• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.498-516
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• 2013

Combat Modeling and Simulation (M&S) is significant to decision makers who predict the next direction of wars. Classical methodologies for combat M&S aimed to describe the exact behaviors of combat entities from military doctrines, yet they had a limitation of describing reasonable behaviors of combat entities that did not appear in the doctrines. Hence, this paper proposed a synthesizing modeling methodology for combat entity models considering both 1) the exact behaviors using descriptive modeling and 2) the reasonable behaviors using prescriptive modeling. With the proposed methodology, combat entities can represent a reality for combat actions rather than the classical methodologies. Moreover, the experiment results using the proposed methodology were significantly different from the results using the classical methodologies. Through the analyses of the experiment results, we showed that the reasonable behaviors of combat entities, which are not specified in the doctrines, should be considered in combat M&S.

• 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.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.203-210
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• 2021

This study analyzed the financing ratio by operation fund financing method and their impact on management performance according to the establishment operation management entity of the medical institution. For the analysis method, ANOVA, logistic regression, and regression analysis were conducted using financial information registered with HASPA.The results of the study, The ratio of gross revenue to operating funds differed significantly depending on the establishment operation management entity. In addition, it was found that the financing ratio of each operation fund financing method was significantly related to the management results(deficit, surplus), and the impact of the operation fund financing method on management performance differed according to the establishment operation management entity. As a result, the management of operating funds of medical institutions is deemed appropriate to apply cost management first considering the ratio of revenue to operating funds, and then to utilize internal operating funds.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.65-88
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• 2024

This pilot study explores a method of extracting metadata values and descriptions from records using named entity recognition (NER), a technique in natural language processing (NLP), a subfield of artificial intelligence. The study focuses on handwritten records from the Guro Industrial Complex, produced during the 1960s and 1970s, comprising approximately 1,200 pages and 80,000 words. After the preprocessing process of the records, which included digitization, the study employed a publicly available language API based on Google's Bidirectional Encoder Representations from Transformers (BERT) language model to recognize entity names within the text. As a result, 173 names of people and 314 of organizations and institutions were extracted from the Guro Industrial Complex's past records. These extracted entities are expected to serve as direct search terms for accessing the contents of the records. Furthermore, the study identified challenges that arose when applying the theoretical methodology of NLP to real-world records consisting of semistructured text. It also presents potential solutions and implications to consider when addressing these issues.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.215-237
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• 2024

This study proposes a selection plan for research entities and PIDs and a strategy for building and operating a PID consortium based on a survey of advanced cases of research entities and PID operations in major countries such as the United Kingdom, Germany, Canada, Japan, China, and Australia. The criteria for selecting research entities and PIDs are 'research life cycle' and 'PID infrastructure maturity'. Based on the two selection criteria, it is proposed to prioritize research entity-PID pairs such as 'Researcher-ORCID', 'Publication-DOI', 'Data-DOI', 'Institution-ROR', 'Grant-DOI', and 'Project-RAiD' and expand to other research entities and PIDs in the emerging stage. The strategy for establishing and operating a PID consortium should encourage the participation of various PID stakeholders, identify the latest trends through collaborative networks with domestic and international PID organizations, lead education and outreach activities to raise awareness and increase utilization of PID, and secure policy support and financial stability. This is expected to lay the foundation for domestic research entities to gain visibility and accessibility at the global level.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.83-94
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• 2011

In the biomedical domain, the longest matching method is frequently used for recognizing named entity written in the literature. This method uses a dictionary as a resource for named entity recognition. If there exist appropriated dictionary about target domain, the longest matching method has the advantage of being able to recognize the entities of target domain quickly and exactly. However, the longest matching method is difficult to recognize the enumerated named entities, because these entities are frequently expressed as being omitted some words. In order to resolve this problem, we propose the partial matching method using a dictionary. The proposed method makes several candidate entities on the assumption that the ellipses may be included. After that, the method selects the most valid one among candidate entities through the optimization algorithm. We tested the longest and partial matching method about HLA entities: HLA gene, antigen, and allele entities, which are frequently enumerated among biomedical entities. As preparing for named entity recognition, we built two new resource, extended dictionary and tag-based dictionary about HLA entities. And later, we performed the longest and partial matching method using each dictionary. According to our experiment result, the longest matching method was effective in recognizing HLA antigen entities, in which the ellipses are rare, and the partial matching method was effective in recognizing HLA gene and allele entities, in which the ellipses are frequent. Especially, the partial matching method had a high F-score 95.59% about HLA alleles.

• Journal of Information Management
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• v.40 no.4
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• pp.1-22
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• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.67-77
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• 2018

This paper suggests that LOD establishes its own link policy and publishes it to LOD cloud to provide identity among entities in different LODs. For specifying the link policy, we proposed vocabulary set founded on RDF model as well. We implemented Policy based In-depth Searching and Cleansing(PISC for short) system that proceeds in-depth searching across LODs by referencing the link policies. PISC has been published on Github. LODs have participated voluntarily to LOD cloud so that degree of the entity identity needs to be evaluated. PISC, therefore, evaluates the identities and cleanses the searched entities to confine them to that exceed user's criterion of entity identity level. As for searching results, PISC provides entity's detailed contents which have been collected from diverse LODs and ontology customized to the content. Simulation of PISC has been performed on DBpedia's 5 LODs. We found that similarity of 0.9 of source and target RDF triples' objects provided appropriate expansion ratio and inclusion ratio of searching result. For sufficient identity of searched entities, 3 or more target LODs are required to be specified in link policy.

• Korea Journal of Hospital Management
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• v.7 no.1
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• pp.88-104
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• 2002

According to the change of mandatory referral system in July 1, 2000, the effect to the medical utilization of outpatient clinic and medical income in ophthalmology of tertiary care medical institute, S Hospital in Seoul was evaluated for 6 months before(1999. 12$\sim$2000. 5) and after(2000. 12$\sim$2001. 5). The results were as follows: 1. The number of outpatients was reduced by 16.6%. The number of patient with blindness low vision, retina, glaucoma increased and that of patient with accommodation refractive error, cataract decreased. 2. The number of cataract patients was reduced by 36.6%. The major location of patient's address was changed to nearer to the hospital. The number of cataract surgery reduced in 4.1%, the waiting time reduced in 42.2%, however surgery time increased in 20.2% and number of postoperative complications increased in 11.4%. 3. The income of outpatient clinic and cataract surgery reduced. Among items of outpatient clinic income, the most increased was ocular examination and the most reduced was injection and drugs. Among items of cataract surgery income, the most increased was operation fee and the most decreased was doctor's fee. In conclusion, for the patient, due to the lowered density of outpatient population more space was provided to the patients with more severe disease entity such as blindness' low vision, retina and glaucoma. For the hospital, the need for the expansion of ophthalmology was not found, however that for creation of the special clinics dealing with more severe disease entity was found. Due to reduced income and increased need of financial investment for the equipment and manpower for the more severe disease entity, the ophthalmology of tertiary care medical institute is faced with financial disaster. It is strongly suggested that the cost of medical practice of more severe disease entity be raised to achieve the success after change of mandatory referral system in ophthalmology.