage: History & Science
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• v.41 no.1
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• pp.5-19
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• 2008

Thirty six samples of Western asia glass vessel shards which were excavated from South Mound of Hwangnamdaechong were each measured for thickness, pore size and specific gravity and analyzed for ten major compositions and thirteen trace elements. The glass samples with colorless, greenish blue and dark purple blue were well classified by principal component analysis(PCA). All glass shards of Hwangnamdaechong belonged to Soda glass system ($Na_2O-CaO-SiO_2$) which have the range of 14~17% $Na_2O$ and 5~6% CaO. The corelation coefficients of (MgO, $K_2O$) and (MnO, CuO) showed above 0.90. The concentrations of thirteen trace elements apparently differentiated from colorless, greenish blue and dark blue glasses. We found that thirteen trace elements were very important indices for studying raw material of glass and the origin of glass making. Colorless glass : The specific gravity is $1.50{\pm}0.04$. Circle or oval circle pores are observed with regular direction in internal zone and the longest one is about 0.35 mm. The raw material of sodium must be the plant ash because sodium glasses contain HCLA(High CaO, Low $Al_2O_3$) and HMK(high MgO, high $K_2O$) and suggested to Sasanian glass. The total amount of coloring agent of colorless glass is below 1 % which is too small to attribute to the color. Greenish blue glass : The specific gravity is $1.58{\pm}0.04$. The fine pores which are 0.1~0.2mm are dispersed in internal zone. Sodium glasses are distributed to HCLA and HMK. Therefore the greenish blue glass also have used plant ash for raw material of sodium with the same as colorless glass. It was also suggested to the glass of Sasanian. The total amount of coloring agent of greenish blue glass is about 4% under the influence of working MnO, $Fe_2O_3$ and CuO. Dark purple blue glass : The specific gravity is $1.48{\pm}0.19$. There are rarely pores in internal zone. They are distributed to HCLA and LMK(Low MgO, Low $K_2O$) and suggested to Roman glass. The raw material of sodium is estimated to natron. The total amount of coloring agents of greenish blue is about 3% by $Fe_2O_3$ and CuO. These studies for western asia glass shards from South Mound of Hwangnamdaechong could be used in the future as the standard data which could be compared with those of other several graves in Korea and dispersed in foreign areas.