• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.67-77
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• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• Korean Journal of Veterinary Research
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• v.34 no.3
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• pp.609-617
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• 1994

This study was performed for assessing carcinogenicity of Folpet using medium-term carcinogenicity bioassay. Sprague-Dawley rats aged six weeks divided into four grout's and were initially given an intraperitoneal injection of diethylnirosamine at 200mg/kg body weight. Two weeks later, group 1(negative control) was treated with basal diet. A Folpet was given per oral administration to group 2(100 ppm) and goup 3(1,000 ppm). Group 4 was fed on water containing 0.05% phenobarbital sodium as a promtor for six weeks. At three weeks after beginning of the experiment, partial hepatectomy was performed in all rats. The tumor-promoting effects were examined by the numbers and areas per $cm^2$ of induced glutathion S-tranferase placetal form(GST-P) positive foci in liver, and silver stained nucleolar organizer regions(AgNORs) which have recently introduced as one of the indicators for the cell proliferative activity. As the results, Folpet didn't have tumor-promoting effects on GST-P positive foci developement and AgNORs during promoting stage after initiation, whereas phenobarbital sodium treatment group showed promoting effect. It was concluded that Folpet didn't have promoting effect at 500, 1,000 ppm using this midium-term carcinogenicity bioassay model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.228-241
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• 2021

This study verified the performance change of a LiDAR when it detects road signs, which are potential cooperation targets for an autonomous vehicle. In particular, road signs of different colors and materials were produced and tested in controlled rainfall on the real road environment. The NPC and intensity were selected as the performance indicators, and a T-Test was used for comparison. The study results show that the performance of LiDAR for the detection of road signs was reduced with the increase of rainfall. The degradation of performance in retroreflective sheets was lesser than painted road signs, but at the amount of 40 mm/h or more, the detection performance of retroreflective sheets deteriorates to an extent that data cannot be collected. The performance level of black paint was lower than that of other colors on a clear day. In addition, the white sheet was most sensitively degraded with the increase in precipitation. These performance verification results are expected to be utilized in the manufacturing of road facilities that improve the visibility of sensors in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.19-27
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• 2022

In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.973-980
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• 2023

This study analyzed the effects of a Micro-learning content-based extracurricular program among university students based on their general characteristics. A survey was conducted on 600 students affiliated with G University, a major national university. Learning immersion and learning motivation were used as the key indicators for measuring the learning effects. Cronbach's α coefficient analysis was performed to validate the reliability of the learning effect measurement tool. Independent sample t-tests were utilized to analyze differences in learning immersion and learning motivation based on gender and major disciplines. One-way analysis of variance (ANOVA) was employed to measure differences in learning immersion and learning motivation according to academic year. According to the research findings, gender and academic year did not significantly influence participation in the Micro-learning content-based program. However, differences in learning immersion and learning motivation were observed depending on the major discipline. Based on this, it is suggested that future programs should provide suitable environments and stimuli based on the students' major disciplines.

• Journal of Environmental Health Sciences
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• v.46 no.3
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• pp.297-311
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• 2020

Objective: We compared the level of blood cadmium exposure with health impacts by using data from a survey of residents near an abandoned mine and a national health survey. Methods: For this study, we used data from 7,046 individuals who participated in the Health Effects Survey of Abandoned Metal Mines (AMS, 2008-2011) and 6,871 individuals who participated in the Korea National Health and Nutrition Examination Survey IV-VI (KNHANES, 2008-2013). To evaluate the health impacts, the quartiles (S1 to S4) were classified according to blood cadmium concentration, and then the odds ratios of S2 to S4 over S1 for exceeding the reference values of renal function, blood pressure, and bone density were compared. Similarly, the odds ratio of AMS over KNHANES was confirmed. Results: In the AMS, adjusted for general characteristics, the geometric mean of blood cadmium concentration was 1.34 ㎍/L, which was statistically significantly higher than that of the KNHANES 1.22 ㎍/L (p<0.001). In the integrated data of AMS and KNHANES, the estimated odds ratio of S4 over S1 for exceeding the reference value was found to be 1.70 for serum creatinine, 1.71 for hypertension, and a T-score 2.02 for the tarsal bone. They were all statistically significant. Conclusion: Residents around abandoned metal mines had a higher blood cadmium concentration than the general population, and the odds for exceeding the reference values were higher for some health indicators. Continuous biomonitoring should be conducted for vulnerable areas such as around abandoned metal mines, and measures to reduce cadmium exposure and management of chronic diseases are needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.290-298
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• 2017

This study compared the median nerve, ulnar never, and F waves of patients diagnosed with early Carpal Tunnel Syndrome to a control group to determine whether F waves could be a useful indicator in the diagnosis of early CTS. The terminal motor latency (TML), terminal motor amplitude and sensory nerve conduction velocity (SNCV) of the section from the palms to the wrists, which are the key indicators to use in a nerve conduction study, and F waves were compared with the control group using the t-test. A correlation analysis was performed to analyze the correlation between the main indicators. The comparison between the median nerve's TML of the early CTS patients and that of the control group shows that there are 2 sections which have high significance (p<0.001). In the comparison of the SNCV of the median nerve between the control group and early CTS patients, high significance was observed (p<0.001). In the analysis of the F waves, there was high significance (p<0.001) between the control group and early CTS patients for the median nerve, but not for the ulnar nerve. The correlation analysis revealed that both the SNCV-TML and F wave-TML had significance. These results suggested that, along with TML and SNCV, F waves can be a useful indicator to diagnose CTS.

• The Journal of Fisheries Business Administration
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• v.49 no.1
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• pp.51-66
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• 2018

During the Joseon period, the East Sea would be called 'Gyeonghae' due to a large number of whales. In the Republic of Korea, whaling was locally permitted in 1946. However, the number drastically dropped because the hunting of the marine mammal had already been carried out in Russia, the U.S. and Japan since 1800s. Before a moratorium on commercial whaling was introduced by the International Whaling Commission(IWC) in 1986, whale populations in the East Sea had plunged. Furthermore, Korean gray whales and fin whales weren't found anymore in that area. With the suspension, whale hunting was banned in Korea as well. Even so, accidentally caught whales have been allowed to be distributed on the market with respect for local food culture. With the establishment of Whale Museum and hosting of the 57th Annual Meeting of the International Whaling Commission(IWC) at Jangsaengpo in 2005, whale tourism was facilitated in earnest. This whale tourism has been operated by Nam-gu Office and Nam-gu City Management Corporation in Ulsan. However, the popularity of whale tourism has increased a demand for whale meat. At the same time, there has been concern over decrease in whale populations because of illegal whaling. In addition, a conflict between the use and protection of whales has caused confusion in tourism identity. Actually, there is a serious doubt on the sustainability of whale tourism due to the decade-long deficit and excessive investments. This study attempts to define a concept of whale tourism and propose a future direction for the sustainable growth and development of Korea's whale tourism industry after developing such comprehensive assessment indicators as a basic research for the introduction of sustainable whale tourism. To achieve the aim of this study, AHP(Analytic Hierarchy Process) was chosen as a main research tool and the factors were ranked by a comprehensive analysis of principal factors and detail factors. The current study showed the following results. First, ecological environment(0.430) was indicated the most important factor of whale tourism assessment indicators. Moreover, Population(0.1302), Action for Cetacean protection(0.1031), Governance(0.0898) were critical factors. On the other hand, Accommodations(0.0085), Whale meat(0.0088) were unimportant factors than others.