• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.63-68
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• 2003

This paper is to measure the sensitivity of relations in communication network operation. In order to procure an important adequacy in the network operation and quality improvement, it is necessary to increase network operation efficiency and analyze the characteristic of network operation. Finally, we analyze costing appropriate operation, propose profit increase scheme and apply realistic business. First of all it's important to improve and estimate a proper operating cost thoroughly and comprehensively. Because the important issue of this process is quality process and this quality process occurs customers' satisfaction, therefore, to make a mutual relation in-between individual change of each element is to analyze a reasonable standard. So, for this reason we study on structuring nice moods for network operation and estimating many scenarios for measuring efficiency. Especially those in economic and sensitivity based. It will be the development of analyzing methods which suites the service and communication system. The result of this study gives a basis for making a flexible and highly predictable system by pre configured sensitivity analysis of each scenarios.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.7-16
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• 2001

The Principle objective of this paper is to introduce a systematic approach to identifying similar container ports in Asia. For this, it analyses data on port facilities, port facility availability, port service level total container throughput, and economic index, by using Multidimentional Scaling (MDS) method. Based on the analysis it identifies five groupings of similar container ports in Asia within which Port comparison can be justifiably made, evaluates a present position of five groupings on the basis of factors used to compare container ports in Asia ; and finally proposes policy implications for operation efficiency of Pusan container port in comparison with Kaohsiung Port. The major implication is that both the Kaosuing and the Pusan port have to strengthen port facility to attract more traffic, and particularly, Pusan Port has to reinforce the number of berth, total length of berth. and yard areas.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.223-241
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• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.65-74
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• 2003

Location-based service is an important spatiotemporal database application area that provides the location-aware information of wireless terminals via positioning devices such as GPS. With the rapid advances of wireless communication systems, the requirement of mobile application areas including traffic, mobile commerce and supply chaining management became the center of attention for various research issues in spatiotemporal databases. In this paper we present the A-Quadtree, an efficient indexing method for answering location-based queries where the movement vector information (e.g., speed and velocity) is not presented. We implement the A-Quadtree with an index structure for object identifiers as a.Net component to apply the component to multiplatforms. We present our approach and describe the performance evaluation through various experiments. In our experiments, we compare the performance with previous approaches and show the enhanced efficiency of our method.

• Korean Journal of Veterinary Service
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• v.31 no.4
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• pp.555-566
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• 2008

This study was performed to evaluate the effects of medicinal herbs on characteristics and qualities of pork for 6 months using 102 post-weaning piglets, To improve the bod gain and feed efficiency rate, post-weaning piglets were fed with medicinal herbs from 4 to 10 weeks after birth, while grower pigs for 60 days before slaughter. Daily body gain of piglets of experimental group was higher(493.1g) than control(447.8g), with feed demand index 1.49 versus 1.6 times in control, indicating. The more pigs were fed with herbs, the higher body gain was observed. Among carcass characteristics, dressing percentage and backfat thickness were higher in experimental group(68.26% and 14.52mm) than control(67.39% and 14.36mm). Experimental group(0.5% medicinal herb-fed) produced more A class carcass. In fatty acid analysis, meats of experimental group contained less saturated(more unsaturated) fatty acids than control. Especially, palmitic acid, a precursor of cholesterol, was less and oleic acid was more contained than control. In amino acid analysis, essential amino acids(methionine and isoleucine) were increased in meats of experimental group. In concolusion, feeding medicinal herbs has effects such as increased body gain, improved feed demand, and carcass class on piglets and improved meat quality on growers.

• Journal of Microbiology and Biotechnology
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• v.30 no.6
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• pp.804-810
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• 2020

The profitability of the dairy and beef industries is largely affected by the actually achieved reproductive efficiency. Although a large proportion of cows worldwide are bred by artificial insemination (AI) services, many potential factors affecting the outcome of pregnancy by AI remain to be addressed. In the present study, we investigated the vaginal microbiota by high-throughput sequencing of 16S rRNA gene and analyzed their association with differential pregnancy outcomes (i.e., pregnant vs. nonpregnant) of multiple AI services in dairy cows. Sequencing of the V3-V4 region totally produced 512,046 high-quality sequences that were computationally clustered into 2,584 operational taxonomic units (OTUs). All OTUs were taxonomically assigned to 10 bacterial phyla. There were statistically significant differences among the three AI service times (T1, T2 and T3) with respect to the Shannon index and number of observed OTUs (p < 0.05). Bray-Curtis distance-based PCoA analysis also revealed that T2 group could be significantly distinguished from T1 and T3. However, no significant difference between the pregnant and nonpregnant cows was found in confidence regarding both alpha diversity and beta diversity. These results could help us better understand the possible influence of vaginal microbial community on pregnancy outcomes of AI service in cows.

• Journal of Information Management
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• v.39 no.4
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• pp.21-46
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• 2008

The Result of this study (1)In the case of KDI school of public policy and management, since it makes up a very interesting and diversified racial environment that shapes the multinational global community, there must be careful considerations for foreign students together with wide publicity about Korea on the side of the school headquarters. (2)The library must become familiar with the ways to utilize outside organizations in order to provide user education to the foreign students. (3)In order to make it perfectly sure for them to provide not only the secondary materials such as bibliography, index, and abstract, but also the necessary full-text from the preparatory stage of the students' studies. (4)The library must grasp the students' needs through communication and must promote the efficiency of library operation by introducing an information service strategy measure similar to that of FISP so they can acknowledge and provide necessary information to fulfill the students' academic needs in advance.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.35-49
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• 2015

The purpose of this paper is to see what the problem is and what the direction of the strategy of asset management after this study has analyzed asset management status of nonlife insurance companies according to interest rate trends, analyzing in time series asset state, management asset lists, asset distribution state, securities list and total asset yield of Nonlife insurance companies during year 2009~2014. As the study result, nonlife insurance companies have managed assets in stability than profitability according to safety asset was increased, but risky asset was decreased. Performance rate of total asset was dropped according to interest rate declined trends. Trend between stock index and performance rates of total asset was not accord. The correlation coefficient between interest rate and performance rates of total asset was highly plus, but the correlation coefficient of KOSPI and performance rate of total asset showed minus.

• Journal of the Korean Geographical Society
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• v.30 no.1
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• pp.68-92
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• 1995

Recentry the structure of the retail trade have been chanaed with its environmantal changes. Some studies may be necessary on the changing process of environment and fundamental structure analyses of the retail trade. This study analyzes the location of retail trades, inhabitants' behavior in retail tredes and their desirable utilization scheme of them in Kwangju-si. Some study methods, contents and coming-out results are as follows: 1. Retail trades can be classified into independent stores, chain-stores (supermarket, voluntary chain and frenchiise system and convenience store), department stores, cooperative associations, traditional, markets mail-order marketing, automatic vending and others by service levels, selling-items, prices, managements, methods of retailing and store or nonstore type. 2. In Kwangju, the environment of retail trades is related to the consumers of population structure: chanes in consumers pattern, trends toward agings and nuclear family, increase of leisur: time and female advances to society. Rapid structural shift in retail trade has also been occurred due to these social changes. Traditionl and premodern markets until 1970s altere to supermarkets or department stores in 1980s, and various types, large enterprises and foreign capitals came into being in 1990s. 3. The locational characteristics of retail trades are resulted from the spatial analysis of the total population distribution, and from the calculation of segregation index in the light of potential demand. The densely-populated areas occurs in newly-built apartment housing complex which is distributed with a ring-shaped pattern around the old urban core. The numbers and rates of the aged over sixty in Kwangsan-gu and the circumference area of Mt.Moodeung, are larger and higher where rural elements are remarkable. A relation between population distribution and retail trade are analysed by the index of population per shop. The index of the population number per shop is lower in urban center, as a whole, being more convenient for consumers. In newly-formed apartment complex areas, on the other, the index more than 1,000 per shop, meeting not the demands for consumers. Because both the younger and the aged are numerous in these areas, the retail trade pattern pertinent to both are needed. Urban fringes including Kwangsan-gu and the vicinity of Mt.Moodeung have some problems owing to the most of population number per shop (more than 1, 500) and the most extensive as well. 4. The regional characteristic of retail trade is analyzed through the location quotient of shops by locational patterns and centerality index. Chungkum-dong is the highest-order central place in CBD. It is the core of retail trades, which has higher-ordered specialty store including three big department stores, supermarkets and large stores. Taegum-dong, Chungsu-dong, Taeui-dong, and Numun-dong that are neiahbored to Chungkum-dong fall on the second group. They have a central commercial section where large chain stores, specialty shopping streets, narrow-line retailing shops (furniture, amusement service, and gallary), supermarkets and daily markets are located. The third group is formed on the axis of state roads linking to Naju-kun, Changseong-kun, Tamyang-kun, Hwasun-kun and forme-Songjeong-eup. It is related to newly, rising apartment housing complex along a trunk road, and characterized by markets and specialty stores. The fourth group has neibourhood-shopping centers including older residential area and Songjeong-eup area with independent stores and supermarkets as main retailing functions. The last group contains inner residential area and outer part of a city including Songjeong-eup. Outer part of miscellaneous shops being occasionally found is rural rather than urban (Fig. 7). 5. The residents' behaviors using retail trade are analyzed by factors of goods and facilities. Department stores are very high level in preference for higher-order shopping-goods such as clothes for full dress in view of both diversity and quality of goods(28.9%). But they have severe traffic congestions, and high competitions for market ranges caused by their sma . 64.0% of respondents make combined purpose trips together with banking and shopping. 6. For more efficiency of retail-trading, it is necessary to induce spatial distribution policy with regard to opportunity frequency of goods selection by central place, frontier regions and age groups. Also we must consider to analyze competition among different types of retail trade and analyze the consumption behaviors of working females and younger-aged groups, in aspects of time and space. Service improvement and the rationalization of management should be accomplished in such as cooperative location (situation) must be under consideration in relations to other functions such as finance, leisure & sports, and culture centers. Various service systems such as installment, credit card and peremium ticket, new used by enterprises, must also be carried service improvement. The rationalization and professionalization in for the commercial goods are bsically requested.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.