• Journal of the Korean Dietetic Association
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• v.18 no.4
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• pp.372-384
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• 2012

The purpose of this study was to provide a basic resource for establishment of hygienic management standards for meal delivery from the central kitchen to schools. Flow diagrams for delivery of food were analyzed, and time-temperature conditions of the food and environment were measured. Four different foods samples including Mexican salad, radish salad, stir-fried pork and vegetables, and stir-fried chicken and vegetables were collected after production and before service. Microbiological analysis was performed for aerobic plate counts (APC), Enterobacteriaceae, coliforms, E. coli, Salmonella spp., S. aureus, B. cereus, C. perfringens, and L. monocytogenes. After completion of production of cooked foods 2~3 hours were taken for the cooked foods to reach the temperature danger zone. Food temperatures at the meal service did not meet the recommended temperatures ($10/57^{\circ}C$) for conventional school food service systems. The highest APC counts were observed in radish salad (5.70 log CFU/g), followed by Mexican salad (5.18 log CFU/g). Enterobacteriaceae and coliform counts were within acceptable levels of those recommended by the UK Public Health Laboratory Service. No E. coli or pathogens were found. These results provide useful information for determination of microbiological hazards in school food service systems, and suggest that time-temperature control during delivery is necessary for the safety of cooked foods.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.447-451
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• 2010

It is quite important for manufacturing firms to stably secure water, because industrial water is used for a variety of purposes as one of the important inputs in the production process. Despite the significance of industrial water use and the increase of industrial water demand, relatively little has studied regarding the industrial water use in Korea. This paper employs the marginal productivity approach in order to estimate the economic value of water in Korean manufacturing industry, and we use the information of 53,912 factories surveyed in 2003. The result of the likelihood ratio test shows that Trans-log is an appropriate model for estimating the data of this study. In Trans-log function model, the industry-wide output elasticity of water is 0.0104, and the marginal value is KRW 1,156 per ton. The estimated values differ across the sectors and these values range from the high value of about KRW 13,760 per ton in the transportation equipment sector to low values of KRW 428 per ton in the precision instrument sector. The research provides useful information to help policy-makers in developing and implementing more appropriate policies regarding the management and distribution of water resources by estimating the value of water resources by sector. In addition, Korean government enables the drafting of future water pricing scenarios based on the estimated value information.

• Preventive Nutrition and Food Science
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• v.15 no.3
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• pp.239-243
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• 2010

The antimicrobial effects of a commercially available, buffered sodium citrate (BSC) were evaluated for the reduction of total aerobic bacteria count, Salmonella Typhimurium, Escherichia coli O157:H7, Listeria monocytogenes and Staphylococcus aureus in a liquid medium and ground beef. BSC at 0, 1, 2 and 4.8% (wt/vol) or 0, 3, and 4.8% (wt/wt) was mixed into inoculated brain heart infusion (BHI) broth and ground beef (80% lean), respectively. BSC at concentrations of 1 and 2% did not inhibit growth of the pathogens tested in BHI broth. E. coli O157:H7 in BHI broth with 4.8% BSC was significantly reduced (p<0.05) by 3～4 log CFU/mL compared with the control for up to 4 days. At 4.8%, BSC treatment of ground beef most significantly reduced (p<0.05) total aerobic count and E. coli O157:H7 by 2.1 and 2.0 log CFU/g, respectively. This study indicates that the legally allowable level of 1.3% (wt/wt) BSC is not effective for reducing the pathogens tested in ground beef stored at $7^{\circ}C$.

• Journal of Animal Science and Technology
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• v.59 no.2
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• pp.3.1-3.7
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• 2017

Background: The modelling of lactation curve provides guidelines in formulating farm managerial practices in dairy cows. The aim of the present study was to determine the suitable non-linear model which most accurately fitted to lactation curves of five lactations in 134 Gir crossbred cows reared in Research-CumDevelopment Project (RCDP) on Cattle farm, MPKV (Maharashtra). Four models viz. gamma-type function, quadratic model, mixed log function and Wilmink model were fitted to each lactation separately and then compared on the basis of goodness of fit measures viz. adjusted $R^2$, root mean square error (RMSE), Akaike's Informaion Criteria (AIC) and Bayesian Information Criteria (BIC). Results: In general, highest milk yield was observed in fourth lactation whereas it was lowest in first lactation. Among the models investigated, mixed log function and gamma-type function provided best fit of the lactation curve of first and remaining lactations, respectively. Quadratic model gave least fit to lactation curve in almost all lactations. Peak yield was observed as highest and lowest in fourth and first lactation, respectively. Further, first lactation showed highest persistency but relatively higher time to achieve peak yield than other lactations. Conclusion: Lactation curve modelling using gamma-type function may be helpful to setting the management strategies at farm level, however, modelling must be optimized regularly before implementing them to enhance productivity in Gir crossbred cows.

• Journal of the FoodService Safety
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• v.2 no.2
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• pp.84-90
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• 2021

This study was performed to assess the microbiological quality and safety of microgreen sampled from harvesting farms and food processing plant in Korea. The samples were analyzed for total viable counts, coliforms, Enterobacteriaceae, Escherichia coli, Salmonella spp., Listeria monocytogenes, Vibrio parahaemolyticus, Bacillus cereus, and Staphylococcus aureus. Total viable counts were highly contaminated in samples collected from farms (7.7~8.2 log CFU/g) and the final products (5.8~7.8 log CFU/g), respectively. B. cereus was detected less than 100 CFU/g, which was satisfied with Korean standards (<1,000 CFU/g) of fresh-cut produce. A predictive model was developed for the changes of total viable counts in microgreens during storage at 5~35℃. The predictive models were developed using the Baranyi model for the primary model and the square root model for the secondary model. The results obtained in this study can be useful to develop the safety management options along the food chain, including fresh-cut produce storage and distribution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1545-1559
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• 2023

In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.476-487
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• 2007

Flash memory offers attractive features, such as non-volatile, shock resistance, fast access, and low power consumption for data storage. However, it has one main drawback of requiring an erase before updating the contents. Furthermore, flash memory can only be erased limited number of times. To overcome limitations, flash memory needs a software layer called flash translation layer (FTL). The basic function of FTL is to translate the logical address from the file system like file allocation table (FAT) to the physical address in flash memory. In this paper, a new FTL algorithm called an efficient and advanced space-management technique (EAST) is proposed. EAST improves the performance by optimizing the number of log blocks, by applying the state transition, and by using reallocation blocks. The results of experiments show that EAST outperforms FAST, which is an enhanced log block scheme, particularly when the usage of flash memory is not full.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.61-79
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• 2006

To come up with the recommendations to improve the patent & trademark retrieval efficiency, 100,016 patent & trademark search requests by 17,559 unique users over a period of 193 days were analyzed. By analyzing 2,202 multi-query sessions, where one user issuing two or more queries consecutively, we discovered a number of retrieval efficiency improvements clues. The session analysis result also led to suggestions for new system features to help users reformulating queries. The patent & trademark retrieval users were found to be similar to the typical web users in certain aspects especially in issuing short queries. However, we also found that the patent & trademark retrieval users used Boolean operators more than the typical web search users. By analyzing the multi-query sessions, we found that the users had five intentions in reformulating queries such as paraphrasing, specialization, generalization, alternation, and interruption, which were also used by the web search engine users.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.33-49
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• 2014

This study empirically examines the impact of firms' environmental (E), social (S), and governancial (G) factors on their short-term and long-term values. To measure firms' non-financial performance, we use ESG performance grades published by KCGS (Korea Corporate Governance Service). We employ stock log return as the proxy of each firm's short-term value, and Tobin's Q ratio as that of its long-term value. From a series of regression analyses, we find each of the ESG factors generally has a negative impact on stock return while it has a positive impact on the Tobin's Q ratio. These results imply that firms' effort for enhancing their non-financial performance may adversely affect their financial performance in a short term; but in the long-term point of view, firms' values increase through their good images engraved by their respective social, environmental and governancial efforts. In addition, we compare the relative strength of impact among E, S, G, the three non-financial factors on the firms' value measured in Tobin's Q ratio, and find that S (social factor) and G (governancial factor) give statistically significant impact on the firms' value respectively. This result tells us it would be advised to strategically embed CSV (creating shared value) pursuing both of profits and social responsibility in the firms' future agenda. While E (environmental factor) is shown to be an insignificant factor for the firms' value, it should be emphasized as a major concern by all the stakeholders in order to form a sound business ecosystem.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.157-165
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• 2004

The paper suggests that web-server security management system will be able to detect the web service attack accurately and swiftly which is keeping on increasing at the moment and reduce the possibility of the false positive detection. This system gathers the results of many unit security modules at the real time and enhances the correctness of the detection through the correlation analysis procedure. The unit security module consists of Network based Intrusion Detection System module. File Integrity Check module. System Log Analysis module, and Web Log Analysis and there is the Correlation Analysis module that analyzes the correlations on the spot as a result of each unit security module processing. The suggested system provides the feasible framework of the range extension of correlation analysis and the addition of unit security module, as well as the correctness of the attack detection. In addition, the attack detection system module among the suggested systems has the faster detection time by means of restructuring Snort with multi thread base system. WSM will be improved through shortening the processing time of many unit security modules with heavy traffic.