• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.59-70
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• 2024

Objectives: The purpose of this study is to analyze each country's infectious disease response capacities and, based on this, find areas for improvement in Korea's infectious disease management response. Methods: First, the capacity to respond to the COVID-19 infectious disease was analyzed by country using the SPAR scores of 96 countries around the world released by WHO in 2022. Second, we analyzed each country's specific COVID-19 quarantine performance using Our World in Data and the Global Health Security Index (GHSI). Results: First, the quarantine intensity index on January 24, 2021 was the highest in the Southeast Asia branch at 67.6, which had strong quarantine measures, and the lowest at 44.5 in the Africa branch. As of December 31, 2022, the quarantine intensity index in Europe was significantly lowered to 11.6. Second, the factor that influenced the SPAR indicator on the total number of patients per million population was national laboratory (C4), p=.027, and the factor that influenced the total number of deaths per million population was infection prevention and control (C9), p=.005., Risk Communication and Community Participation (C10) p=.040. The influential factor on GDP per capita was infection prevention and control (C9) p=.009, and the influential factor on GHSI was infection prevention and control (C9) p=.002. Conclusion: The research findings indicate that it was difficult to find a correlation between the SPAR, which is each country's self-assessment of their infectious disease capacities, and the number of COVID-19 cases or the intensity of pandemic responses. However, mortality rates, as well as factors such as the Global Health Security Index (GHSI) and national income, appear to be somewhat influenced. For future improvements in infectious disease management and response in our country, it is necessary to develop pandemic strategies that can reduce socio-economic costs based on more scientific and reliable data like JEE or GHSI, especially in preparation for potential unknown emerging infectious diseases. Based on this, proactive decision-making led by a control tower of experts and effective health communication are also required to respond to public health crises at a national level.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.177-200
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• 2017

This writer have thus far reviewed the civil and criminal obligations of the directors of a parent company that sponsored financially troubled affiliates. What was discussed here applies to logistics companies in the same manner. Hanjin Shipping cannot expect its parent company, Korean Air to prop it up financially. If such financial aid is offered without any collateral, under Korean criminal law, the directors of the parent company bears the burden of civil and criminal responsibility. One way to get around this is to secure fairness in terms of the process and the content of aid. Fairness in terms of process refers to the board of directors making public all information and approving such aid. Fairness in terms of content refers to impartial transactions that block out any possibilities of the chairman of the corporate group acting in his private interest. In the case of Korean Air bailing out Hanjin, the meeting of board of directors were held five times and a thorough review was conducted on the risks involved in the loans being repaid or not. After the review, measures to guard against undesirable scenarios were established before finally deciding on bailing out Hanjin. As such, there are no issues. In terms of the fairness of content, too, there were practically no room for the majority shareholder or controlling shareholder to pocket profits at the expense of the company. This is because the continued aid offered to a financially troubled company (i.e. Hanjin Shipping) was a posing a burden to even the controlling shareholder. This writer argues that the concept of the interest of the entire corporate group needs to be recognized. That is, it must be recognized that the relationship of control and being controlled between parent company and affiliate company, or between affiliate companies serves a practical benefit to the ongoing concern and growth of the group and is therefore just. Moreover, the corporate group and its affiliates, as well as their directors and management must recognize that they have an obligation to prioritize the interests of the corporate group ahead of the interests of the company that they are directly associated with. As such, even if Korean Air offered a loan to Hanjin Shipping without collateral, the act cannot be treated as an offense to law, nor can the directors be accused of damages that they bear the responsibility of compensating under civil law.

• Journal of Chest Surgery
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• v.32 no.5
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• pp.448-455
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• 1999

Background: Recent developments in techniques of video-assisted thoracic surgery(VATS) and endoscopic equipment has expanded the application of video-assisted surgical procedures in the field of thoracic surgery. Especially, it will probably become the treatment of choice of spontaneous pneumothorax(SP). There is, however, a high recurrence rate, high cost, and paucity of long-term results. We report the results of postoperative follow-up and analyze perioperative parameters affected to recurrence, retrospectively. Material and Method: From march 1992 to march 1997, 276 patients with spontaneous pneumothorax underwent 292 VATS procedures. Conversion to open thoracotomy was necessitated in eight patients, and this patients excluded from the study. Result: The sex distribution was 249 males and 31 females. The mean age was 28.1 12.2 years(range, 15 to 69 years). Primary SP was 237cases(83.5%) and secondary SP was 47cases(16.5%). The major underlying lung diseases associated with secondary SP were tuberculosis 27cases(57.4%) and emphysema 8cases (38.3%). Operative indications included Ipsilateral recurrence 123(43.9%), persistent air-leak 53(18.9%), x-ray visible bleb 40(14.3%), tension 30(10.7%), contralateral recurrence 21(7.5%), uncomplicated first episode 8(2.9%), bilateral 3(1.1%), complicated episode 2(0.7%). Blebs were visualized in 247cases(87%) and 244cases(85.9%) performed stapled blebectomy. Early postoperative complications occurred in 33 cases(11.6%): 16 prolonged air-leak more than 5 days(four of them were required a second operation and found missed blebs); 5 bleeding; 5 empyema; 2 atelectasis; 1 wound infection. No deaths occured. The mean operative time was 52.8 23.1 minutes(range, 20 to 165 minutes). The mean d ration of chest tube drainage was 5.0 4.5 days(range, 2 to 37 days). The mean duration ofhospital stay was 8.2 5.5 days (range, 3 to 43days). At a mean follow-up 22.3 18.4 months(range, 1 to 65 months), 12 patients(4.2%) were lost to follow-up. There were 24 recurrences and seven patients underwent second operation and 6 patients(85.7%) were found the missed blebs. 12 perioperative parameters(age, sex, site, underlying disease, extent of collapse, operative indication, size of bleb, number of bleb, location of bleb, bleb management, pleural procedure, prolonged postoperative air-leak) were analyzed statistically to identify significant predictors of recurrence. The significant predictors of recurrence was the underlying disease[17.0%(8/47): 6.8%(16/237), p=0.038], prolonged postoperative air-leakage[37.5%(6/16): 6.7%(18/268), p=0.001], and pleural procedure [11.4%(19/167): 4.3%(5/117), p=0.034]. Blebectomy has less recurrence rate then non-blebectomy [8.2%(20/244) : 10.0%(4/40), p>0. 5]. However, this difference was not statistically significant(p=0.758). Conclusion: We conclude that it is important that we shoud careful finding of bleb during VATS due to reducing of recurrnece, and cases of no bleb identified and secondary spontaneous pneumothorax were indicated of pleurodectomy. VATS is a valid alternative to open procedure for the treatment of spontaneous pneumothorax with less pain, shorter hospital stay, more rapid return to work, high patient acceptance, less scar and exellent cosmetics. But, there is high recurrence rate and high cost, and than it is necessary to evaluate of long-term results for recurrence and to observate carefully during VATS.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.9
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• pp.1172-1181
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• 2007

This research involved 226 Jeonbuk Province school dietitians as subjects to investigate intake and perceptions of the healthy functional foods. Sixty nine percent of the school dietitians didn't even know about the law enforcement concerning the health functional foods. Although 68.1% of the respondents said that they slightly knew about health functional foods, only 25% knew exactly what it was. As shown in the survey, most didn't have the cognitive understanding did not understand which should be obtained by education. Sixty two percent of the answerers said they had experience of taking health various functional food products of various kinds such as supplements (57.9%), red ginseng products (52.9%), and chlorella products (30.0%). The motive of intake was in the order of fatigue restoration (25.7%), sickness prevention (22.9%), and nutrient replenishment (22.9%). A fascinating fact from this study was that the reason for healthy functional product intake was different between groups that was primarily interested in the products and those that was not. For those who had interest, the reason for intake was for sickness prevention. On the other hand, for those who didn't have any interest, the reasons was primarily for fatigue restoration and they were mostly persuaded by close friends and relatives. Main concerns were in the order of side effects (4.72), efficacy after intake (4.59), cleanliness (4.51), reliability of the company (4.29), and price (4.23). In view of the study, it is clear that a lot of people are showing interest in healthy functional food products. However, dietitians who are experts in food and nutrition lacked knowledge and information on healthy functional food.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.