• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.612-628
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• 2001

This paper presents a methodology to extract classes and inheritance relations from procedural software. The methodology is based on the idea of generating all groups of class candidates, based on the combinatorial groups of object candidates, and their inheritance with all possible combinations and selecting a group of object candidates, and their inheritance with all possible combinations and selecting a group with the best or optimal combination of candidates with respect to the degree of relativity and similarity between class candidates in the group and classes in a domain model. The methodology has innovative features in class candidates in the group and classes in a domain model. The methodology has innovative features in class and inheritance extraction: a clustering method based on both static (attribute) and dynamic (method) clustering, the combinatorial cases of grouping class candidate cases based on abstraction, a signature similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement, that is, the horizontal measurement for overall group similarity between n class candidates and m classes, and the vertical measurement for specific similarity between a set of classes in a group of class candidates and a set of classes with the same class hierarchy in a domain model, etc. This methodology provides reengineering experts with a comprehensive and integrated environment to select the best or optimal group of class candidates.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.171-183
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• 2020

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.405-414
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• 2014

This research aims to strengthen the ethical decision-making capability of nursing students, and involves 82 fourth-year undergraduate nursing students in a nonequivalent control group pre-post quasi experimental research design from March 4 to June 3, 2013. Experimental group took a discussion-based class and control group took a traditional lecture-based class and we identified the differences in ethical knowledge, class satisfaction and ethical values between the two groups. Experimental group had higher scores for ethical knowledge after the class. There was no significant change in ethical values after the class in the two groups. The experimental group achieved significantly higher scores for the comprehension of class contents and practical application within the class satisfaction criteria. So we propose to use this model as an effect teaching method to apply ethical principles in nursing practice.

• Journal of Engineering Education Research
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• v.22 no.4
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• pp.71-77
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• 2019

Capstone design is a very important college course that enhances students' creativity and skills. However, in most universities, the operation of capstone design is operated by the experience and intuition of the advisor, and it is somewhat lacking in the generation of useful results such as patent rights and technology start-up from the capstone design result. In this study, we proposed a performance - based capstone design operation model through patent linkage so that the capstone design class can create creative and useful results. The proposed operating model includes support for research on prior art of patent information utilization, patent right of idea, and technology commercialization. The proposed operating model was directly applied to the capstone design class in the university, and it was confirmed that useful results such as expansion of the scope of the research achievement and technology start - up were created compared to the existing operation model.

• Journal of the Korean Wood Science and Technology
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• v.47 no.1
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• pp.101-109
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• 2019

This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.

• The korean journal of orthodontics
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• v.48 no.6
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• pp.349-356
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• 2018

Objective: This study was performed to investigate the alveolar bone of lower incisors in skeletal Class III adults of different vertical facial patterns and to compare it with that of Class I adults using cone-beam computed tomography (CBCT) images. Methods: CBCT images of 90 skeletal Class III and 29 Class I patients were evaluated. Class III subjects were divided by mandibular plane angle: high (SN-MP > $38.0^{\circ}$), normal ($30.0^{\circ}$ < SN-MP < $37.0^{\circ}$), and low (SN-MP < $28.0^{\circ}$) groups. Buccolingual alveolar bone thickness was measured using CBCT images of mandibular incisors at alveolar crest and 3, 6, and 9 mm apical levels. Linear mixed model, Bonferroni post-hoc test, and Pearson correlation analysis were used for statistical significance. Results: Buccolingual alveolar bone in Class III high, normal and low angle subjects was not significantly different at alveolar crest and 3 mm apical level while lingual bone was thicker at 6 and 9 mm apical levels than on buccal side. Class III high angle group had thinner alveolar bone at all levels except at buccal alveolar crest and 9 mm apical level on lingual side compared to the Class I group. Class III high angle group showed thinner alveolar bone than the Class III normal or low angle groups in most regions. Mandibular plane angle showed negative correlations with mandibular anterior alveolar bone thickness. Conclusions: Skeletal Class III subjects with high mandibular plane angles showed thinner mandibular alveolar bone in most areas compared to normal or low angle subjects. Mandibular plane angle was negatively correlated with buccolingual alveolar bone thickness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.677-678
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• 2017

Currently, vocational high schools are trying to learn through project learning and similar courses. This is to nurture talented students who can be directly involved in the industrial field. In this study, we modified the existing ADDIE model, designed the model for the class, and operated the actual augmented reality programming class to verify the validity. As a result of the operation, the learners' satisfaction and achievement were high, and the ability to solve the problem was improved as it was developed in the actual field. In this study, it is meaningful to develop a teaching model closely related to the field through the project learning using the augmented reality programming.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.5
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• pp.31-38
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• 2002

In this paper, we model a two-server queueing system with priority, to which we put a restriction on the number of servers for each customer class. customers are divided into two different classes. Class 1 customers have non-preemptive priority over class 2 customers. They are served by both servers when available but class 2 customers are served only by a designated server. We use a method of generating function depending on the state of servers. We find the generating function of the number of customers in queue, server utilization, mean queue length and mean waiting time for each class of customers.

• Korean Journal of Agricultural Science
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• v.20 no.2
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• pp.221-236
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• 1993

Economic conditions of Korean agriculture have been aggravated since farmers experienced the shortage of labor, instability of farm product price, lack of capital and pressure of opening domestic market. Nevertheless, agriculture must be maintained because structure of national economy can not be progressed without balanced growth of food industry. So the problem that we must solve is to keep agriculture competitive. In that case technology is important in terms of improving productivity, overcoming labor shortage and stabilizing price. This paper is to study the technology adoption on the farm level, focusing on the theories of technology adoption, their empirical test and effect of technology adoption on the farm household income. In this study five theories-independent model, linear model, middle class conservation model, modified middle class conservation model, basic needs and wealfare model- were introduced concerning differentiated technology adoption rate by farmers' class. Based on the survey of controlled strawberry farming in Nonsan County, Chungnam Province, who adopted six kinds of technology, modified middle class conservation model was found to explain five kinds of technology adoption pattern and linear model was useful to explain one kind of technology, that is, irrigation method, These results may mean that controlled strawbary cultivators of middle class were reluctant to accept new technology. There are many variables to effect on the technology accepting rate, that is, farmer's age, labor capacity, education level, cultivation career, size of total cultivated land, and size of strawberry farming land. LOGIT model was used to find which variable influence the technology adoption rate. Results of estimation showed that variables of cultivation career and total land size, of which coefficients were statistically significant at the 5 percent level, might be main influential factors in accepting more than three farming techniques. There was a significant income difference between farm households accepting new methods and those rejecting them. Especially in case of low class of farming group, income of farmers who was adopting new technology was examined to be much higher than that of farmers who did not adopt. This result suggests that new technology play an important role in increasing farm household income. Finally this study emphasized that there is a need to develop proper measure of technology transfer considering various socioeconomic conditions of farm households.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.139-150
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• 2021

Object orientation has become the predominant paradigm for conceptual modeling (e.g., UML), where the notions of class and object form the primitive building blocks of thought. Classes act as templates for objects that have attributes and methods (actions). The modeled systems are not even necessarily software systems: They can be human and artificial systems of many different kinds (e.g., teaching and learning systems). The UML class diagram is described as a central component of model-driven software development. It is the most common diagram in object-oriented models and used to model the static design view of a system. Objects both carry data and execute actions. According to some authorities in modeling, a certain degree of difficulty exists in understanding the semantics of these notions in UML class diagrams. Some researchers claim class diagrams have limited use for conceptual analysis and that they are best used for logical design. Performing conceptual analysis should not concern the ways facts are grouped into structures. Whether a fact will end up in the design as an attribute is not a conceptual issue. UML leads to drilling down into physical design details (e.g., private/public attributes, encapsulated operations, and navigating direction of an association). This paper is a venture to further the understanding of object-orientated concepts as exemplified in UML with the aim of developing a broad comprehension of conceptual modeling fundamentals. Thinging machine (TM) modeling is a new modeling language employed in such an undertaking. TM modeling interlaces structure (components) and actionality where actions infiltrate the attributes as much as the classes. Although space limitations affect some aspects of the class diagram, the concluding assessment of this study reveals the class description is a kind of shorthand for a richer sematic TM construct.