• Asia pacific journal of information systems
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• v.10 no.2
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• pp.71-95
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• 2000

Despite repeated exhortation about the importance of social and human dimensions of systems development, socio-organizational issues continue to be neglected and ignored in the current information systems practice. A review of the human information processing literature suggests that the reasons for this continuing lack of attention to social issues may be found in the limitations of human cognition and information processing capacities. Bostrom and Heinen(1978) and Kumar and Bjorn-Anderson(1990) also suggest that the inadequate attention to social problems and issues by the analyst could originate from the analysts limited problem perception. This research explores how the representation forms of information systems(IS) methodology used in understanding and modeling the problem situation affect such systems development problem perception. Typically, a system development methodology prescribes the use of system models(i.e., system representations) to understand, analyze, evaluate, and design the information system. Given the size and complexity of information systems, and the abstraction and simplification underlying the modeling process, system representations usually depict only a limited set of aspects of the system. Thus, a methodology whose representations are limited to technical aspects will tend to limit the analyst's perspective to a technical one only(Kumar & Welke, 1990). Following the same line of argument, in contrast, it is the conjecture of this study that a methodology which specifies both social and technical aspects of IS development will help the analyst develop a more comprehensive view of the IS problem domain. Based on the above concept, a theoretical model was first developed which explained the systems analysts cognitive process. Drawing on this model, a research model was developed hypothesizing the impacts of representation forms on problem identification. The model was tested using a laboratory experiment with 70 individual subjects. A special computer software was developed with a hypermedia authoring tool to conduct the experiments in order to avoid experimenter biases and to maintain consistency in administrating repeated experiments. The program, designed to replace the experimenter, consisted of functions such as presenting the subjects with problem material, asking the subjects questions, and saving the typed answers of the subjects. The results indicate that representation forms strongly influence problem identification. It was found that the use of the socio-technical representation form led to the findings of more social problems than the use of technical representation form. The results imply significant effects of representation forms on problem findings and also suggest that the use of adequate representation forms may help overcome dysfunctional effects of our limited information processing capacity.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.713-733
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• 2016

Purpose: The primary objective of this case study is to establish a COQ(Cost of Quality) management system for power generation industries. Key topics of this study include collecting COQ elements, their classifications, COQ computation formula, and determining COQ improvement projects. Results: A comprehensive set of COQ elements have been isolated for electric power generation companies. The COQ elements were classified in such a way that they could be managed according to the PAF model as well as the SIPOC diagram. This study showed that a systematic approach could be established for monitoring the COQ elements and using them in the process of improving quality competitiveness. Methods: The PAF(Prevention-Appraisal-Failure) model has been employed in the process of collecting COQ elements for a power generation company. All the cost of quality elements were first examined through an extensive review of articles and books in the field of quality. The cost elements were then refined and augmented by conducting a comparative study with international standards. The COQ elements have been verified by a group of quality managers and classified according to both the PAF model and the SIPOC diagram for better understanding in the entire organization. An improvement strategy has been also proposed by using a typical COQ level of power generation companies. Conclusion: The conventional PAF model was used in establishing a COQ management system for power generation industries. This case study illustrates the procedure about identification, classification and computation of quality costs, including selection of improvement projects. The system can be used not only for observing the current state of cost elements related to quality, but also for planning an improvement strategy using the ratio of cost classification.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1708-1717
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• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.127-137
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• 2002

This study aims at developing and empirically testing a comprehensive model of organizational justice derived from the prior empirical studies on organizational justice. The study seeks to understand the antecedents to and the consequences are addressed. The first question is what characteristics of the HRM systems determine the levels of perceived distributive and procedural justice. Hypotheses are derived from the two prominent theoretical models, i.e., the self-interests model (SIM) and the group value model (GVM). Those factors include neutrality, consistency, accuracy. ethicality. credibility. and reciprocity in the processes of making HRM decisions. All nine factors suggested by the two models aye adopted for this study as major determinants of both distributive and procedural justice. The second question of this study is related to the moderating effects of individual differences on the relationship between the SIM and GVM variables and perceived distributive and procedural justice in organizational contexts. The final research question deals with the consequences of perceived organizational justice. specifically job - related altitudes and organizational commitment. Job-related attitudes in this study refer to job satisfaction, job motivation, and job involvement, i.e., the willingness to make contributions. identification with organization, and intent to stay. In examining the consequences of perceived organizational justice, the study focuses on the interaction effects of procedural and distributive justice on the above nine outcome variables. The results show that both SIM and GVM variables significantly influence distributive and procedural justice. However, hierarchical regression analyses reveal that the GVM variables except more influence has been focused on the consequences of perceived distributive justice with regard to outcomes provided by the organization.

• Research in Community and Public Health Nursing
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• v.21 no.3
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• pp.341-350
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• 2010

Purpose: The purpose of this study was to contribute to enhancing elementary school health teachers professional job performance by analyzing their job identity and job stress. Methods: The participants were 138 elementary school health teachers registered at the Busan Metropolitan City Office of Education, and the survey was conducted from the 22nd to 23rd of July, 2010. The collected data were analyzed by percentile, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple regression using the SPSS/WIN 17.0 program. Results: The average percentiles of job identity and job stress were 70.6 and 64.0 respectively. Among the sub-factors of job identity, autonomy was highest as 73.5, and among the sub-factors of job stress, job demand was highest as 73.9. There were significant differences in the degree of job identity and job stress according to education status, the number of classes, job satisfaction, enthusiasm for work, and the image of nursing teachers expressed in a word. The regression model explained 21.2% of the variance of job identity. job stress explained 32.0% of the variance. Conclusion: It is important to develop various comprehensive programs for improving job identity and managing job stress. In addition, it is necessary to provide support systems including persons, promotion and rewards to school health teachers.

• Industry Promotion Research
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• v.8 no.3
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• pp.201-210
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• 2023

This study is based on data ecology theory and takes Chinese local governments' open public data as the research object. Data asset value assessment methods are compared from a new perspective of data business operations. The results show that the assessment model constructed using the hierarchical analysis method (AHP) can more objectively reflect the commercial value of government open data assets than the traditional cost, revenue and market methods, has the advantage of a comprehensive assessment of data value index, and better reflects the findings of a comprehensive index of regional data value. The data show that the local government data value assessment index is positively proportional to the region's digital economy development index, highlighting the driving effect on the digital economy. The results of the study provide a good help for the identification of local government data value rights. The research and practice of promoting the construction of data innovation and data business operation models, improving social well-being and promoting the rapid development of the digital economy to achieve data realisation provides a good reference.

• Analytical Science and Technology
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• v.13 no.1
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• pp.101-107
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• 2000

The automotive paints could be generally differentiated by color, layer sequence and chemistry of the paint layers comprising each of the topcoat and the primer system. The successful identification of hit-andrun a and traffic accidental vehicles from evidential paint fiagments is greatly facilitated with a comprehensive laboratory collection of reference paint samples and the technique for direct analysis without sample preparation. The Pyrolysis-Gas Chromatography(PGC) is a precise and reliable method for performing both quantitative and qualitative analysis of polymeric materials and forensic samples. Our Forensic Laboratory is conducting the examination and identification of 73 reference paint samples; 4 colors of each domestic automotive make that is popular in Korea, by Curie Point Pyrolyzer(JHP-3) and GC with capillary column(ultra alloy-5). This method can be used not only to compare paint traces with their suspected sources, but also to identify the type, make and model of the automotive car.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.33-38
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• 2016

Understanding of current features of collapsed buildings, terrain, and other infrastructures is a critical issue for disaster site managers. On the other hand, a comprehensive site investigation of current location of survivors buried under the remains of a building is a difficult task for disaster managers due to the difficulties in acquiring the various information on the disaster sites. To overcome these circumstances, such as large disaster sites and limited capability of rescue workers, this study makes use of a drone (unmanned aerial vehicle) to effectively obtain current image data from large disaster areas. The framework of 3D model reconstruction of disaster sites using aerial imagery acquired by drones was also presented. The proposed methodology is expected to assist fire fighters and workers on disaster sites in making a rapid and accurate identification of the survivors under collapsed buildings.

• Journal of Gifted/Talented Education
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• v.24 no.5
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• pp.851-876
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• 2014

As an empirical test of a model of giftedness with learning disabilities (Song & Porath, 2011), this paper investigated domain thoughts of gifted students without learning disabilities and gifted students with learning disabilities (GLD) in reading, writing, and math. Gifted students in each group were interviewed and the data were analyzed for domain thoughts. The results showed that the former group of gifted students exhibited domain thoughts in a more balanced manner, whereas GLD students showed large discrepancies between domain thoughts; they showed weak specific domain thoughts in contrast to strong other domain thoughts. They also showed ambivalent attitudes even in a domain activity; they presented positive and negative thoughts at the same time. With a comprehensive explanation of the differences between the two groups of gifted students through a cognitive mechanism presented in the model of GLD model, this paper provides new approaches for identification and education of gifted students and GLD students.