• Horticultural Science & Technology
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• v.32 no.5
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• pp.577-583
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• 2014

Benzyladenine (BA, 99% purity), MaxCel$^{(R)}$ (1.9% BA), Fruitone (3.5% NAA), MaxCel$^{(R)}$ + Fruitone, a nd s imazine were applied postbloom as fruitlet thinning agents to mature 'Hongro' and 'Fuji' apple (Malus domestica Borkh.) trees. BA and MaxCel$^{(R)}$ were applied at $100mg{\cdot}L^{-1}$ a.i. while Fruitone at $0.1mg{\cdot}L^{-1}$ a.i. and simazine at $400mg{\cdot}L^{-1}$ a.i. All PGRs were applied at 8 days after full bloom (DAFB, 6 mm fruit diameter) in both cultivars, while simazine was treated twice at 7 and 14 DAFB. In 'Hongro', the number of total fruit set per flower cluster in terminal buds was 1.67, 1.84, and 1.81 in MaxCel$^{(R)}$ + F ruitone, MaxCel$^{(R)}$, and simazine applications, respectively, when compared with 2.35 of water control. These reductions in fruit set were mainly attributed to the increased ratio of defruited clusters by the thinning agents. In 'Fuji' apple, the number of total fruit set per flower cluster in terminal buds was 1.29, 1.60, and 1.76 in MaxCel$^{(R)}$ + Fruitone, Fruitone, and MaxCel$^{(R)}$, respectively, when compared with 2.56 of water control in 'Fuji' apple. The addition of Fruitone to the MaxCel$^{(R)}$ promoted the thinning efficacy in both cultivars, compared to MaxCel$^{(R)}$ only. The thinning efficacies were similarly observed with lateral flowers in both cultivars. A significant increase of fruit weight by the postbloom thinning treatments was observed only in the BA application in 'Hongro', while the effect was observed in BA and MaxCel$^{(R)}$ in 'Fuji'. While the soluble solids content increased in the BA, MaxCel$^{(R)}$ and MaxCel$^{(R)}$+Fruitone treatments in both cultivars, other fruit quality attributes were not affected by the application of post-bloom thinning agents.

• Journal of Gifted/Talented Education
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• v.22 no.3
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• pp.619-637
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• 2012

The purpose of this study is to develop a new program for elementary math-gifted students by using 'Girih Tililng' and apply it to the elementary students to improve their math-ability. Girih Tililng is well known for 'the secrets of mathematics hidden in Mosque decoration' with lots of recent attention from the world. The process of this study is as follows; (1) Reference research has been done for various tiling theories and the theories have been utilized for making this study applicable. (2) The characteristic features of Mosque tiles and their basic structures have been analyzed. After logical examination of the patterns, their mathematic attributes have been found out. (3) After development of Girih tiling program, the program has been applied to math-gifted students and the program has been modified and complemented. This program which has been developed for math-gifted students is called 'Exploring the Secrets of Girih Hidden in Mosque Patterns'. The program was based on the Renzulli's three-part in-depth learning. The first part of the in-depth learning activity, as a research stage, is designed to examine Islamic patterns in various ways and get the gifted students to understand and have them motivated to learn the concept of the tiling, understanding the characteristics of Islamic patterns, investigating Islamic design, and experiencing the Girih tiles. The second part of the in-depth learning activity, as a discovery stage, is focused on investigating the mathematical features of the Girih tile, comparing Girih tiled patterns with non-Girih tiled ones, investigating the mathematical characteristics of the five Girih tiles, and filling out the blank of Islamic patterns. The third part of the in-depth learning activity, as an inquiry or a creative stage, is planned to show the students' mathematical creativity by thinking over different types of Girih tiling, making the students' own tile patterns, presenting artifacts and reflecting over production process. This program was applied to 6 students who were enrolled in an unified(math and science) gifted class of D elementary school in Daejeon. After analyzing the results produced by its application, the program was modified and complemented repeatedly. It is expected that this program and its materials used in this study will guide a direction of how to develop methodical materials for math-gifted education in elementary schools. This program is originally developed for gifted education in elementary schools, but for further study, it is hoped that this study and the program will be also utilized in the field of math-gifted or unified gifted education in secondary schools in connection with 'Penrose Tiling' or material of 'quasi-crystal'.

• Food Science and Preservation
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• v.24 no.7
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• pp.898-907
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• 2017

This study was aimed to test harvest time effect with polyethylene (PE) film liner, 1-methylcyclopropene (1-MCP) and aminoethoxyvinylglycine (AVG) treatments on fruit quality attributes in 'Sangjudungsi' persimmon fruit during cold storage. The fruits were harvested 10 days earlier in 2016 than the mature harvest time in 2015. The ethylene production was significantly lower in early harvested fruits than in mature harvested ones. Flesh firmness was maintained higher in 1-MCP treated fruit than in other treatments during cold storage. The rate of fruit weight loss was significantly inhibited by PE film liner treatment during storage, regardless of harvest time. 1-MCP treatment showed less change in fruit peel color variables ($L^*$ and $b^*$) from the calyx-end and equatorial regions during cold storage, compared with those from the control and PE film treatments. The incidence rate of fruit decay and softening was higher in PE film treated fruits than in the other treatments. However, there was no decay detected in AVG treated fruit. The early harvested fruits were maintained higher flesh firmness, compared with mature harvested fruits. Nevertheless, the mature harvested fruits showed much higher soluble solids content, the redness (Hunter a value) of the fruit peel and respiration rate, compared with early harvested fruits. Furthermore, the rate of weight loss in the fruit was remarkably inhibited in the PE film treatment.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.10
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• pp.1326-1333
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• 2007

For preparing the basic ingredients of Gomtang-like products from the extracts of salmon frame, the extraction conditions of salmon frame were examined, and the characteristics of the extracts were compared with commercial Gomtang. Based on the crude protein, Ex-N and sensory attributes, the extractions were optimized by extracting pretreated-salmon frame in 12 times (v/w) of water for 12 hrs, before filtering with cheese cloth to yield 3 times the volume of the raw material. The concentrations of heavy metals in extracts from salmon frame were below the safety limits suggested by KFDA. The mai or amino acids were glutamic acid and aspartic acid as the free amino acids, and glycine, proline, and glutamic acid as the total amino acids. The calcium and phosphorus contents were 18.0 mg/100 mL and 33.1 mg/100 mL, respectively, and they accounted for 20% and 18% of the recommended daily allowance for mineral intake. The angiotensin I converting enzyme (ACE) inhibitory activity was improved by incubation with Flavourzyme for 4 hrs and its $IC_{50}$ was 2 mg/mL. The results above suggested that the enzymatic hydrolysates from extracts of salmon frame could be used as a basic ingredient for preparing Gomtang-like products.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.558-568
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• 2021

Poor supervision and tourism activities have resulted in forest degradation in islands in Korea. Since the southern coastal region of the Korean peninsula was originally dominated by warm-temperate evergreen broad-leaved forests, it is desirable to restore forests in this region to their original vegetation. In this study, we identified suitable areas to be restored as evergreen broad-leaved forests by analyzing the environmental factors of existing evergreen broad-leaved forests in the islands of Jeollanam-do. We classified forest lands in the study area into six vegetation types from Sentinel-2 satellite images using a deep learning algorithm and analyzed the tolerance ranges of existing evergreen broad-leaved forests by measuring the locational, topographic, and climatic attributes of the classified vegetation types. Results showed that evergreen broad-leaved forests were distributed more in areas with a high altitudes and steep slope, where human intervention was relatively low. The human intervention has led to a higher distribution of evergreen broad-leaved forests in areas with lower annual average temperature, which was an unexpected but understandable result because an area with higher altitude has a lower temperature. Of the environmental factors, latitude and average temperature in the coldest month (January) were relatively less contaminated by the effects of human intervention, thus enabling the identification of suitable restoration areas of the evergreen broad-leaved forests. The tolerance range analysis of evergreen broad-leaved forests showed that they mainly grew in areas south of the latitude of 34.7° and a monthly average temperature of 1.7℃ or higher in the coldest month. Therefore, we predicted the areas meeting these criteria to be suitable for restoring evergreen broad-leaved forests. The suitable areas cover 614.5 km², which occupies 59.0% of the total forest lands on the islands of Jeollanamdo, and 73% of actual forests that exclude agricultural and other non-restorable forest lands. The findings of this study can help forest managers prepare a restoration plan and budget for island forests.

• Korean Journal of Food Science and Technology
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• v.54 no.3
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• pp.334-342
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• 2022

To meet the needs of Muslim consumers, sausages were prepared using Halal-certified chicken thighs and different amounts of biji powder (0, 20, 30, 40, and 50%), and then the properties of the sausages were compared. As the biji powder levels increased, both the moisture content and the pH of the sausages significantly decreased, whereas their fiber content increased. As the biji powder levels increased, the free radical scavenging effect (DPPH, ABTS) and water holding capacity also increased, and the textural properties also improved. When Muslim consumers evaluated the sensory attributes of the sausages prepared in this experiment and those currently on the market, the ones prepared in this experiment were preferred over the market products. Based on the above results, chicken sausage for Muslim consumers could be successfully produced, and their overall quality and antioxidant effects could be improved by the addition of biji powder (up to 30%).

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.17-29
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• 2021

Recently, as social distancing have been raised due to the re-spread of COVID-19, the number of serial entrepreneurs who are closing their business is rapidly increasing. Learning from failure is a source of success, but business failure can result in psychological and economic losses and negative emotions of the serial entrepreneur. At this point, it is very important to find a way to recover the negative emotions caused by business failures of serial entrepreneurs. Recently, a strategic model has emerged to deal with the negative emotions of grief caused by business failures of serial entrepreneurs. This study identified the recovery factors from the grief of business failures of serial entrepreneurs and analyzed Shepherd's(2003) three areas: loss orientation, restoration orientation, and dual process. To this end, individual in-depth interviews were conducted with 12 small business serial entrepreneurs who challenged re-startup to identify the attributes of recovery factors that were not identified with quantitative data. As a result of the study, first, recovery factors were investigated in three areas: individual orientation, family orientation, and network orientation. It was found to help improve recovery in nine categories: self-esteem, persistence, personal competence, hobbies, self-confidence, family support, networks, religion, and social support. Second, recovery obstacle factors were investigated in three areas: psychological, economic, and environmental factors. Nine categories including family, health, social network, business partner, competitor, partner, fund, external environment, and government policy were found to persist negative emotions. Third, the emotional processing process for grief was investigated in three areas: loss orientation, restoration orientation, and dual process. Ten categories such as family, partner support, social member support, government support, hobbies, networks, change of business field, moving, third-party perspective, and meditation were confirmed to enhance rapid recovery in the emotional processing process for grief. The implications of this study are as follows. The process of recovering from the grief caused by business failures of serial entrepreneurs was attempted by a qualitative study. By extending the theory of Shepherd(2003), This study can be applied to help with recovery research. In addition, conceptual models and propositions for future empirical research were presented, which can be discussed in carious academic ways.

• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.1-16
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• 2024

Most wetlands worldwide have suffered from extensive human exploitation. Unfortunately they have been less explored compared to river and lake ecosystems despite their ecological importance and economic values. This is the same case in Korea. This study was aimed to estimate the assemblage attributes and distribution characteristics of benthic macroinvertebrates for fifty wetlands distributed throughout subtropical Jeju Island in 2021. A total of 133 taxa were identified during survey periods belonging to 53 families, 19 orders, 5 classes and 3 phyla. Taxa richness ranged from 4 to 31 taxa per wetland with an average of 17.5 taxa. Taxa richness and abundance of predatory insect groups such as Odonata, Hemiptera and Coleoptera respectively accounted for 67.7% and 68.2% of the total. Among them Coleoptera were the most diverse and abundant. Taxa richness and abundance did not significantly differ from each wetland type classified in accordance with the National Wetland Classification System. There were three endangered species (Clithon retropictum, Lethocerus deyrolli and Cybister (Cybister) chinensis) and several restrictively distributed species only in Jeju Island. Cluster analysis based on the similarity in the benthic macroinvertebrate composition largely classified 50 wetlands into two major clusters: small wetlands located in lowland areas and medium-sized wetlands in middle mountainous regions. All cluster groups displayed significant differences in wetland area, long axis, percentage of fine particles and macrophyte composition ratio. Indicator Species Analysis selected 19 important indicators with the highest indicator value of Ceriagrion melanurum at 63%, followed by Noterus japonicus (59%) and Polypylis hemisphaerula (58%). Our results are expected to provide fundamental information on the biodiversity and habitat environments for benthic macroinvertebrates in wetland ecosystems, consequently helping to establish conservation and restoration plans for small wetlands relatively vulnerable to human disturbance.