• Journal of Preventive Medicine and Public Health
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• v.30 no.4 s.59
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• pp.764-778
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• 1997

To find the medical insurance utilization of workers when suffering from low back pain, an analysis was made toward the data of medical insurance benefits matched with the general characteristics of 10,183 workers, who were registered continuously from 1993 to 1995 at a medical insurance cooperation for industrial workers. The results were as follows; 1. The period prevalence of the medical insurance utilization for low back pain for 3 years from 1993 to 1995 was calculated as 17.1% for male workers and 19.4% for female workers. Most common cause of utilization was other dorsopathies including the herniation of lumbar discs. 2. The utilization rate increased significantly as the present age and the age joining the company got older(p<0.001). As the duration of employment got longer, the utilization rate of the male showed the tendency to increase and that of the female increased significantly(p<0.05). Among male workers employed at cement and concrete manufacturing companies showed higher utilization rate and among female laborers showed significantly higher utilization rate than clerical workers(p<0.01). 3. Annual utilization rate for low back pain didn't show any difference, but the portion of other dorsopathies among cause of utilization showed the tendency to increase from 1993 to 1995. 4. The mean number of claims for outpatient medical care for low back pain differed significantly by age, working duration, type of industries, income level(p<0.05), and the mean of total visiting days for care of low back pain differed significantly by working duration. In conclusion, considering the fact that the medical insurance utilization for low back pain increased annually and other dorsopathies including the herniation of dorsopathies were increasing, an effective preventive or management program for low back pain toward worker employed at industries were required.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.161-172
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• 2018

A mixed farming system that includes organic rice production and freshwater fish farming is being called into attention in Korean agricultural industry and rural areas in order to improve farm management and environmental conservation. This study was conducted to evaluate the environmental and ecological value of such mixed farming practices. Expert assessment and rapid assessment method (RAM) of wetland evaluation were employed for this study. Experts have responded that biodiversity conservation including amphibian and reptile habitat (2.39), aquatic insect habitat (2.36), Fishery habitat (2.34), vegetation diversity (2.13), avian habitat (2.05), and experience and education were the most important function of mixed farming. The wetland function evaluation conducted using modified RAM indicated that rice-fish mixed system showed improvements in most of the evaluated functions, compared to the conventional rice paddies. The overall wetland function of rice paddies in rice-fish mixed system was greatly improved as compared with the conventional rice paddies. Rice paddies are known to play an important role in biodiversity maintenance, and provide ecosystem services such as climate modulation and carbon reduction. Rice-fish mixed system of farming may not only improve various ecosystem services of rice paddies, but may increase farm income through value added fish farming, as well as promotion of social services such as education and maintenance of tradition. Additional research is needed for quantitative analysis of the values gained from the most improved wetland function when mixed farming system is actually put into practice, and to utilize the results in advertising of the organic rice, and in various sectors such as food, education and direct payment policy.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.1-12
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• 2016

This study was carried out for the improvement of nutrition and quality of streamed bread. For this purpose, brown rice liquid starter and brown rice sourdough were made and steamed bread was made with different amounts of starter addition followed by a measurement of its physicochemical and sensory characteristics. The pH of dough and titratable acidity tended to decrease significantly according to brown rice sourdough. In addition, the titratable acidity of the control group had significant different by samples. As for the volume of dough, there was no significant difference between the control sample and each sample, but after 15 minutes of fermentation, the volume increased the most in the control sample, with sample D having the least volume. As for volume and specific volume of steamed bread, sample B had the largest at 3.34 and each sample had significant differences based on fermentation time. As for diameter, sample B was the largest at 88.11 and sample D was the smallest at 79.04, with significant differences among samples. As for height of steamed bread, the control group was the highest at 42.91 and sample D was the lowest at41.87, with significant differences among samples. As for the cross-section structure of steamed bread, the porous of sample B, which had the largest volume and specific volume, was the largest with uniform texture and even distribution. L value tended to be higher in the added sampleroups than in the control sample. a value increased as brown rice sourdough increased, and b value was lower when volume and specific volume of the steamed bread increased, which showed a similar trend with that a L value. As for hardness, viscosity, and chewing capacity, sample D was the highest and sample B was the lowest, with significant differences among samples. As a result of measurement of overall preference, sample B had the highest preference with the highest preference in flavor, taste, appearance and texture, and D had the lowest preference with the lowest preference in taste, appearance and texture, with significant differences among samples.

• Fire Science and Engineering
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• v.17 no.1
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• pp.8-20
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• 2003

Natural gas has been supplied through underground pipelines and valve stations as a new city gas in Seoul. In contrast to its handiness the natural gas has very substantial hazards due to fires and explosions occurring from careless treatments or malfunctions of the transporting system. The main objectives of this study are to identify major hazards and to perform risk assessments after assessing reliabilities of the composing units in dealing with typical pipeline networks. there-fore two method, fault tree analysis ;1nd event tree analysis, are used here. Random valve stations are selected and considered its situation in location. The value of small leakage, large rupture, and no supply of liquefied natural gas is estimated as that of top event. By this calculation the values of small leakage are 3.29 in I)C valve station, 1.41 in DS valve station, those of large rup-lure are $1.90Times10_{-2}$ in DC valve station, $2.32$\times$10^{-2}$ in DS valve station, and those of no supply of LNG to civil gas company are $2.33$\times$10 ^{-2}$ , $2.89$\times$10^{-2}$ in each valve station. And through minimal cut set we can find the parts that is important and should be more important in overall system. In DC valve station one line must be added between basic event 26,27 because the potential hazard of these parts is the highest value. If it is added the failure rate of no supply of LNG is reduced to one fourth. In DS valve station the failure rate of basic event 4 is 92eye of no supply of LNG. Therefore if the portion of this part is reduced (one line added) the total failure rate can be decreased to one tenth. This analytical study on the risk assessment is very useful to prepare emergency actions or procedures in case of gas accidents around underground pipeline networks and to establish a resolute gas safety management system for loss prevention in Seoul metropolitan area.

• The Korean Journal of Air & Space Law and Policy
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• v.23 no.2
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• pp.137-172
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• 2008

The earliest safety data programs, the FDR and CVR, were electronic reporting systems that generate data "automatically." The FDR program, originally instituted in 1958, had no publicly available restrictions for protections against sanctions by the FAA or an airline, although there are agreements and union contracts forbidding the use of FDR data for FAA enforcement actions. This FDR program still has the least formalized protections. With the advent of the CVR program in 1966, the precursor to the current FAR 91.25 was already in place, having been promulgated in 1964. It stated that the FAA would not use CVR data for enforcement actions. In 1982, Congress began restricting the disclosure of the CVR tape and transcripts. Congress added further clarification of the availability of discovery in civil litigation in 1994. Thus, the CVR data have more definitive protections in place than do FDR data. The ASRS was the first non-automatic reporting system; and built into its original design in 1975 was a promise of limited protection from enforcement sanctions. That promise was further codified in an FAR in 1979. As with the CVR, from its inception, the ASRS had some protections built in for the person who might have had a safety problem. However, the program did not (and to this day does not) explicitly deal with issues of use by airlines, litigants, or the public media, although it appears that airlines will either take a non-punitive stance if an ASRS report is filed, or the airline may ignore the fact that it has been filed at all. The FAA worked with several U.S. airlines in the early 1990s on developing ASAP programs, and the FAA issued an Advisory Circular about the program in 1997. From its inception, the ASAP program contained some FAA enforcement protections and company discipline protections, although some protection against litigation disclosure and public disclosure was not added until 2003, when FAA Order 8000.82 was promulgated, placing the program under the protections of FAR 193, which had been added in 2001. The FOQA program, when it was first instituted through a demonstration program in 1995, did not contain protections against sanctions. Now, however, the FAA cannot take enforcement action based on FOQA safety data, and an airline is limited to "corrective action" under the program. Union contracts can exclude FOQA from the realm of disciplinary action, although airline practice may be for airlines to require retraining if there is no contract in place forbidding it. The data is protected against disclosure for litigation and public media purposes by FAA Order 8000.81, issued in 2003, which placed FOQA under the protections of FAR 193. The figure on the next page shows when each program began, and when each statute, regulation, or order became effective for that program.

• Korean journal of applied entomology
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• v.47 no.2
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• pp.155-162
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• 2008

The Welsh onion beet armyworm, Spodoptera exigua (Hubner), has attacked Welsh onion and is now the most important pest of Welsh onion in southwestern Korea. The beet armyworm has a wide host range, occurring as a serious pest of vegetable and fields. The relatively high abundance of beet armyworm has stimulated frequent application of insecticides to foliage. Insecticide resistance is a major problem in management of this insect. Accordingly, pesticide application for the control of beet armyworm was tried in both the open field and in laboratory, using 4 synthetic compounds such as metaflumizone and chlorfenapyr, indoxacarb, flufenoxuron, emamectin benzoate. In the laboratory, each developmental stages from eggs, larva to pupa was tested against 4 insecticides. Against the eggs of welsh onion beet armyworm, there was no significantly different with each other. These tested chemicals no killing effect to eggs. However, the population of 1st larva hatched from eggs were reduced because they eaten the egg shell with residual insecticides. The tested insecticides were taken very high mortalities to 1st to 3rd larva of Welsh onion beet armyworm. Otherwise, there were decreased the death rate from 4th to 6th larva. On the other hand, their value of control effects were relatively good against Welsh onion beet armyworms in the field between 87.2 and 90.5% on 10 days after insecticide application.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Distribution Science
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• v.7 no.4
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• pp.15-26
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• 2009

The internet has dramatically changed a way of business management and competition in the business environment. Especially, it stimulated not only to evolve online floral distribution service but also to change a phase of competition among floral retail stores in industry. And that also led to keen competition among IT service providers as well. This study is to examine how floral retail stores have been evolved and competed with the radical situation of the floral distribution industry through IT service in the aspect of business and information technology. In addition, the Typhoon Positioning Strategy(TPS), a strategy for the IT service positioning, is introduced from IT service provider's perspective. For IT service providers to create high business value and continuous service providing, IT service should be positioned on the customers' "core business" and developed to the level of "solution." The Typhoon Positioning Strategy(TPS) is a strategy for the IT service positioning, indicating that IT service should be positioned according to a Business Process-Service model with the consideration of business development direction, IT service trend, and user's IT capability. That is, IT service providers should find out customers' "core business" area first to provide a right IT service to the company, and the IT service provided should meet to the level of business solution. The capability of the IT solution users is also an important factor to be considered for the advanced IT service. There are four principles of the Typhoon Positioning Strategy(TPS). Principle 1) IT service provided should be an IT solution Map suitable for customer business processes. Principle 2) IT service provided should be able to support customer core business. Principle 3) IT service provided should be a business solution. Principle. 4) IT service provided should be applied differently according to the level of customer's IT capability.

• Journal of Radiation Industry
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• v.9 no.2
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• pp.85-90
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• 2015

Purpose: Time of operation has been reduced and accuracy of operation has been improved since C-arm, which offer real-time image of patient, was introduced in operation room. However, because of the contamination of patient, C-arm could not be used more appropriately. Therefore, this study is to know factors of controlling exposure dose, image quality and the exposed dose of health professional in operation room. Materials and methods: Height of Wilson frame (bed for operation) was fixed at 130 cm. Then, Model 76-2 Phantom, which was set by assembling manual of Fluke Company, was set on the bed. Head/Spine Fluoroscopy AEC mode was set for exposure condition. According to detector size of C-arm, the absorbed dose per min was measured in the 7 steps OFD (cm) from 10 cm to 40 cm (10, 15, 20, 25, 30, 35, 40 cm). In each step of OFD, the absorbed dose per min of same diameter of collimation was measured. Moreover, using Nero MAX Model 8000, exposure dose per min was measured according to 3 step of distance from detector (20 cm, 60 cm, 100 cm). Finally, resolution was measured by CDRH Disc Phantom and magnification of each OFD was measured by aluminum stick bar. Result: According to detector size of C-arm, difference of absorbed dose shows that the dose of 20 cm OFD is 1.750 times higher than the dose of 40 cm OFD. It means that the C-arm, which has smaller size of detector, shows the bigger difference of absorbed dose per min (p<0.05). In the difference of absorbed dose in the same step of OFD (from 20 cm to 40 cm), the absorbed dose of 9 inch detect or C-arm was 1.370 times higher than 12 inch' s (p<0.05). When OFD was set to 20 cm OFD, the absorbed dose of non-collimation case was approximately 0.816 times lower than the absorbed dose of collimation cases (p<0.05). When the distance was 20 cm from detector, exposed does includes first-ray and scatter-ray. When the distance was 60 cm and 100 cm from detector, exposed does includes just scatter-ray. So, there was the 2.200 times difference of absorbed does. Finally, when OFD was increased, spatial resolution was 4 to 5 step was increased. However, low contrast resolution was not relative. Moreover, there was 1.363 times difference of magnification (p<0.05). Conclusion: When C-Arm is used, avoiding contamination of patient is more important factor than reducing exposed dose of health professional in operation room. Just controlling exposure time is just way to reduce the exposed does of workers. However, in the case, non-probability influence could be occurred. Therefore, this study proved that the exposed dose will be reduced if the factors such as using small detector size of C-arm, setting OFD from 20 cm to 25 cm and non-collimating. Moreover, dose management of C-arm in the non-interesting area will be considered additionally.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.