• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Journal of the Korean Society of International Agriculture
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• v.31 no.3
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• pp.249-254
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• 2019

'Japonica 6' is a japonica rice variety developed from a cross between 'MS11', the beginning variety adaptable to tropical region, and 'IR86743-28-1-4', an elite line of high yield and good plant type by a Korea(RDA)-IRRI cooperative breeding program at IRRI in 2017. The growth duration of 'Japonica 6' is 121 days from sowing to harvest. It is 10 days later than that of the check variety 'MS11'. The culm length of 'Japonica 6' is 70 cm, and 1,000-brown rice grain weight is 26.7 g. It has a shorter culm and a larger grain. size than that of MS11. 'Japonica 6' is moderately resistant to blast disease but susceptible to bacterial blight, tungro virus and plant hoppers. The milled rice recovery rate of 'Japonica 6' is improved than that of 'MS11'. The head rice rate of 'Japonica 6' is significantly higher than that of 'MS11'. Yield of 'Japonica 6' is averagely 3.59 MT/ha of milled rice in 5 areas of the Philippines. The 'Japonica 6' was registered in Philippines and would be adaptable to the diverse regions of tropical Asia (Registration No in Philippines. BPI-NSIC-2017-Rc 484SR).

• Korean Journal of Breeding Science
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• v.51 no.4
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• pp.448-453
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• 2019

'Haedamssal' is an early maturing and rice stripe virus disease-resistant cultivar adaptable for early-transplanting cultivation that was developed by the rice breeding team of the Department of Southern Crop, NICS, RDA, in 2014. This cultivar was derived from the cross YR25869 (YR21247-B-B-B-49-1/Sasanishiki BL4//Koshihikari) and YR25868 (Unkwang//YR21247-B-B-B-49-1/Sasanishiki BL4) made in the 2005/2006 winter season and was advanced to the F₅ generation by a bulk breeding method using rapid generation advance. To incorporate rice stripe virus resistance, marker-assisted selection on the RSV gene was conducted in 3-way and 6-way cross F₁ generation using the tightly linked marker RM6897. From testing in the replicated yield trial in 2011, a promising line YR26258-B-B-B-33-3 was selected and it was designated as 'Milyang276'. A local adaptability test of 'Milyang276' was performed at three locations from 2012 to 2014 and it was named as 'Haedamssal', which was a good eating quality variety. The culm length was 67 cm in yield trials, which was 4 cm shorter than 'Jopyeong'. The number of spikelets per panicle was lower than 'Jopyeong', whereas the number of tillers per hill was higher. This variety was resistant to RSV disease, bacterial blight, and leaf blast disease. The milled rice yield of 'Haedamssal' was 5.48 MT per ha at the early transplanting in the local adaptability test. 'Haedamssal' is well adapted to early transplanting cultivation in the southern plain area (Registration No. 6811).

• Journal of the East Asian Society of Dietary Life
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• v.21 no.6
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• pp.934-947
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• 2011

The purpose of this study is to analyze products for good taste and convenience, which become an engine to constantly create customers. In addition, this study is aimed at investigating the relationship between the selective attributes of Home Meal Replacement, the perceived utilitarian value, and the repurchase intention, and drawing new suggestions on the Home Meal Replacement market from a new marketing perspective. Based on a total of 215 samples, this study reviewed the reliability and fitness of the research model and verified a total of 5 hypothesized using the Amos program. The result of study modeling was GFI=0.905, AGFI=0.849, NFI=0.889, CFI=0.945, and RMR=0.0.092 at the level of $x^2$=230.22 (df=126, p<0.001). First, the food quality (${\beta}$=0.221), convenience (${\beta}$=0.334), packing (${\beta}$=0.278), and employee service (${\beta}$=0.204) of home meal replacement consideration attributes had a positive (+) influence on perceived utilitarian value. Second, perceived utilitarian value (${\beta}$=0.584) had a positive (+) influence on repurchase intention. The factors to differentiate one company from other competitors in terms of the utilitarian value are the quality of food, convenience, wrapping, and services by employees. This study has illustrated the need to focus on the development of a premium menu to compete with other companies and to continue to research and develop nutritious foods that are easy to cook. Moreover, the key factors to have a distinct and constant competitive edge over other companies are the alleviation of consumer anxiety over wrapping container materials, the development of more designs, and the accumulation of service know-how. Therefore, it is necessary for a company to strongly develop the key factors based on its resources as a core capability.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.3
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• pp.103-134
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• 1977

The physiological and biochemical role of potassium for upland crops according to recent research reports and the nutritional status of potassium in Korea were reviewed. Since physical and chemical characteristics of potassium ion are different from those of sodium, potassium can not completely be replaced by sodium and replacement must be limited to minimum possible functional area. Specific roles of potassium seem to keep fine structure of biological membranes such as thylacoid membrane of chloroplast in the most efficient form and to be allosteric effector and conformation controller of various enzymes principally in carbohydrate and protein metabolism. Potassium is essential to improve the efficiency of phoro- and oxidative- phosphorylation and involve deeply in all energy required metabolisms especially synthesis of organic matter and their translocation. Potassium has many important, physiological functions such as maintenance of osmotic pressure and optimum hydration of cell colloids, consequently uptake and translocation of water resulting in higher water use efficiency and of better subcellular environment for various physiological and biochemical activities. Potassium affects uptake and translocation of mineral nutrients and quality of products. potassium itself in products may become a quality criteria due to potassium essentiality for human beings. Potassium uptake is greatly decreased by low temperature and controlled by unknown feed back mechanism of potassium in plants. Thus the luxury absorption should be reconsidered. Total potassium content of upland soil in Korea is about 3% but the exchangeable one is about 0.3 me/100g soil. All upland crops require much potassium probably due to freezing and cold weather and also due to wet damage and drought caused by uneven rainfall pattern. In barley, potassium should be high at just before freezing and just after thawing and move into grain from heading for higher yield. Use efficiency of potassium was 27% for barley and 58% in old uplands, 46% in newly opened hilly lands for soybean. Soybean plant showed potassium deficiency symptom in various fields especially in newly opened hilly lands. Potassium criteria for normal growth appear 2% $K_2O$ and 1.0 K/(Ca+Mg) (content ratio) at flower bud initiation stage for soybean. Potassium requirement in plant was high in carrot, egg plant, chinese cabbage, red pepper, raddish and tomato. Potassium content in leaves was significantly correlated with yield in chinese cabbage. Sweet potato. greatly absorbed potassium subsequently affected potassium nutrition of the following crop. In the case of potassium deficiency, root showed the greatest difference in potassium content from that of normal indicating that deficiency damages root first. Potatoes and corn showed much higher potassium content in comparison with calcium and magnesium. Forage crops from ranges showed relatively high potassium content which was significantly and positively correlated with nitrogen, phosphorus and calcium content. Percentage of orchards (apple, pear, peach, grape, and orange) insufficient in potassium ranged from 16 to 25. The leaves and soils from the good apple and pear orchards showed higher potassium content than those from the poor ones. Critical ratio of $K_2O/(CaO+MgO)$ in mulberry leaves to escape from winter death of branch tip was 0.95. In the multiple croping system, exchangeable potassium in soils after one crop was affected by the previous crops and potassium uptake seemed to be related with soil organic matter providing soil moisture and aeration. Thus, the long term and quantitative investigation of various forms of potassium including total one are needed in relation to soil, weather and croping system. Potassium uptake and efficiency may be increased by topdressing, deep placement, slow-releasing or granular fertilizer application with the consideration of rainfall pattern. In all researches for nutritional explanation including potassium of crop yield reasonable and practicable nutritional indices will most easily be obtained through multifactor analysis.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.1-10
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• 2009

The purpose of this study was to categorize the gap between coffee shop 'importance' (as perceived by customers before patronizing the coffee shop) and 'satisfaction' (perception of customers after patronizing the coffee shop) as positive or negative and to analyze the effect of these gaps on purchasing behavior. To do this, I used the gap between importance and satisfaction regarding the choice of a coffee shop as the explanatory variable and performed an empirical analysis of the direction and size of the effect of the gap on purchasing behavior (overall satisfaction, willingness-to-revisit) by applying the Ordered Probit Model (OPM). A previous study that used IPA to evaluate the effects of gaps estimated the direction and size of a quadrant but failed to analyze the effect of gaps on customers. In this study, I evaluated the effects of positive and negative gaps on customer satisfaction and willingness-to-revisit. Using OPM, I quantified the effect of positive and negative gaps on overall customer satisfaction and willingness-to-revisit. Per-head expenditure, frequency of visits, and coffee-purchasing place had the most positive effects on overall customer satisfaction. Frequency of visits, followed by per-head expenditure and then coffee-purchasing place, had the most positive impact on willingness-to-visit. Thus per-head expenditure and frequency of visits had the greatest positive effects on overall satisfaction and willingness-to-revisit. This finding implies that the higher the actual satisfaction (gap) of customers who spend KRW5,000 or more once or more per week at coffee shops is, the higher their overall satisfaction and willingness-to-revisit are. Despite the fact that economical efficiency had a significant effect on overall satisfaction and willingness-to-revisit, college and university students still use coffee shops and are willing to spend KRW5,000 because they do not only purchase coffee as a product itself, but use the coffee shop for other activities, such as working, meeting friends, or relaxing. College and university students also access the Internet in coffee shops via personal laptops, watch movies, and study; thus, coffee shops should provide their customers with the appropriate facilities and services. The fact that a positive gap for coffee shop brand had a positive effect on willingness-to-revisit implies that the higher the level of customer satisfaction, the greater the willingness-to-revisit. A negative gap for this factor, on the other hand, implies that the lower the level of customer satisfaction, the lower the willingness-to-revisit. Thus, the brand factor has a comparatively greater effect on satisfaction than the other factors evaluated in this study. Given that the domestic coffee culture is becoming more upscale and college/university students are sensitive to this trend, students are attentive to brands. In most upscale coffee shops in Korea, the outer wall is built out of glass that can be opened, the interiors are exotic with an open kitchen. These upscale coffee shops function as landmarks and match the taste of college/university students. Coffee shops in Korea have become a cultural brand. To make customers feel that coffee shops are upscale, good quality establishments and measures to provide better services in terms of brand factor should be instituted. The intensified competition among coffee shop brands in Korea as a result of the booming industry indicates that provision of additional services is needed to differentiate competitors. These customers can also use a scanner free of charge. Another strategy that can be used to boost brands could be to provide and operate a seminar room for seminars and group study. If coffee shops adopt these types of strategies, college/university students would be more likely to consider the expenses they incur worthwhile and, subsequently, they would be more likely to be satisfied with the brands of these coffee shops, with an associated increase in their willingness-to-revisit. Gender and study year had the most negative effects on overall satisfaction and willingness-to-revisit. Female students were more likely to be satisfied and be willing to return than male students, and third and fourth-year students were more likely to be satisfied and willing-to-return than first or second-year students. Students who drink coffee, read books, and use laptops alone at coffee shops are easily noticeable. High-grade students tend to visit coffee shops alone in order to use their time efficiently for self-development and to find jobs. The economical efficiency factor had the greatest effect on overall satisfaction and willingness-to-revisit in terms of a positive gap. The higher the actual satisfaction (gap) of students with the price of the coffee, the greater their overall satisfaction and willingness-to-revisit. Economical efficiency with a negative gap had a negative effect on willingness-to-revisit, which implies that a less negative gap will result in a greater willingness-to-revisit. Amid worsening market conditions, coffee shops located around colleges/universities are using strategies, such as a point or membership card, strategic alliances with credit-card companies, development of a set menu or seasonal menu, and free coffee-shot services to increase their competitive edge. Product power also had a negative effect in terms of a negative gap, which indicates that a higher negative gap will result in a lower willingness-to-revisit. Because there are many more customers that enjoy coffee in this decade, as compared to previous decades, the new generation of customers, namely college/university students, want various menu items in addition to coffee, and coffee shops should, therefore, add side menu items, such as waffles, rice cakes, cakes, sandwiches, and salads. For example, Starbucks Korea is making efforts to enhance product power by selling rice cakes flavored in strawberry, wormwood, and pumpkin, and providing coffee or cream free of charge. In summary, coffee shops should focus on increasing their economical efficiency, brand, and product power to enhance the satisfaction of college/university students. Because shops adjacent to colleges or universities enjoy a locational advantage, providing differentiated services in terms of economical efficiency, brand, and product power, is likely to increase customer satisfaction and return visits. Coffee shop brands should, therefore, be innovative and embrace change to meet their customers' desires. Because this study only targeted college/university students in Seoul, comparative studies targeting diverse regions and age groups are required to generalize the findings and recommendations of this study.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Journal of Embryo Transfer
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• v.26 no.1
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• pp.19-25
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• 2011

This study was carried out to evaluate the effect of early pregnant cow as donor for Ovum Pick-Up (OPU) derived oocyte aspiration and embryo production in Holstein heifers. Four non-pregnant and 2 pregnant Holstein heifers were used as donor and then carried out total 17 OPU session for 10 weeks (2 times per week). Recovered cumulus-oocyte-complexes (COCs) were classified into 4 grade by oocyte cytoplasm and cumulus cells and matured in vitro in TCM-199 supplemented with 10% FBS, 10 mg/ml FSH and 1 mg/ml estradiol in 5% $CO_2$ and over 99% humidity for 24 h. After 24 h co-incubation with post-thaw sperm, the presumed zygotes were cultured in CR1aa medium with 4 mg/ml BSA for 3 days and then changed CR1aa medium with 10% of FBS for another 3~4 days. The Mean number of aspirated follicles and collected oocytes in the early stage pregnant and non-pregnant heifers were $13.0{\pm}4.3$ and $10.6{\pm}3.9$, $5.4{\pm}3.4$ and $7.7{\pm}3.6$ per session, respectively. Rate of collected oocyte from aspirated follicles were 59.2% and 50.5%, respectively. The average number of good quality oocytes (Grade I and II) in the early stage pregnant and non-pregnant heifers was $3.7{\pm}2.7$ and $4.9{\pm}2.6$ (Mean${\pm}$SD). Cleavage and blastocyst developmental rates in Grade I and II were 22.2% and 25.5%, and then $1.7{\pm}0.9$ and $1.4{\pm}1.1$ blastocyst per session, respectively. In conclusion, OPU technology can be used in early stage pregnant and non-pregnant heifers without any problem and so applied OPU derived embryo production to maximize the ability of genetically valuable females.

• Korean Journal of Food Science and Technology
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• v.9 no.2
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• pp.131-137
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• 1977

This study was conducted to examine the changes of pH, proteolytic enzymic activity, and every kind of nitrogen compounds during their fermentation of the three groups of meju for 90days. Among the three groups, the first group was conventional Korean meju which was proved to be good quality (sample J), the second group was prepared with soybean paste using B. subtilis (sample K), and the third group was an improved meju which was fermented with the soybean and wheat (7 : 3) mixtured paste with Asp. sojae (sample L). These groups were analyzed at an interval of 10 day and the results are summarized as follows: 1) The pH of the all three groups was lowered from $6.45{\sim}6.75\;to\;4.85{\sim}5.20$ in just the 30 days and maintained the weak acidity during this fermentation. 2) The proteolytic enzymic activity was increased as soon as the three groups of meju were fermented and marked the maximum value in 30 days. The maximum value of the three groups of meju J.K. and L was 147, 112, and 52 respectively. The proteolytic enzymic activity of sample J and K was decreased to 23.5 and 20.5 in 20 days, while that of sample L was decreased to 18.0 in 40 days, and maintained the volues to the end of fermentation for 90 days. The conventional meju J and the improved meju K showed sparkling activity at the pH 7, while the activity of improved meju L was strong at the pH 10. 3) The PAA-N content of sample J and K was increased and reached to the peak point with 1.55% and 1.49% respectively in 60 days. But the sample L marked the maximum value with 1.28% after 80 days. 4) The amino-N content of sample J was increased and reached to 0.36% after 60 days, and that of sample K and L was increased and reached to 0.29% and 0.21% respectively after 40 days. After reaching to the peak point, the contents were decreased. 5) The content of ammonia-N was most abundant in sample K which was fermented with soybean paste using B. subtilis. 6) The peptide-N content of sample K and L was increased after decreasing in the middle of fermentation period, while that of sample J was increased gradually during fermentation. 7) The changes of nitrogen compounds were seemed to complete in 60 days of fermentation.