• Korean Journal of Computational Design and Engineering
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• v.7 no.1
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• pp.9-17
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• 2002

The study is insufficient on process planning of the elliptical deep drawing product. Thus, in this present study, the expert system for elliptical deep drawing products was constructed by using process sequence design. The expert system was developed to be based on the general concept of each entity. The system was developed in this work consists of sixth modules. The first one is a shape recognition module to recognize non-axisymmetric products and to generate Entity_list. The second one is three dimensional (3-D) modeling module to calculate the surface area for non-axisymmetric products. The third one is a blank design module to create suggested blanks of three shapes with the identical surface area. The fourth one is shape design module based on the production rules that play the most important role in an expert system for manufacturing. The production rules are generated and upgraded by inter- viewing field engineers, plastic theory and experiments. The fifth and sixth ones are a graphic module to visualize results of the expert system and a post module to rise user's convenience, respectively. According to constructed the expert system for process sequence design, it was possible to reduce the lead time.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.137-142
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• 1999

The purpose of this study is to develope a CAD-based tool for rasterization of polygonal vector map in AutoCAD. To identity the layer property of polygonal entity with user-defined coordinates as topology, algorithm in processing entity data of selection set that intersected with scan line was used, and the layers were extracted sequentially by sorted intersecting points in data-list. In addition to the functions for querying and modifying topology, two options for mapping were set up to construct plan projection type and to change meshes' properties in existing DTM data. In case of plan projection type, user-defined cell size of 3DFACE mesh is available for more detailed edge, and topological draping on landform can be executed in case of referring DTM data as an AutoCAD's drawing. The concept of algorithm was simple and clear, but some unexpectable errors were found in detecting intersected coordinates that were AutoCAD's error, not the utility's. Also, the routines to check these errors were included in algorithmic processing. Developed utility named MESHMAP was written in entity data control functions of AutoLISP language and dialog control language(DCL) for the purpose of user-oriented interactive usage. MESHMAP was proved to be more effective in data handling and time comparing with GRIDMAP module in LANDCADD which has similar function.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.573-584
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• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.77-87
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• 1994

This paper deals with an automated forming sequence design system by which designers can determine desirable operation sequences even if they have little experience in the design of cold forging process. The forming sequence design in the cold forging is very important and requires many kinds of technical and empirical knowledge. They system isproposed, which generates forming sequence plans for the multistage cold forging of axisymmtrical solid products. Since the process of metal forming can be considered as a transformation of geometry, treatment of the geometry of the product is a key in planning process. To recognize the geometry of the product section, section entity representation and primitive geometries were used. Section entity representation can be used for the calculation of maximum diameter, maximum height, and volume. Forming sequence for the part can be determined by means of primitive geometries such as cylinder, cone, convex, and concave. By utilizing this geometrical characteristics (diameter, height, and radius), the product geometry is expressed by a list of the priitive geometries. Accordingly the forming sequence design is formulated as the search problem which starts with a billet geometry and finishes with a given product one. Using the developed system, the sequence drawing with all dimensions, which includes the proper sequence of operations for the part, is generated under the environment of AutoCAD. Based on the results of forming sequence, process variables(strain, punch pressure, die inner pressure, and forming load) are determined.

• Imaging Science in Dentistry
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• v.37 no.4
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• pp.221-223
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• 2007

The radiographic diagnosis of typical Stafne bone cavity could be done easily with cyst-like round or oval radiolucency near the angle of the mandible, under mandibular canal with or without involving mandibular base, and no symptoms. However there are some atypical cases suggesting possible variations of this entity. We report a quite unusual case, where Stafne bone cavity was lastly included in the differential diagnosis list. Histological examination of salivary gland tissues confirmed the final diagnosis.

• Journal of KIISE
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• v.44 no.5
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• pp.496-502
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• 2017

Pointer Networks is a deep-learning model for the attention-mechanism outputting of a list of elements that corresponds to the input sequence and is based on a recurrent neural network (RNN). The coreference resolution for pronouns is the natural language processing (NLP) task that defines a single entity to find the antecedents that correspond to the pronouns in a document. In this paper, a pronoun coreference-resolution method that finds the relation between the antecedents and the pronouns using the Pointer Networks is proposed; furthermore, the input methods of the Pointer Networks-that is, the chaining order between the words in an entity-are proposed. From among the methods that are proposed in this paper, the chaining order Coref2 showed the best performance with an F1 of MUC 81.40 %. The method showed performances that are 31.00 % and 19.28 % better than the rule-based (50.40 %) and statistics-based (62.12 %) coreference resolution systems, respectively, for the Korean pronouns.

• Journal of KIISE
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• v.41 no.11
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• pp.992-1005
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• 2014

Coreference resolution finds all expressions that refer to the same entity in a document. Coreference resolution is important for information extraction, document classification, document summary, and question answering system. In this paper, we adapt Stanford's Multi-pass sieve system, the one of the best model of rule based coreference resolution to Korean. In this paper, all noun phrases are considered to mentions. Also, unlike Stanford's Multi-pass sieve system, the dependency parse tree is used for mention extraction, a Korean acronym list is built 'dynamically'. In addition, we propose a method that calculates weights by applying transitive properties of centers of the centering theory when refer Korean pronoun. The experiments show that our system obtains MUC 59.0%, $B_3$ 59.5%, Ceafe 63.5%, and CoNLL(Mean) 60.7%.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4369-4371
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• 2012

Aim: Metastatic tumor of bone is the most common malignancy involving bone and is an important predictor of prognosis in advanced cancers. The prognosis depends upon the primary site of origin and the extent of disease. In current study, we present the pattern and distribution of metastatic bone disease seen in the leading cancer care center of Pakistan, Shaukat Khanum Cancer Hospital & Research Center (SKMCH & RC), Lahore. Materials & Methods: All cases of bony metastatic disease were included that presented in the Pathology Department, from Jan 2005 to July 2011. Patients of all ages and both sexes were included. Primary bone tumors, lymphomas, sarcomas and other malignancies were excluded. The data were recorded and analyzed with SPSS 16.0. Results: A total of 146 cases of metastatic bone disease were included in the study. Out of the total cases, 79 were male and 67 were female. Age range 25-82 years (median 52). Hip bone was the most frequent bone involved, with femur and vertebrae as second and third in the list. The commonest bone involved in males was vertebrae with 23 cases and in females was hip bone with 22 cases. Regarding primary site, cancers of breast, prostate and gastrointestinal tract were at the top of the list with prostate and breast being the most frequent primary sites of metastasis in males and females respectively. Conclusion: Bone metastasis is an important entity to consider in the differential diagnosis whenever a bony tumor especially carcinoma present in older age. Our data are comparable with international findings and the literature available regarding the site and distribution of skeletal metastatic lesions. A slight deviation noted was more common bony metastatic lesions with ovarian primaries in females and gastrointestinal tract cancers in males in our study.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.101-124
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• 2023

Book recommendations in libraries can be used as a tool to help users with vague needs browse and select books. Therefore, libraries spend a lot of time and effort to introduce various materials to their users and recommend suitable books. Meanwhile, various organizations other than libraries also publish recommended reading lists, and these lists reflect the intentions of the entity that selects the recommended books. The purpose of this study is finding out how the recommended book lists of libraries differ from the recommended reading lists of non-library organizations. To achieve this, the study limited the scope to 'teenagers', who are the main target audience for book recommendations in many organizations, and compared the recommended book lists of libraries and non-library organizations in terms of (1) the selection criteria for recommended books, (2) the characteristics of recommended books, and (3) the way of providing recommended book lists. Through this analysis, the study identified the characteristics and limitations of library recommended book lists and discussed areas for improvement.

• MALSORI
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• v.68
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• pp.115-126
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• 2008

In this paper, we propose a vocabulary coverage improvement method for embedded continuous speech recognition (CSR) using knowledgebase. A vocabulary in CSR is normally derived from a word frequency list. Therefore, the vocabulary coverage is dependent on a corpus. In the previous research, we presented an improved way of vocabulary generation using part-of-speech (POS) tagged corpus. We analyzed all words paired with 101 among 152 POS tags and decided on a set of words which have to be included in vocabularies of any size. However, for the other 51 POS tags (e.g. nouns, verbs), the vocabulary inclusion of words paired with such POS tags are still based on word frequency counted on a corpus. In this paper, we propose a corpus independent word inclusion method for noun-, verb-, and named entity(NE)-related POS tags using knowledgebase. For noun-related POS tags, we generate synonym groups and analyze their relative importance using Google search. Then, we categorize verbs by lemma and analyze relative importance of each lemma from a pre-analyzed statistic for verbs. We determine the inclusion order of NEs through Google search. The proposed method shows better coverage for the test short message service (SMS) text corpus.