• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.74-81
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• 1995

Several non-manifold data structures have been compared, which are radial-edge data structure, partial-face data structure, vertex-based data structure, and Yamaguchi's data structrue. All the entities in the data structures are classified into common entities and special entities. The entities are also classified as model entities, primitive entities bounding entities, and coupling entities. The four data structures for nonmanifold solid modelers are compared in terms of accessing efficiency, storage requirements, and inclusion of circulation. The results of comparison will serve as the basis to develope a nonmanifold modeler.

• International Journal of Contents
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• v.18 no.1
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• pp.56-64
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• 2022

To improve the cooperation ability of emergency entities, in this research, the emergency activities model, skill contribution degree, entity-relationship strength, activity continuity, and emergency entity cooperation degree were defined. Emergency entity cooperation degree and emergency activity continuity table were constructed with emergency cases, emergency plans, and emergency drill plans, and factors were further excavated which affected them. In this paper, we focus on the factors which affect the cooperation ability of emergency entities, the relationship between the emergency cooperation ability and the number of cooperation, entity-relationship intensity, emergency activity frequency, and skill contribution of fire entities and medical entities were obtained. These data results are of great significance to decision-makers in formulating emergency rescue and emergency plans.

• Genomics & Informatics
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• v.18 no.2
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• pp.15.1-15.6
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• 2020

Named entity recognition tools are used to identify mentions of biomedical entities in free text and are essential components of high-quality information retrieval and extraction systems. Without good entity recognition, methods will mislabel searched text and will miss important information or identify spurious text that will frustrate users. Most tools do not capture non-contiguous entities which are separate spans of text that together refer to an entity, e.g., the entity "type 1 diabetes" in the phrase "type 1 and type 2 diabetes." This type is commonly found in biomedical texts, especially in lists, where multiple biomedical entities are named in shortened form to avoid repeating words. Most text annotation systems, that enable users to view and edit entity annotations, do not support non-contiguous entities. Therefore, experts cannot even visualize non-contiguous entities, let alone annotate them to build valuable datasets for machine learning methods. To combat this problem and as part of the BLAH6 hackathon, we extended the TextAE platform to allow visualization and annotation of non-contiguous entities. This enables users to add new subspans to existing entities by selecting additional text. We integrate this new functionality with TextAE's existing editing functionality to allow easy changes to entity annotation and editing of relation annotations involving non-contiguous entities, with importing and exporting to the PubAnnotation format. Finally, we roughly quantify the problem across the entire accessible biomedical literature to highlight that there are a substantial number of non-contiguous entities that appear in lists that would be missed by most text mining systems.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.885-895
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• 2001

Existing system analysis models suggest various ideas to present entity relations and event flows for consistency between analysis and design paradigms. However, they are preferred to derive and arrange related entities on system flow than to identify entities. To identify entities systematically is a basic and important work of software development, and identified entities can be major assets of business system. In case of business systems the business rules or the computed or derived information like attendance lists of lecture system can be the most important system assets. The management information or meta data are also. In this paper, we suggest a business system analysis models to derive and present entities. System is identified entities, interfaces and event or behaviors through this model then entities are extended to independent entities, dependent entities, which are dependent to independent entities, constraint shows the physical and administrative notices. Various entity identification can reduce the incompleteness of entity analysis.

• Korean Journal of Construction Engineering and Management
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• v.5 no.1 s.17
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• pp.140-148
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• 2004

Based on the CMBOK (Construction Project Management Body of Knowledge) Framework previously developed in early study by the authors in conjunction with use of some questionnaire surveys and personal interviews with industry professionals, the authors analyze interactions among the entities in the CMBOK framework for the extraction of pivotal entities of construction project management and identify twelve pivotal entities in construction project management, then verify the existence of twelve pivotal entities in real construction project management of construction company and checked the validity of the entities with a real case of interaction phenomenon. This research provides the construction industry with a starting point for improving construction project management efficiency by identifying the pivotal entities.

• 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 the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.108-118
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• 1989

The clustering problem for multi-dimensional entities is investigated. A heuristic method, which is named as Difference Order Clustering (DOC) is developed for the grouping of multi-dimensional entities DOC method has an advantage of identifying the bottle-neck entities. Comparisons among the proposed DOC method, modified rank order clustering (MODROC) method, and lexicographical rank order clustering using minimum spanning tree (lexico-MMSTROC) are illustrated by a part type selection problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.672-678
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• 2008

Entities in reality have direct relationships between each other. They also have new and indirect relationships through such direct relationships. An ontology gives explicit meaning of such relationships. Thus, we can discover new relationships between entities based on an ontology. Such new relationships are applied in indentifying new communities or constructing social networks. Measuring for the degree of relationships is an important problem in such domains. This paper proposes a measurement for the degree of relationships between entities based on an ontology. Most of researches are based on connected paths between entities. However, there are meaningful relationships between two entities through the schema in an ontology even through there are no connected paths between the entities. The proposed method measures for the degree of relationships between two entities not based on connected paths, but also relationships through the schema. The experiment result shows that the relationships through the schema are meaningful to measure the degree of relationships between entities.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.213-231
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• 2021

Purpose: This study intends to provide decision-making information to improve efficiency by analyzing the management efficiency of smart greenhouse business entities and identifying factors that affect the efficiency based on input and output. Methods: The subjects of analysis were business entities for cultivating strawberries in smart greenhouses in Jeolla region (northern and southern Jeolla provinces), and the analysis focused on the management performance of the 2019-2020 crop period (year). Data Envelopment Analysis(DEA) was applied as an analysis method for efficiency analysis, Quantile Regression(QR) analysis was applied as a factor affecting the efficiency. Results: The reason for the efficiency gap between business entities was that there were many business entities that did not minimize the input cost at the current level of output, and the area where the variance among business entities was large was the fixed cost per 10a. In the results of the affecting factor analysis, it was found that the seed-seedlings cost, fertilizer cost, other material cost, and employment and labor cost had a negative (-) effect on the efficiency, and that the repair and maintenance cost had a positive (+) effect. Conclusion: Therefore, to achieve the efficiency of scale, it is necessary to reduce the input scale to an appropriate level. In the case of business entities with low efficiency by quartile, the seed-seedlings, fertilizer, and other material costs reduce expenditures, and repair maintenance costs can improve efficiency by increasing expenditures.

• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.2
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• pp.12-37
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• 2017

The analysis of results of the market of loans granted to legal entities, the physical persons are provided in the work. The assessment of condition of industry segments of the market of the credits of legal entities is carried. The results of assessment of the market of the credits of physical persons by types of the granted loans are provided. The correlation and regression analysis on the industry segments of crediting of legal entities is carried out. The dynamics of development of debt on the industry segments of crediting is determined. The results show that: Hypothesis 1. The amount of the issued credits to the legal entities steadily in-creases on all industries of economy. Communication between the industry segments of market very high. Hypothesis 2. Crediting of physical persons is characterized by relative stability. The structure of overdue debt repeats the structure of the issued credits to the physical persons.