• Korean journal of food and cookery science
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• v.18 no.6
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• pp.692-697
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• 2002

The purpose of this study is to investigate the characteristics of the doughs and noodles cooked with the pea starch-wheat composite flour which was substituted with 20% and 30% of pea starch for the flour by the mechanical and sensory evaluation. Wheat dough had the most cohesive property among various composite non.(p＜0.05) There was no significant differences in weight gain after cooking among various noodles. The more the pea starch was subsituted, the lighter the color was shown by increasing L value. It was also noted that the b value was decreased significantly. While pea starch noodle were more transparent in appearance and less smooth in the texture, corn starch-wheat composite flour noodle was sorter in the texture significantly. There was no significant difference on the hardness between wheat and pea stach composite flour noodles. There were also no significant differences in stickiness, chewiness and overall acceptability among various noodles. Considering mechanical and sensory results, the composite flour with 20% substitution of pea starch for flour was more suitable for the production of the noodle than those of 30% substitution of pea starch.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.1
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• pp.59-70
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• 2013

This study was to suggest cultural landscape preservation, value creation, as well as utilization plan to help landscape development of Hahoe village by identify the existence of Okyeonsipyeong(玉淵十詠) natural features, which were set around Buyongdae(芙蓉臺) in Hahoe Village by Seoae(西崖) Ryu, Seongryong(柳成龍), and understanding their characteristics and meanings of natural features and meanings. Based on the writings of "Okyeonseodanggi" and "Okyeonsipyeong", the major results of this study are as belows. 'Okyeon(玉淵)' letters carved on the rocks, also known as the name of pavilion in Okyeonjeongsa(玉淵精舍), is the center of Okyeonsipyeong that symbolizes the enlightenment of clean noble man, as well as the symbolic locational expression of studying room. One of Okyeonsipyeong, 'Wansimjae', is assumed to be the name from the combination of two Buddhist names, 'Wanjeok(玩寂)' and 'Seshim(洗心)', 'Dangho(堂號)', lined on both sides with Wonlakjae, the residence of Seoae, as the center. Wansimjae is after all the natural feature indicating the overall Okyeonjeongsa as the core of Okyeonsipyeong with west edge Gyeomamjeongsa(謙巖精舍). Among ten Okyeonsipyeong natural features, Wansimjae(玩心齋), Ganjukmun(看竹門), Gyeomamsa(謙菴舍), Dalgwandae(達觀臺), Ssangsongae(雙松厓), and Dohwacheon (桃花遷) are on the right side of the stairway from Okyeonjeongsa to Gyeomamjeongsa, while Chuwoldam(秋月潭), Neungpadae(凌波臺), Gyeseonam(繫船巖), and Jijuam(砥柱巖) are on the road to the cliff under river cliff in Buyongdae as well as to the dock, and all are located within 500m radius close and diameter area. As the results of lexeme and context analyses of Okyeonsipyeong poet, they are mainly about Confucian teachings symbolizing the constancy of the classical scholar including ego becoming one with the nature and back to the nature, unworldliness and farsighted view, transcendence and seclusion, as well as integrity spirit. In Dohwacheon and Gyeomamsa poets, there is Tao characteristics and brotherhood that pursue fairylands such as Mooreungdowon(武陵桃源). To create tourism brand and landscape of Okyeonsipyeong, it is necessary to prepare storytelling plans including the letters carved on the rocks introduction in Buyongdae area, and also synopsis of the Silgyeongsusang musical, 'Buyongjiae(芙蓉之愛)' that is related to 10 natural features. In addition, the related plans of the experience road from Gyeseonam, which is the boat stop in Buyongdae, to Ganjukmun of Okyeonjeongsa, and again to viewing routes on the stairways to Gyeomamjeongsa using boats are necessary. For preliminary preservation and maintenance plans, the safety of the stairway from Okyeonjeongsa to Gyeomamjeongsa should be secured, the rock inscription should be preserved, landscape interpretation plates should be installed, trees and shrubs around Dohwacheon rock inscription should be removed, Dalgwandae letters carved on the rocks should be restored, and the bamboo forest outside Ganjukmun as well as Prunus persica plantation around Dohwacheon should be pointed out.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of Gastric Cancer
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• v.6 no.4
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• pp.263-269
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• 2006

Purpose: The aim of this study was to investigate the causes of under-staging in patients with advanced gastric cancer that was proven to be unresectable after a laparotomy. Materials and Methods: We retrospectively analyzed 25 gastric cancer patients who had undergone a diagnostic laparotomy between 2001 and 2005. For the preoperative evaluation, spiral CT and multidetector-row CT were performed. We analyzed the clinicopathologic features of patients and compared the image findings and the results of surgery. The causes of under-staging were divided into 3 groups; patient factor, CT factor, and interpretation factor. Results: Grossly, there were 12 cases of Borrmann type-III tumors and 13 cases of Borrmann type-IV tumors. The most frequent histologic type was poorly differentiated adenocarcinomas (8 cases) and signet ring cell carcinomas (7 cases). There were 13 cases of adjacent organ invasion, and the pancreas was the most frequently invaded organ (9 cases). There were 17 cases of peritoneal metastasis, and 3 cases of distant lymph node metastasis. For the cause of under-staging, there were four cases of patient factor, 19 cases of interpretation factor, and 9 cases of CT factor. In three cases, the cause of under-staging could not be identified. Conclusion: CT interpretation factor was the most frequent cause of under-staging in the preoperative diagnosis with gastric cancer patients. Therefore, more cautious CT interpretation is necessary to avoid unnecessary laparotomies in gastric cancer patients.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.529-544
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• 2001

Prefetching is an effective method to minimize the number of roundtrips between the client and the server in database management systems. In this paper we propose new notions of the type-level access pattern and the type-level access locality and developed an efficient prefetchin policy based on the notions. The type-level access patterns is a sequence of attributes that are referenced in accessing the objects: the type-level access locality a phenomenon that regular and repetitive type-level access patterns exist. Existing prefetching methods are based on object-level or page-level access patterns, which consist of object0ids of page-ids of the objects accessed. However, the drawback of these methods is that they work only when exactly the same objects or pages are accessed repeatedly. In contrast, even though the same objects are not accessed repeatedly, our technique effectively prefetches objects if the same attributes are referenced repeatedly, i,e of there is type-level access locality. Many navigational applications in Object-Relational Database Management System(ORDBMs) have type-level access locality. Therefore our technique can be employed in ORDBMs to effectively reduce the number of roundtrips thereby significantly enhancing the performance. We have conducted extensive experiments in a prototype ORDBMS to show the effectiveness of our algorithm. Experimental results using the 007 benchmark and a real GIS application show that our technique provides orders of magnitude improvements in the roundtrips and several factors of improvements in overall performance over on-demand fetching and context-based prefetching, which a state-of the art prefetching method. These results indicate that our approach significantly and is a practical method that can be implemented in commercial ORDMSs.