• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.57-75
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• 2024

This study aimed to investigate the current state and educational needs of risk education related to science and technology as perceived by secondary science teachers. A survey was conducted with a total of 366 secondary science teachers. The results are as follows. First, There were more teachers who had not provided education on risks arising from science and technology in terms of risk perception, risk assessment, and risk management than those who had not. Global warming was the most common risk taught by teachers, followed by earthquakes, artificial intelligence, and traffic accidents. Second, teachers recognized that they lacked understanding that the achievement standards of the 2022 revised science curriculum include risks that may occur due to science and technology, but they thought they were prepared to teach. Third, teachers recognized that their understanding of risk perception was higher than that of risk management and risk assessment. Fourth, the experience of teachers in training on risk was very limited, with fewer having training in risk assessment and risk management compared to risk perception. The most common training experienced was in laboratory safety. Fifth, teachers recognized that their capabilities for the 10 goals of risk education were not high. Middle school teachers or teachers majoring in integrated science education evaluated their capabilities relatively highly. Sixth, many teachers thought it was important to address risks in school science education. They prioritized 'information use', 'decision-making skills', and 'influence of mass media', in that order, for importance and called for urgent education in 'action skills', 'information use', and 'influence of risk perception'. Seventh, as a result of deriving the priorities of education needs for each of the 10 goals of risk education, 'action skills', 'influence of risk perception', and 'evaluate risk assessment' were ranked 1st, 2nd, and 3rd, respectively.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.225-285
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• 2017

In regard to the regulations related to the RPA(Remotely Piloted Aircraft), which is sometimes called in other countries as UA(Unmanned Aircraft), ICAO stipulates the regulations in the 'RPAS manual (2015)' in detail based on the 'Chicago Convention' in 1944, and enacts provisions for the Rules of UAS or RPAS. Other contries stipulates them such as the Federal Airline Rules (14 CFR), Public Law (112-95) in the United States, the Air Transport Act, Air Transport Order, Air Transport Authorization Order (through revision in "Regulations to operating Rules on unmanned aerial System") based on EASA Regulation (EC) No.216/2008 in the case of unmanned aircaft under 150kg in Germany, and Civil Aviation Act (CAA 1998), Civil Aviation Act 101 (CASR Part 101) in Australia. Commonly, these laws exclude the model aircraft for leisure purpose and require pilots on the ground, not onboard aricraft, capable of controlling RPA. The laws also require that all managements necessary to operate RPA and pilots safely and efficiently under the structure of the unmanned aircraft system within the scope of the regulations. Each country classifies the RPA as an aircraft less than 25kg. Australia and Germany further break down the RPA at a lower weight. ICAO stipulates all general aviation operations, including commercial operation, in accordance with Annex 6 of the Chicago Convention, and it also applies to RPAs operations. However, passenger transportation using RPAs is excluded. If the operational scope of the RPAs includes the airspace of another country, the special permission of the relevant country shall be required 7 days before the flight date with detail flight plan submitted. In accordance with Federal Aviation Regulation 107 in the United States, a small non-leisure RPA may be operated within line-of-sight of a responsible navigator or observer during the day in the speed range up to 161 km/hr (87 knots) and to the height up to 122 m (400 ft) from surface or water. RPA must yield flight path to other aircraft, and is prohibited to load dangerous materials or to operate more than two RPAs at the same time. In Germany, the regulations on UAS except for leisure and sports provide duty to avoidance of airborne collisions and other provisions related to ground safety and individual privacy. Although commercial UAS of 5 kg or less can be freely operated without approval by relaxing the existing regulatory requirements, all the UAS regardless of the weight must be operated below an altitude of 100 meters with continuous monitoring and pilot control. Australia was the first country to regulate unmanned aircraft in 2001, and its regulations have impacts on the unmanned aircraft laws of ICAO, FAA, and EASA. In order to improve the utiliity of unmanned aircraft which is considered to be low risk, the regulation conditions were relaxed through the revision in 2016 by adding the concept "Excluded RPA". In the case of excluded RPA, it can be operated without special permission even for commercial purpose. Furthermore, disscussions on a new standard manual is being conducted for further flexibility of the current regulations.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.9
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• pp.1265-1273
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• 2012

The purpose of this study was to investigate the BMI, intake of snacks, and perceptions and use of food and nutrition labels by middle school students (144 boys and 189 girls) in Chuncheon area. The average height and weight of boys were $171.0{\pm}6.4$ cm and $61.0{\pm}11.4$ kg, respectively, whereas those of girls were $160.0{\pm}4.8$ cm and $50.8{\pm}6.6$ kg, respectively. Average body mass index (BMI) of boys and girls were $20.8{\pm}3.3$ and $19.8{\pm}2.4$, respectively (p<0.01). Dietary intake attitude score of girls ($34.39{\pm}5.66$) was higher than that of boys ($33.92{\pm}5.40$) (p<0.05). Subjects bought and ate snacks 1 to 3 times per week (40.2%) by themselves, and most consumed snacks were cookies (23.1%), instant noodles (16.2%), ice cream (13.2%), and candy and chocolates (13.2%). The most important factor in purchasing of snacks was 'taste' ($4.49{\pm}0.67$). When subjects bought processed foods, the rates of reading food labels was 86.6%. The most important factor of the food labels was 'expiration date' (42.9%). The degree of reading food labels on processed foods by girls ($22.70{\pm}5.72$) was higher than that of boys ($20.96{\pm}5.35$) (p<0.01). Of the 13.2% of subjects that did not read food labels, the reason why was that they were not interested (50.0%). Of the 78.4% of subjects that read nutrition labels, the most important component of the nutrition labels was 'calories' (75.9%). The main reason for reading nutrition labels was 'to control weight' (45.6%). In general, use of food labels correlated positively with dietary intake attitude score (p<0.05) and use of nutrition labels (p<0.01). Using multiple regression analysis, we found that 'usefulness of dietary life' was the most significant variable that affects the importance of food and nutrition labels. Therefore, development of an educational program on food and nutrition labels for adolescents will be effective in improving dietary life.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1895-1904
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• 2015

Foodborne illness associated with food service establishments is an important food safety issue in Korea. In this study, foodborne pathogens (Bacillus cereus, Clostridium perfringens, Escherichia coli, pathogenic Escherichia coli, Listeria monocytogenes, Salmonella spp., Staphylococcus aureus, and Vibrio parahaemolyticus) and hygiene indicator organisms [total viable cell counts (TVC), coliforms] were analyzed for food and environmental samples from foodservice establishments at schools in Gyeonggi province. Virulence factors and antimicrobial resistance of detected foodborne pathogens were also characterized. A total of 179 samples, including food (n=66), utensil (n=68), and environmental samples (n=45), were collected from eight food service establishments at schools in Gyeonggi province. Average contamination levels of TVC for foods (including raw materials) and environmental samples were 4.7 and 4.0 log CFU/g, respectively. Average contamination levels of coliforms were 2.7 and 4.0 log CFU/g for foods and environmental swab samples, respectively. B. cereus contamination was detected in food samples with an average of 2.1 log CFU/g. E. coli was detected only in raw materials, and S. aureus was positive in raw materials as well as environmental swab samples. Other foodborne pathogens were not detected in all samples. The entire B. cereus isolates possessed at least one of the diarrheal toxin genes (hblACD, nheABC, entFM, and cytK enterotoxin gene). However, ces gene encoding emetic toxin was not detected in B. cereus isolates. S. aureus isolates (n=16) contained at least one or more of the tested enterotoxin genes, except for tst gene. For E. coli and S. aureus, 92.7% and 37.5% of the isolates were susceptible against 16 and 19 antimicrobials, respectively. The analyzed microbial hazards could provide useful information for quantitative microbial risk assessment and food safety management system to control foodborne illness outbreaks in food service establishments.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

• Journal of Nutrition and Health
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• v.47 no.3
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• pp.214-220
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• 2014

Purpose: The purpose of this study was to assess hygiene status of meals for poorly-fed children through microbiological quality. Methods: Meals were provided by two social enterprises, one franchise, and one convenience store. There were a total of six meal samples; two samples (social enterprise meal 1; SEM 1, social enterprise meal 2; SEM 2) from two social enterprises, respectively, two samples (franchise meal 1; FM 1, franchise meal 2; FM 2) from one franchise, and two samples (convenience store meal 1; CSM 1, convenience store meal 2; CSM 2) from one convenience store. Microbiological analysis and assessment were performed by Korean food standards codex (KFSC). Results: General bacteria and E. coli in SEM 1 were detected, but the levels were not over KFSC, and Coliform less than $9.2{\times}10$ CFU/g was also detected in seasoned bean sprouts of SEM 1. General bacteria was detected at $1.6{\times}10^6$ CFU/g in cabbage kimchi of SEM 2. Coliform was detected in cabbage kimchi, squid cutlet, stir-fried pork, and fried chicken of FM1 and 2, but the levels were not over KFSC. In addition, S. aureus was detected in cabbage kimchi and seasoned dried white radish of FM 1 and 2 ($9.8{\times}10^2$ CFU/g, $9.4{\times}10^3$ CFU/g respectively), thus was over KFSC. B. cereus was detected in stir-fried pork and fried chicken ($1.2{\times}10^3$ CFU/g, $1.5{\times}10^3$ CFU/g respectively) of FM 1 and 2, thus was over KFSC. Finally, S. aureus was detected in stir-fried dried squid, seasoned spicy chicken, and stir-fried kimchi of CSM 1 and 2, and was over KFSC too ($9.5{\times}10^4$ CFU/g, $2.4{\times}10^2$ CFU/g, $1.3{\times}10^3$ CFU/g respectively). Conclusion: Results of this study suggest that systemic management of hygiene is necessary to safely providing meals to poorly-fed children.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.