• Nutrition Research and Practice
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• v.9 no.5
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• pp.517-522
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• 2015

BACKGROUND/OBJECTIVES: The objective of this study was to investigate food allergens and prevalence rates of food allergies, followed by comparison of consumer attitudes and preferences regarding food allergy labeling by diagnosis of food allergies. SUBJECTS/METHODS: A total of 543 individuals living in Seoul and Gyeonggi area participated in the survey from October 15 to 22 in 2013. RESULTS: The results show that the prevalence of doctor-diagnosed food allergies was 17.5%, whereas 6.4% of respondents self-reported food allergies. The most common allergens of doctor-diagnosed and self-reported food allergy respondents were peaches (30.3%) and eggs (33.3%), respectively, followed by peanuts, cow's milk, and crab. Regarding consumer attitudes toward food labeling, checking food allergens as an item was only significantly different between allergic and non-allergic respondents among all five items (P < 0.001). All respondents reported that all six items (bold font, font color, box frame, warning statement, front label, and addition of potential allergens) were necessary for an improved food allergen labeling system. PLSR analysis determined that the doctor-diagnosed group and checking of food allergens were positively correlated, whereas the non-allergy group was more concerned with checking product brands. CONCLUSIONS: An effective food labeling system is very important for health protection of allergic consumers. Additionally, government agencies must develop policies regarding prevalence of food allergies in Korea. Based on this information, the food industry and government agencies should provide clear and accurate food labeling practices for consumers.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

• Journal of Animal Science and Technology
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• v.50 no.1
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• pp.1-8
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• 2008

This study was conducted to develop a traceability system for systematic animal identifi- cation to increase efficiency of animal production, post production and processing to ensure that quality and sanitary meat products reach the consumers of the entire country. The new animal identification traceability system was designed for easy management, data collection and storage considering bar code, registration number and farm number.Specifically the system aimed 1) To provide standard radio frequency technology identification (RF-ID) for livestock management, standard of ear tag, microchip and ear tag identification equipment, 2) To guarantee meat product label thereby safeguarding the consumers 3) To give incentives to farmers for producing quality meat products and 4) To provide unified system for national livestock management.Results of the research which started in July 2003 which was used by several farmers’ cooperatives and Department Store revealed the feasibility of using the RF-ID system although much will be done to conform to global nomenclatures.

• Journal of Fashion Business
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• v.1 no.2
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• pp.46-54
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• 1997

The purpose of this study is to understand women's wear manufacturing industries. First, the study was to investigate the present production systems and how much the automatic facility are by comparing them. This study enhanced more efficient, stable, and suitable work line. This intern will direct the way in which automatic facilities will be created. Second, through this study on the general character of the inspectors, the ratio of impaired goods, and the reasons for unsatisfactory goods, I intended to find out a way to decrease the impaired goods and to produce competitive and high quality goods. The results of the survey can be summarized as follows; 1. The result of the research on the automatic industrial facilities shows that the majority of the factories (77.4%) are 40% below the automatic facility rate. The reasons for this according to order are that was a deficit in money, no reason for expensive machines, and lack of the technique and the number of workers required to handle the machines. 2. At this time, the most required equipments are shown according to its importance; automatic sewing machine, automatic cutting machine, automatic spreading machine, and finishing & pressing machine. So in the women's wear manufacturing industries, they think that they need more automatic cutting machine, automatic spreading machine in the cutting field rather than high price automatic machine in the sewing field such as pattern former, pocket welting, automatic sleeve connecting machine and automatic label connecting machine. 3. The result of the research in the goods quality shows that the average impaired rate is 12.7% at the first inspection. In addition the average rate for complete impaired rate is 1.52%. The line system shows that it has a impaired rate that is double the rate of the pair system. Because of this, the industries plan to combine the line system and pair system to create an improved and suitable production system which can boost the quality and productivity of the goods. 4. The fabric is the main point of the impaired goods. The factors of the impaired goods in manufacturing are the lack of mental abilities of the worker, impaired fabrics and a lack of cooperation in the working system. Furthermore, there is a lack of technique for new material. 5. To prohibit impaired goods in manufacturing, there need to be a way to educate the workers and to enhance the workers' mind on the productive goods. Also there need to increase in the investments of automatic production machines. Finally there need to be a standardized working line. Therefore, there need to be an improvement on the management of the production of goods, the development of technique and an increase in the education for the workers, with this there will be a decrease in impaired goods, and an increase in better quality of goods to enforce the domestic apparel industries.

• Journal of Animal Science and Technology
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• v.45 no.2
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• pp.273-282
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• 2003

Consumer survey(n=1,343) was carried out to investigate the consumer's perception, purchase behavior and demand on the processed meat products. Most consumers purchased the ham and sausage products once a month (40.73%). Consumers(47.19%) didn’t distinguish between ham and sausage products due to the similarity of meat contents and additives in products. Consumers(72.75%) considered the product label when they purchased whereas 27.25% of consumers were not interested in the product label. Consumers(47.65%) were not satisfied with ham and sausage products because there were too much additives other than meat, there were many similar processed products in kinds and appearance(27.70%) and they could hardly detect meat taste(11.62%). Consumers demanded to produce the ham and sausage products which contain high meat contents(64.04%). Consumers were favored with establishment of the price differential system depending on the quality based on meat contents in the product(83.54%). In conclusion, the establishment of the price differential system depending on quality as well as the quality grading system for processed meat products is needed not only to increase the processed meat market but also increase the pork consumption especially for non-preferred pork portions.

• Journal of Korean Academy of Nursing Administration
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• v.5 no.2
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• pp.209-224
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• 1999

I have practiced this reserch for the purpose of proposition of basic data for amendment and addition of computer system after I surveyed the degree of abilities and satisfaction on the computerization in nursing\ practice. Subjects were collected from September 1 to September 30, 1998. Study subjects are 151 clinical nurses who are working at university hospital in Chonbuk area. Study instrument consists of 116 questionnaire which was developed by Kim H. K(1998). The data were analized number, mean ,t-test, ANOVA by using SPSS. The study results are as follows: 1. Most of the nurses who answered the questions were educated computerizing(96%). The abilities of computer program utilities were the most in inputting data(74%). The program nurses wanted computerizing education was wordprocess, dealing internet and statistics. 2. As for applying parts of computer system in nursing, the most nurses were Dr's order check (96%), treatment activity(91.4%), medication(89.4%), lab. test(87 .4%), transfering department(85.4%), transfering room(79.5%), diet(71.8%), discharge (70.2%), Barcord Sticker(70.2%) , reservation(62.2%) in order that were all conected order system mutually to other part. It showed that computer system was not applied for treating the original nursing work such as nursing record (13%), duty scheduling(6.0%) , nursing process(4.6%) , Q.I(1.3%), nursing research(1.3%), education(1.3%), 3. As for the benefit when computer system is applied for, the most respondence was promptness of work and convenience(90.6%) , exactness of work (82.8%), offering information exactily and efficiently(36.3%), offering good quality of nursing (6.0%) in order. 4. The degree of contentment on computerizing in nursing practice showed average 3.24%. The best marking item is that they are eager to participate in the computer education. Next, the automatic output of label and giving the number automatically is to prevent loss and mentioned items of patient registration from being changed(3.95) and to prevent mistakes possibly happening because of doctor's difficult order(3.85). 5. The problems which may happen to in nurses' utilization of computerization for the nursing practice showed average 3.18. The most problem is that the practice may stop because of the problem of computer itself(3.67), and the next, the indication of act can be imperfect(3.66) , manual training may overlap because of incomplete computerization (3.60), practical education for the computerizing is lack(3.41), and the computer literate nurses are lack(3.40) . 6. Study subject's contentment by age was significant difference(F=3.10,P=0.0119). Study subject's contentment by job posision was significant difference(F=6.001P=0.0034) I will propose the following according to the above results. The domain of original nursing practice is urgernt. Manual and indication of act should be made before long in computer obstacle. Nursing department should support the nurses so that they could receive the education needed for the nurses themselves.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.4
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• pp.347-362
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• 2009

The United Nation agreed to adopt the Globally Harmonized System of Classification and Labelling of Chemicals (GHS) until 2008 to solve the significant differences enough to result in different labels or MSDS for the same chemical in different jurisdictions. Though the GHS is an ideal solution in the respect of pursuing only one format of a MSDS throughout the world, it may cause confusion at the beginning due to lack of information. So the Korean Ministry of Labor (MOL) revised the Industrial Safety and Health Act (ISHA) and related public notice on the classification & labelling of chemicals according to the GHS in 2006. The transition period for the implementation of the GHS for substances was set until Jun 30, 2010, and for mixtures until Jun 30, 2013. To promote the implementation of the GHS in Korea, we developed an application program for constructing MSDS database and a management program for providing MSDS contents on the web in accordance with the GHS. We analyzed the sixteen sections of MSDS by the GHS guideline, and the result showed the necessity to construct logically connected DB for chemical identifier, hazard classification, label, standard phrases and regulatory information. Each section of a MSDS was divided into sub-databases to update the database efficiently. According to Relational Database Management System (RDBMS), the sub-databases were automatically assembled and subsequently a full MSDS is produced. At present, MSDS database for 6,314 substances has been built and provided through internet as the MSDS Editing program. During the service period from January 1 to March 31, 13,666 users have searched MSDSs for 33,401 substances. During program review, some comments about the classification results and other MSDS element sources were reported but no technical bug reported. We expect that the MSDS DB management system in accordance with GHS will accelerate the implementation of the GHS in Korea.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.185-197
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• 2022

Recently, deep learning networks with high performance for object recognition are emerging. In the case of object recognition using deep learning, it is important to build a training data set to improve performance. To build a data set, we need to collect and label the images. This process requires a lot of time and manpower. For this reason, open data sets are used. However, there are objects that do not have large open data sets. One of them is data required for license plate detection and recognition. Therefore, in this paper, we propose an artificial license plate generator system that can create large data sets by minimizing images. In addition, the detection rate according to the artificial license plate arrangement structure was analyzed. As a result of the analysis, the best layout structure was FVC_III and B, and the most suitable network was D2Det. Although the artificial data set performance was 2-3% lower than that of the actual data set, the time to build the artificial data was about 11 times faster than the time to build the actual data set, proving that it is a time-efficient data set building system.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.464-475
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• 2023

In this study, based on an analysis of two DNA barcode markers (cytochrome c oxidase subunit I and cytochrome b genes), we performed species identification and monitored labeling compliance for 50 commercial pufferfish products sold in on-line markets in Korea. Using these barcode sequences as a query for species identification and phylogenetic analysis, we screened the GenBank database. A total of seven pufferfish species (Takifugu chinensis, T. pseudommus, T. xanthopterus, T. alboplumbeus, T. porphyreus, T. vermicularis, and Lagocephalus cheesemanii) were identified and we detected 35 products (70%) that were non-compliant with the corresponding label information. Moreover, the labels on 12 commercial products contained only the general common name (i.e., pufferfish), although not the scientific or Korean names for the 21 edible pufferfish species. Furthermore, the proportion of mislabeled highly processed products (n = 9, 81.8%) was higher than that of simply processed products (n = 26, 66.7%). With respect to the country of origin, the percentage of mislabeled Chinese products (n = 8, 80%) was higher than that of Korean products (n = 26, 66.7%). In addition, the market and dialect names of different pufferfish species were labeled only as Jolbok or Milbok, whereas two non-edible pufferfish species (T. vermicularis and T. pseudommus) were used in six commercial pufferfish products described as JolboK and Gumbok on their labels, which could be attributable to the complex classification system used for pufferfish. These monitoring results highlight the necessity to develop genetic methods that can be used to identify the 21 edible pufferfish species, as well as the need for regulatory monitoring of commercial pufferfish products.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.