• Journal of the Korean Society of Tobacco Science
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• v.24 no.1
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• pp.67-73
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• 2002

In light of addressing consumer health concern, coping with anti-tobacco movement, and promoting new product, tobacco industry is actively pursuing to make a new generation of cigarettes with low tar and nicotine deliveries, and less harmful substances. Low tar and low nicotine cigarettes increases their market shares dramatically world wide, especially in KT&G, multinational tobacco companies, EU countries, even in China regulated by CNTC to set up yearly target to lower tar and nicotine deliveries. On the other hand, to design a new cigarette with reduced harmful substances begins to gain speed. The "modified Hoffmann list" publishes thirty plus substances in tobacco leaf and main smoke stream, which is the prime suspect causing health problems. Various ways and means are developed to reduce such components including new tobacco breeds, new curing method, tobacco leaf treatment before processing, selected filtration system, innovated casing system to reduce free radicals, as well as some non conventional cigarette products. In TSRC held this year, the main topic is related to reduce tobacco specific nitrosamines in tobacco leaf. The new generation of cigarette is in the horizon. It still needs a lot help to produce commercial products with satisfied taste and aroma characters. The flavor industry is not regulated by many governments demanding which ingredients might or might not be for tobacco use. However, most of the cigarette companies self impose a list of ingredients to guide flavor suppliers to design flavors. Unfortunately, the number of ingredients in those lists is getting shorter every year. It is understandable that the health is not the only reason. Some cigarette companies are playing safe to protect the company from potential lawsuit, while others are just copying from their competitors. Moreover, it is obvious that it needs more assistance from casings and flavors to design new generation of cigarettes with missing certain flavor components in tobacco leaf and main smoke stream. These flavor components are either non-existed or at lower level at new form of cured tobacco leaf or filtered in the main smoke stream along with reduced harmful substances. The use of carbon filters and other selected filtration system poses another tough task for flavor system design. Specific flavor components are missing from the smoke analysis data, which brings a notion of "carbon taste" and "dryness" of mouth feel. It is ever more demanded by cigarette industry to flavor suppliers to produce flavors as body enhancer, tobacco notes, salivating agents, harshness reducer, and various of aromatic notes provided they are safe to use. Another trend is that water based flavor or flavor with reduced ethanol as solvent is gaining popularity. It is preferred by some cigarette companies that the flavor is compounded with all natural ingredients or all ingredients should he GMO free. The new generation of cigarettes demands many ways of new thinking process. It is also vital for tobacco industry. It reflects the real needs for the consumers that the cigarette product should be safe to use as well as bearing the taste and aroma characters smokers always enjoyed. An effective tobacco flavor system is definitely a part of the equation. The global trend of tobacco industry is like trends of any other industries lead by consumer needs, benefited with new technology availability, affected by the global economy, and subjected for various rules and regulations. Anti-tobacco organizations and media exceptionally scrutinize cigarette, as a legal commercial product. Cigarette is probably the most studied commercial product for its composition, structure, deliveries, effects, as well as its new developmental trend. Therefore, any new trend of cigarette development would be within these boundaries. This paper is trying to point out what it would be like for tobacco industry in the next few yews and what concerns the tobacco industry. It focuses mostly on the efforts to produce safer cigarettes. It is such a vital task for the tobacco industry and its affiliate industries such as cigarette papers, filters, flavors, and other materials. The facts and knowledge presented in this paper might be well known for the public. Some of the comments and predictions are very much personal opinion for a further discussion.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.99-111
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• 2023

The purpose of this study was to provide basic data for setting more detailed standards for baby food and to provide food information that can be used in real-world settings. We purchased 80 snacks and 40 drinks for infants and toddlers from supermarkets and online markets and analyzed tar color, artificial sweeteners, mycotoxins, and nutritional components (e.g., sucrose, sodium, and calcium). Fortunately, it was confirmed that both tar color and sodium saccharin, which do not have detection criteria for labeled foods for infants and toddlers, were not detected. However, acesulfame potassium was detected at 0.07 g/kg in one snack sample. As for myxotoxins, aflatoxin (B1, B2, G1, and G2) and ochratoxin A were not detected. Fumonisin B1, fumonisin B2, and zearalenone were detected in the ranges of 9.78-78.94 ㎍/kg, 5.58-11.73 ㎍/kg, and 2.96-8.83 ㎍/kg, respectively, but only in snacks. Sucrose was detected in 65 of the snacks (0.02-40.94 g/net weight [g]) and in 24 of the drinks (0.12-27.60 g/net weight [g]). Minerals were detected in most of the samples, and in four snacks, the zinc content per net exceeded the tolerable upper intake level for infants. Sixteen snacks exceeded the food standards for sodium content for infants and toddlers, but none of them were labeled as food for infants and toddlers in the product manufacturing report, such that the corresponding standards could not be applied. Therefore, it seems necessary to establish institutional improvements, such as strengthening labeling standards, so that the currently enforced standards can be appropriately applied, and establishing standards for labeled foods for infants and toddlers.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.