• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.140-149
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• 1996

Cursive characters are written on an economical principle to reduce the motion of a pen in the limit of distinction between characters. That is, the pen is not lifted up to move for writing a next stroke, the pen is not moved at all, or connected two strokes chance their shapes to a similar and simple shape which is easy to be written. For these reasons, strokes and korean alphabets are not only easy to be changed, but also difficult to be splitted. In this paper, we propose a curvature stroke modeling method for splitting and matching by using a structural primitive. A curvature stroke is defined as a substroke which does not change its curvanture. Input strokes handwritten in a cursive style are splitted into a sequence of curvature strokes by segmenting the points which change the direction of rotation, which occur a sudden change of direction, and which occur an excessive rotation Each reference of korean alphabets is handwritten in a printed style and is saved as a sequence of curvature strikes which is generated by splitting process. And merging process is used to generate various sequences of curvature strikes for matching. Here, it is also considered that imaginary strokes can be written or omitted. By using a curvature stroke as a unit of recognition, redundant splitting points in input characters are effectively reduced and exact matching is possible by generating a reference curvature stroke, which consists of the parts of adjacent two korean alphasbets, even when the connecting points between korean alphabets are not splitted. The results showed 83.6% as recognition rate of the first candidate and 0.99sec./character (CPU clock:66MHz) as processing time.

• Journal of KIISE:Information Networking
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• v.29 no.6
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• pp.595-612
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• 2002

One of the most important issues in guaranteeing the high degree of QoS on mobile computing is how to reduce hand-off drops caused by lack of available bandwidth in a new cell. Each cell can request bandwidth reservation to its adjacent cells for hand-off calls. This reserved bandwidth can be used only for hand-offs, not for new calls. It is also important to determine how much of bandwidth should be reserved for hand-off calls because reserving too much would increase the probability of a new call being blocked. Therefore, it is essential to develop a new mechanism to provide QoS guarantee on a mobile computing environment by reserving an appropriate amount of bandwidth and call admission control. In this paper. bandwidth reservation and call admission control mechanisms are proposed to guarantee a consistent QoS for multimedia traffics on a mobile computing environment. For an appropriate bandwidth reservation, we propose an adaptive bandwidth reservation mechanism based on an MPP and a 2-tier cell structure. The former is used to predict a next move of the client while the latter to apply our mechanism only to the client with a high hand-off probability. We also propose a call admission control that performs call admission test only on PNC(Predicted Next Cell) of a client and its current cell. In order to minimize a waste of bandwidth caused by an erroneous prediction of client's location, we utilize a common pool and QoS adaptation scheme. In order evaluate the performance of our call admission control mechanism, we measure the metrics such as the blocking probability of new calls, dropping probability of hand-off calls, and bandwidth utilization. The simulation results show that the performance of our mechanism is superior to that of the existing mechanisms such as NR-CAT2, FR-CAT2, and AR-CAT2.

• Korean Journal of Food Science and Technology
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• v.27 no.6
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• pp.1017-1027
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• 1995

This study was attempted to investigate physicochemical properties, molecular structural properties of native and acid-treated chestnut starch and chestnut starch gel. The amylose content was 18.9% and X-ray diffraction pattern showed Cb type. Swelling power was increased abruptly in the range of $65^{\circ}C{\sim}75^{\circ}C$ but increased slowly after that and solubility was increased abruptly until $70^{\circ}C$ but increased slowly after that. In amylograms which have different heating temperatures, cooling viscosity at $50^{\circ}C$ was reduced as heating temperature was increased. In molecular structural properties of amylose, ${\lambda}_{max}$ was 640 nm, ${\beta}-amylolysis$ limit was 84.2% and the degree of polymerization was 951 and in those of amylopectin, ${\lambda}_{max}$ was 570 nm, ${\beta}-amylolysis$ limit was 58.2%, the degree of polymerization was 1371 and average chain length was 22.6. In gel chromatography elution profiles of starch and amylose, 4.0% and 11.5% of low molecular weight-molecules($<5{\times}10^5$) were leached out. In gel chromatography elution profiles of soluble starch, the higher heating temperature was, the more high molecular weight-starches were leached out. The elution profiles after debranching amylopectin with pullulanase showed 2.2 of the ratio of peakIII(DP 10-15) to peakII(DP 35-45). Acid hydrolysis extent of 2.2 N HCI-treated starch at $35^{\circ}C$ for 10 days was 96% and hydrolysis rate showed two step pattern which had border line at 4 days. In elution profiles of acid treated chestnut starch, amylopectin peak was disappeared compeletly after 6 hrs and converted short chains of DP 10-15. Amylose content was increased until 6 hrs but decreased after that. Hardness of starch gel made at $75^{\circ}C$ of heating temperature and cohesiveness of starch gel made at $85^{\circ}C$ of heating temperature were the highest. Retrogradation rate of starch gels were relatively high, especially for the starch gel made at $75^{\circ}C$ of heating temperature.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.34-42
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• 2019

Baseflow which is one of the unmeasurable components of streamflow and slowly flows through underground is important for water resource management. Despite various separation methods from researches preceded, it is difficult to find a significant separation method for baseflow separation. This study applied the MRC method and developed the improved approach to separate baseflow from total streamflow hydrograph. Previous researchers utilized the whole streamflow data of study period at once to derive synthetic MRCs causing unreliable results. This study has been proceeded with total nine areas with gauging stations. Each three areas are selected from 3 domestic major watersheds. Tool for drawing MRC had been used to draw MRCs of each area. First, synthetic MRC for whole period and two other MRCs were drawn following two different criteria. Two criteria were set by different conditions, one is flow condition and the other is seasonality. The whole streamflow was classified according to seasonality and flow conditions, and MRCs had been drawn with a specialized program. The MRCs for flow conditions had low R2 and similar trend to recession segments. On the other hand, the seasonal MRCs were eligible for the baseflow separation that properly reflects the seasonal variability of baseflow. Comparing two methods of assuming MRC for baseflow separation, seasonal MRC was more effective for relieving overestimating tendency of synthetic MRC. Flow condition MRCs had a large distribution of the flow and this means accurate MRC could not be found. Baseflow separation using seasonal MRC is showing more reliability than the other one, however if certain technique added up to the flow condition MRC method to stabilize distribution of the streamflow, the flow conditions method could secure reliability as much as seasonal MRC method.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.2
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• pp.165-170
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• 1994

High quality rapeseed cultivars including Nojeokchae, Yeongsanyuchae Halla-yuchae and Tamrayuchae have been released and recommended as a zero erucic acid variety to Cheju farmers for 13 years, where is a major rapeseed production area in korea. However, rapeseeds produced in Cheju island in 1992 and 1993 contained 47.7% and 37.0% of erucic acid respectively resulting in poor quality oil being not adequate for edible oil. It was considered that the zero erucic acid varieties did not have an opportunity to be cultivated in Cheju island by farmers living in the Island. Thus, the new rapeseed varieties without erucic acid should be bred and recommended to the farmers of southern area of Korea as a multiple cropping crop just after rice harvest, and for large scale mechanized and labour-serving rapeseed culture. The change of rapeseed breeding goal would be desirable for fatty acid composition improvement of rapeseed to develop varieties adaptable to southern part of Korea, and to produce rapeseed oil directly used as an edible oil safely.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• 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.