• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.55-64
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• 2019

The flowering seasons can be advanced due to climate change that would cause an abnormally warm winter. Such warm winter would increase the frequency of crop damages resulted from sudden occurrences of low temperature before and after the vegetative growth stages, e.g., the period from germination to flowering. The degree and pattern of freezing damage would differ by the development stage of each individual fruit tree even in an orchard. A critical temperature, e.g., killing temperature, has been used to predict freeze damage by low-temperature conditions under the assumption that such damage would be associated with the development stage of a fruit flower bud. However, it would be challenging to apply the critical temperature to a region where spatial variation in temperature would be considerably high. In the present study, a phenological model was used to estimate major bud development stages, which would be useful for prediction of regional risks for the freeze damages. We also derived a linear function to calculate a probabilistic freeze risk in spring, which can quantitatively evaluate the risk level based solely on forecasted weather data. We calculated the dates of freeze damage occurrences and spatial risk distribution according to main production areas by applying the spring freeze risk function to apple, peach, and pear crops in 2018. It was predicted that the most extensive low-temperature associated freeze damage could have occurred on April 8. It was also found that the risk function was useful to identify the main production areas where the greatest damage to a given crop could occur. These results suggest that the freezing damage associated with the occurrence of low-temperature events could decrease providing early warning for growers to respond abnormal weather conditions for their farm.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.517-526
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• 2023

The harvest time of the late-ripening 'Fuji' apple (Malus × domestica) is variable, depending on the coloration of the fruit skin. Ethephon, a plant growth regulator, promotes the ethylene production and induces physiological responses associated with fruit maturation in climacteric fruit crops, such as apples. This study aimed to investigate the effect of ethephon treatment on fruit characteristics after fruit enlargement, with the objective of proposing an economical and stable harvest control method for 'Fuji'/M.26 apples. Fruit characteristics were assessed at 10-days intervals following the application of 100 mg/L ethephon and mixture of 100 mg/L ethephon and 0.5% CaCl₂ at 145 days after full bloom (DAFB). Starch contents of ethephon-treated (ET) and ethephon with CaCl₂-treated (EC) apples began to decrease from 155 DAFB, and the starch contents of ET and EC at 10 days before harvest were similar to those of control at harvest time. Red coloration of fruit skin in EC was lower compared to ET but higher than control. The average fruit firmness was low in ET, while the control and EC exhibited similar levels of firmness. Fruit sugar acid ratios did not show significant differences between treatments. However, the titratable acidity of EC was significantly lower than that of the control at 10 days before harvest. Moreover, fruit sugar acid ratio of ET and EC at 10 days before harvest in 2021 was similar to their sugar acid ratio at harvest time. Therefore, it was thought that fruit maturation and skin coloration could be accelerated by 10 days from the harvest time through the combined treatment of 100 mg/L ethephon and 0.5% CaCl₂ at the end of fruit enlargement in 'Fuji'/M.26.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of the Korean Society of Food Science and Nutrition
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• v.32 no.8
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• pp.1408-1413
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• 2003

This study was conducted to analyze manganese contents of Korean common foods. Contents of manganese in 30 foods were analyzed by ICP spectrometer. And daily manganese intake through 30 common foods was calculated using analysis data of this study and daily food intakes cited from report on 1998 national health and nutrition survey. The average manganese contents of foods analyzed were 949.6 $\mu\textrm{g}$ for rice, 236.1 $\mu\textrm{g}$ for Korean chinese cabbage kimchi, 27.2 $\mu\textrm{g}$ for citrus fruit, 2.6 $\mu\textrm{g}$ for milk, 214.6 $\mu\textrm{g}$ for radish root, 40.0 $\mu\textrm{g}$ for apple, 60.4 $\mu\textrm{g}$ for persimmon, 13.9 $\mu\textrm{g}$ for pork, 9.5 $\mu\textrm{g}$ for beef, 638.3 $\mu\textrm{g}$ for soybean curd, 184.0 $\mu\textrm{g}$ for radish kimchi, 56.0 $\mu\textrm{g}$ for pear, 18.4 $\mu\textrm{g}$ for beer, 11.3 $\mu\textrm{g}$ for egg, 9.5 $\mu\textrm{g}$ for carbonated beverage, 345.0 $\mu\textrm{g}$ for bread, 50.7 $\mu\textrm{g}$ for soju, 270.3 $\mu\textrm{g}$ for potato, 236.1 $\mu\textrm{g}$ for sweet potato, 91.2 $\mu\textrm{g}$ for ramyeon, 32.5 $\mu\textrm{g}$ for onion, 68.0 $\mu\textrm{g}$ for nabak kimchi, 538.2 $\mu\textrm{g}$ for soybean sprout, 112.5 $\mu\textrm{g}$ for welsh onion, 336.7 $\mu\textrm{g}$ for rice cake, 589.9 $\mu\textrm{g}$ for Korean chinese cabbage, 430.4 $\mu\textrm{g}$ for somyeon, 144.3 $\mu\textrm{g}$ for pumpkin, 3.0 $\mu\textrm{g}$ for yoghurt, and 614.4 $\mu\textrm{g}$ for spinach per 100 g of each food. The daily manganese intake through 30 common foods of Koreans in 1998 was 3420.7 $\mu\textrm{g}$. Major sources of dietary manganese were rice, kimchi, and soybean curd. Especially, rice supplied 68.1% of total dietary manganese intake through 30 common foods. Further studies are required to establish database and RDA of manganese.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.251-262
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• 2019

In this study, we analyzed Korean dietary habits with food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) and the Korea Centers for Disease Control and Prevention and we proposed a set of management guidelines for future Korean dietary habits. A total of 839 food items (1,419 foods) were analyzed according to the food catagories in "Food Code", which is the representative food classification system in Korea. The average total daily food intake was 1,585.77 g/day, with raw and processed foods accounting for 858.96 g/day and 726.81 g/day, respectively. Cereal grains contributed to the highest proportion of the food intake. Over 90% of subjects consumed cereal grains (99.09%) and root and tuber vegetables (95.80%) among the top 15 consumed food groups. According to the analysis by item, rice, Korean cabbage kimchi, apple, radish, egg, chili pepper, onion, wheat, soybean curds, potato, cucumber and pork were major (at least 1% of the average daily intake, 158.6 g/day) and frequently (eaten by more than 25% of subjects, 5,168 persons) consumed food items, and Korean spices were at the top of this list. In the case of kimchi, the proportion of intake of Korean cabbage kimchi (64.89 g/day) was the highest. In the case of alcoholic beverages, intake was highest by order of beer (63.53 g/day), soju (39.11 g/day) and makgeolli (19.70 g/day), and intake frequency was high in order of soju (11.3%), beer (7.2%), and sake (6.6%). Analysis results by seasonal intake trends showed that cereal grains have steadily decreased and beverages have slightly risen. In the case of alcoholic beverage consumption frequency, some kinds of makgeolli, wine, sake, and black raspberry wine have decreased gradually year by year. The consumption trend for kimchi has been gradually decreasing as well.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.