• Journal of Korean Elementary Science Education
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• v.23 no.1
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• pp.37-43
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• 2004

In this study, we investigated the effects of using concept mapping as an instructional tool on 4th graders' achievement, science learning motivation, and attitude toward science classes. Two classes (38 students) from an elementary school were respectively assigned to a control group and a treatment group. Students were taught about "expansion of matter by heat" and "heat transfer". These topics were chosen because they require students to understand more concepts as well as relationships among them. A science learning motivation test and an attitude toward science classes test were administered as pretests. A researcher-made achievement test, the science learning motivation test, and the attitude toward science classes test were administered as posttests. The results indicated that using concept mapping in 4th-grade science classes was not significantly effective in improving students' achievement though a statistically significant positive effect was found in the subcategory of knowledge. No statistically significant effect of using concept mapping was found in the scores of the science learning motivation test and the attitude toward science classes test. Educational implications are discussed.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.163-178
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• 2005

The ultimate objective of Personal Information Management (PIM) is to collect, handle and manage wanted information in a systematic way that enables individuals to search the information more easily and effectively, However, existing personal information management systems are usually based on a traditional hierarchical directory model for storing information, limiting effective organization and retrieval of information as well as providing less support in search by associative interrelationship between objects (documents) and their attributes, To improve these problems, in this paper we propose a personal information management model based on the concept lattice of Formal Concept Analysis (FCA) to easily build and maintain individuals' own information on the Web, The proposed system can overcome the limitations of the traditional hierarchy approach as well as supporting search of other useful information by the inter-relationships between objects and their attributes in the concept lattice of FCA beyond a narrow search.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8738-8744
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• 2015

This study was conducted to identify the relationships among critical thinking disposition, professional self-concept and satisfaction of clinical practice in nursing students. The participants were 212 nursing students in Gyeonggy Province. Data was collected from June 1 to 12, 2015 using self-report questionnaires and analyzed through descriptive statistics, t-test, ANOVA and Pearson correlation coefficient with SPSS/win. 21.0. Critical thinking disposition, professional self-concept and satisfaction of clinical practice averaged 3.61(out of 5), 2.94(4), and 3.54(5), respectively. Significant positive correlations between critical thinking disposition and professional self-concept, satisfaction of clinical practice and professional self-concept were found, Therefore it is necessary to strengthen critical thinking and professional self-concept and improve satisfaction of clinical practice through effective educational program.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.549-554
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• 2016

ConceptNet is a common sense knowledge base which is formed in a semantic graph whose nodes represent concepts and edges show relationships between concepts. As it is difficult to make knowledge base integrity, a knowledge base often suffers from incompleteness problem. Therefore the quality of reasoning performed over such knowledge bases is sometimes unreliable. This work presents neural tensor networks which can alleviate the problem of knowledge bases incompleteness by reasoning new assertions and adding them into ConceptNet. The neural tensor networks are trained with a collection of assertions extracted from ConceptNet. The input of the networks is two concepts, and the output is the confidence score, telling how possible the connection between two concepts is under a specified relationship. The neural tensor networks can expand the usefulness of ConceptNet by increasing the degree of nodes. The accuracy of the neural tensor networks is 87.7% on testing data set. Also the neural tensor networks can predict a new assertion which does not exist in ConceptNet with an accuracy 85.01%.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.147-156
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• 2019

This study was conducted to understand the relationship among self-efficacy, career identity and professional self-concept of nursing students. Data were collected from 175 nursing students in the 3rd and 4th grades of the nursing students by questionnaire method. The analysis method was stepwise multiple regression. It revealed professional self-concept was statistically significant according to gender, health status, interpersonal relationships, satisfaction on university life, satisfaction on major and perceptive academic achievements and self-efficacy, career identity and satisfaction on major to be significant predictors of professional self-concept. These variables accounted for 56.4% of professional self-concept. Therefore, it is necessary to strengthen the professional self-concept of nursing students by implementing a gradual intervention program that can improve the self-efficacy, career identity and satisfaction on major from the freshman period.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.2
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• pp.1-13
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• 2014

Put Abstract text here. Recently, the Korea industry need systems engineering technology more than yesterday. The systems engineering management function is needed to use the systems engineering engine process effectively. The systems engineering management function is overlapped a lot with project management function and has vague interface. The project management and systems engineering are two independent disciplines. So there are few references which address the scope and relationships clearly between systems engineering management and project management. This paper suggest the scope and relationships between systems engineering management and project management and revise the PMP and SEMP structure of Blanchard and Fabrycky. Followings are the key concept of this paper presenting. The project management(PM) composed of technical management and non-technical management. The technical management scope is same with systems engineering management. The non-technical management scope is composed of parts of enterprise support processes.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.238-246
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• 1999

The modeling method to support product development processes (PDP) must have certain characteristics including the ability to represent multiple viewpoints of the product development and integrate with currently available analysis and design methods based on CE concept. This paper describes the reference model to support multiple viewpoints (PPO: Products, Processes, and Organizations/Resources viewpoints) of the product development processes, from which each model (Products model, Processes model, and Organizations/Resources model) can be extracted, as well as produces PPO data schema. This reference model has associative relationships among the products, processes, and organizations/resources. To allow the extensibility to support design evolution, we propose structured dat representation methods using semantic network, which can be constructed through first-order logic. The product development processes is so represented by specifying entities and semantic relationships among them hat he appropriate information can be accessed and all of the relevant attributes about the entities can be retrieved simultaneously.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04a
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• pp.3-8
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• 1998

This research is to examine the relationships between viscosity and fluidity according to binders in the super flowing concrete. And this research is described with respect to rheology concept, confined water ratio($\beta_p$) of binders in paste and mortar, also investigated experimentally the relationships between the relative flowing ratio ($\Gamma_m$) and the funneling velocity ratio($R_m$) on the mortar state according to the water binder ratio(W/B) and the dosage of the superplasticizer. From the confined water ratio tests, it is found that $\beta_p$ of the class C fly ash is higher than that of the class F fly and limestone in paste and mortar, therefore class F fly ash and limestone and super flowing concrete. The result of test, the optimum mix condition to the compactibility if satisfied when the replacement ratio is 30% and $K_p$ is 0.8 for the case of fly ash and limestone.

• Korean Journal of Child Studies
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• v.28 no.2
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• pp.39-53
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• 2007

This study investigated the relationship between young children's comprehension and story making(narrative) by age and gender. Subjects were 109 3-, 4-, and 5-year-olds at two child care centers in K Province. Data were analyzed by two-way ANOVA and simple regression analysis. Results showed differences in comprehension between 3-, 4- and 5-year old children and differences in story making ability between 3- and 5-year-old children. Children's comprehension and story making had positive relationships. Specifically, there were significant relationships with children's comprehension and story construct concept, sentence structure level, language(vocabulary and sentence structure). In sum, the results of this study reveal that young children's comprehension ability is partially related to story making ability by age.