• Applied Biological Chemistry
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• v.39 no.5
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• pp.368-373
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• 1996

Korean general medicinal herbs-sasam, gilkyung, jakyak, danggwi, hwangki, and chunkung-were added In the normal brewing procedure as a raw material or in the distilling procedure as a packing material. The distillates from the former procedure and those from the latter procedure were compared in quality and distillation properties. As distillation proceeded, pH of the medicinal herb wine distillate and the control(not added herbs) distillates were decreased, whereas that of the herb packing distillate was increased slowely of $0.05{\sim}0.97$ during $1{\sim}4$ fractions and decreased remarkably of $0.92{\sim}0.98$ afterward. Average pH was the highest of 5.70 in jakyak and lowest of 4.37 In gilkyung. Absorbances of the herb Packing distillate were decreased rapidly of $0.60{\sim}1.59$ in the $1{\sim}4$ fractions but slowely of $0.19{\sim}0.54$ in the next fractions. During distillation both fractional alcohol concentration of the distillates and distillation rate were decreased. Their values were decreased more slowly than the control. Distillation rates of medicinal herb wine distillate were varied by medicinal herb varieties and alcohol concentration of fermented wine. Danggwi and control showed the highest average distillation rate as $0.12\;m{\ell}/sec$ and gilkyung the lowest value as $0.073\;m{\ell}/sec$. Maximum concentration of index component, paeoniflorin of jakyak was observed as 293 mg% in the 5th fraction of herb packing distillate and decrusin of danggwi as 3514 mg% In the 1st fraction of herb packing distillate. The extraction rate was 41.3% for paeoniflorin and 20.5% for decrusin. From sensory evaluation, the highest overall Qualify was observed in the medicinal herb wine distillate of hwangki added wine, the next in those of danggwi and jakyak added wine.

• Applied Biological Chemistry
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• v.49 no.3
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• pp.227-232
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• 2006

Styela clava (also called as rough sea squirt or leathery tunicate) is regarded as native to the northwest Pacific region including Korea and widely distributed in parts of northwestern Europe, North America and Australia. To evaluate Styela clava as a potential bioactive agent, the antioxidant activity of aceton extracts from Styela clava (whole, substance and tunic) was tested by measuring inhibitory effect of $H_2O_2$ induced DNA damage using comet assay. Also, anticancer activity on human colon cancer cell (HT-29) was investigated by MTT reduction assay. The $200\;{\mu}M$ $H_2O_2$ induced DNA damage was inhibited with Styela clava aceton extract in dose dependent manner in human leukocytes. The maximum inhibition was by 62.8, 62.1 and 78.3% at the concentration of $50\;{\mu}g/ml$ of whole, substance and tunic extracts, respectively. The aceton extracts from S. clava were also found to inhibit the growth of human colon cancer cell. The cell proliferation rates decreased to 26.9, 30.6 and 12.0% at the concentration of $500\;{\mu}g/ml$ of whole, substance and tunic extracts, respectively. These results support that aceton extracts from S. clava may be a potential candidate as a possible antimutagenic and chemotherapeutic agent.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.439-450
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• 2015

This study objects to find characteristics in chemical tanker markets and to determine optimal chemical tanker size using a total shipping cost in main trading route of asia chemical tankers .Precedent studies of determination of the optimal ship size and case studies about chemical tankers was carried out and tried to introduce a cost model which is applicable to chemical tanker. This study is dependant on numerical analysis and involves scenario analysis to minimize sensitivity of results. This analysis shows as follows. First, 12,000DWT tanker is an optimal size on the 'Far East-Middle East' services, 9,000DWT tanker is a most competitive on the 'Far East-South East Asia' services and 3,000DWT tanker is a most economic size on the 'Inner Far East' services at average market situation. Second, the bigger size of chemical tanker, the more competitive advantage the tanker will obtain when bunker fuel prices rise. Small size ship gets more competitive during bunker prices down. Third, market fluctuation of time charter rate for chemical tanker is less than 20% against its average time charter hire which means less volatile. And tanker's competitiveness per each size is remained mostly same when time charterer rates rise at same proportion. Fourth, bigger size chemical tankers have cost advantages when tanker's quantity of each part cargo increase. And small-sized tanks are more competitive when part cargo scales decrease. For the last, ship's port stay strongly influences on the determination of the optical tanker size. When vessel has shorter port stay, bigger-sized tanker will be more competitive and even can be competitive if applies in short voyage as well.

• Korean Security Journal
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• no.61
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• pp.109-135
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• 2019

The purpose of this study is to investigate the occupational diseases(the number of medical treatment) of fire officials by using time-series analysis. The results of the study are as follows. First, the average rates of the occupational diseases of fire officials were as follows: ① internal diseases were the highest at 9.24% in December, the lowest at 7.76% in February, ② otolaryngologic diseases were the highest at 9.29% in December, the lowest at 6.74% in August, ③ dermatological diseases were the highest at 10.03% in July, the lowest at 7.35% in January and February, ④ surgical diseases were the highest at 10.38% in November, the lowest at 5.62% in February, ⑤ orthopedic diseases were the highest at 9.69% in March, the lowest at 7.52% in November, ⑥ neurosurgical diseases were the highest at 9.33% in April, the lowest at 6.82% in February, ⑦ neurological diseases were the highest at 9.47% in December, the lowest at 7.06% in October, and ⑧ mental health diseases were the highest at 9.93% in December, the lowest at 6.51% in May. Second, the seasonal decomposition of the disease occurrence of fire officials were described by assigning seasonal factor(S), trend factor(T), circulation factor(C) and irregular factor(R): ① internal diseases were 1.075(S) × 189.355(T·C) × 1.174(R) = 238.975(F), ② otolaryngologic diseases were 1.023(S) × 69.605(T·C) × 1.040(R) = 74.000(F), ③ dermatological diseases were 1.002(S) × 73.088(T·C) × 0.874(R) = 64.000(F), ④ surgical diseases were 1.099(S) × 27.229(T·C) × 0.669(R) = 20.000(F), ⑤ orthopedic diseases were 1.115(S) × 73.182(T·C) × 1.213(R) = 99.000(F), ⑥ neurosurgical diseases were 0.993(S) × 27.836(T·C) × 1.303(R) = 36.000(F), ⑦ neurological diseases were 1.029(S) × 62.417(T·C) × 1.152(R) = 74.000(F), and ⑧ mental health diseases were 1.210(S) × 8.781(T·C) × 1.035(R) = 11.000(F).

• Korean Journal of Poultry Science
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• v.30 no.2
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• pp.135-143
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• 2003

This study was conducted to investigate feeding effects of the high pressure boiled extract(HPBE) of the Ogol chicken on weight gain and serum lipid composition of rat. Rats(S.D,♂) were fed with normal feed(T$_1$), normal feed ＋ herb HPBE(T$_2$), normal feed ＋ Ogol chicken HPBE(T$_3$), normal feed ＋ mixture of cross­bred Ogol chicken HPBE hydrolyzed with Flavourzyme 0.1% for 35 days. During experimental period, the effects of the treatments on growth performance, plasma triglyceride(TG) and cholesterol were determined. The effects of feeding HPBE on growth performance and serum triglyceride levels in rat. After a 6 day treatment, body weights were 39.96g, 44.56g, 43.34g, and 45.99g for T$_1$, T$_2$, T$_3$ and T$_4$ groups respectively. The growth rates of T$_2$ and T$_4$ groups were significantly(P<0.05) higher than T$_1$ group, but the differences were not observed after 18 days of feeding period. Triglyceride contents were 62.89${\pm}$6.24mg/dl, 55.70${\pm}$6.76mg/dl, 43.60${\pm}$4.68mg/dl and 45.00${\pm}$3.75mg/dl for T$_1$, T$_2$, T$_3$ and T$_4$ groups respectively, where T$_1$ group was significantly (P<0.05) higher than T$_3$ and T$_4$ groups. In serum total cholesterol contents, there was no significant difference among the groups. GOT(glutamic oxaloacetic transaminase) and GPT(glutamic pyruvic transaminase) also showed similar levels among the treatments.

• Korean Journal of Poultry Science
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• v.43 no.2
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• pp.111-118
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• 2016

Mycotoxins are secondary metabolites produced by molds, such as Aspergillus, Fusarium and Penicillium, that have adverse effects on animals and humans. Aflatoxin, ochratoxin, zearalenone, fumonisin and deoxynivalenol are the mycotoxins of greatest agro-economic importance and cause acute disease called mycotoxicoses. Mycotoxicosis in poultry birds results in decreased meat/egg production, immunosuppressant, and hepatotoxicosis. Some of toxins or their metabolites may be retained in animal or human tissues and induce health problems. This study was designed to develop a sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous detection and quantification of mycotoxins, such as aflatoxin $B_1$, aflatoxin $M_1$, ochratoxin A, zearalenone, fumonisin B and deoxynivalenol, in chicken liver and kidney tissues. The mycotoxins were extracted and purified using modified QUECHERS methods, separated by LC and detected by an electrospray ionisation interface (ESI) and tandem MS. Good precision and linearity were observed for most of six mycotoxins. The recovery test for each mycotoxin in liver and kidney tissues mostly indicated good average recovery rates between 80.94% and 98.10% and the coefficient of variation mostly under 13.78%, except for aflatoxin $M_1$ and fumonisin $B_1$. The limit of detection (LOD) for six mycotoxins was $7.6{\sim}145.79{\mu}g/kg$ in liver tissues and $6.07{\sim}197.20{\mu}g/kg$ in kidney tissues. The quantification limits (LOQ) for 6 mycotoxins were in the range $23.04{\sim}441.78{\mu}g/kg$ in liver tissues and $18.40{\sim}597.59{\mu}g/kg$ in kidney tissues, respectively. The developed multi-mycotoxin method in this study permits simultaneous, simple, and rapid determination of several co-existing mycotoxins in chicken liver and kidney tissues.

• Korean Journal of Poultry Science
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• v.42 no.3
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• pp.247-256
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• 2015

There are approximately 1,500 broiler farms in Korea, each raising 55,000 birds. Ninety-five percent of the farms are contracted with Integration Company. According to the Korean broiler performance index, broilers in Korea are marketed at 32 days with 1.52 kg of body weight. In contrast, the market age and body weight of broilers are 47 days/2.8 kg in the United States and 42 days/2.5 kg in Europe. Because of the younger market age of the Korean broiler, the pre-starter feed is important. Chicks exhibit poor absorption of dietary nutrients up to 7 days after hatching due to an immature digestive system and low enzyme secretion rate and activity. At the beginning of hatching, chicks obtain their nutrients from the egg yolk sac. It is highly recommended that chicks, after consuming the nutrients in the egg yolk sac, are given supplemented pre-starter feed to increase early growth rates and improve the performance of broiler production. Pre-starter nutrient requirements are not expressed in NRC, so Korean feeding standards for poultry and commercial breeding companies determine the nutrient requirements of pre-starter broiler chickens. Three approaches are followed to formulate specially designed pre-starter feeds for broiler chicks: (i) selective use of raw materials, (ii) proper standards of nutrient supply, and (iii) application of feed additives such as exogenous enzymes. In the selection of raw materials, those with high digestibility can be used. The absorption rate of carbohydrates in grains can be increased through feed processing at high temperature and high pressure. Soy proteins and fish meal can also be added as protein sources. As an energy source, vegetable oils are preferred over animal fats because of the former's high digestibility. It is suggested that the levels of proteins and amino acids are higher in pre-starter feed than in starter feed. With regard to energy, the sources of energy are more important than the levels of energy in feed. Feed additives such as exogenous enzymes can be used to improve nutrient digestibility. In addition, organic acids and plant extracts can be used as alternatives to animal growth promoters to stimulate immunity and prevent diseases. The growth performance of broilers is affected by various factors, such as management and disease control, in addition to the nutritional strategy; however, nutritional strategies play an important role in improving the productivity of broilers. Therefore, nutritional strategies, along with management and disease control, are required for improving the productivity of broilers in Korea.