• Research in Community and Public Health Nursing
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• v.13 no.4
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• pp.767-777
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• 2002

The purpose of this study was to construct a grounded theory as the basis for developing future nursing interventions by describing and analyzing the holistic lives of the physically handicapped adolescents. The subjects were 10 physically handicapped adolescents who were attending a rehabilitation school located in Kyunggi region and could understand and respond to the questions. The aim and purpose of the study were explained to the subjects, and only those who accepted to participate in the study were selected as the actual study subjects. The study data were collected from July to November 2000. The investigators provided detailed explanations to the subjects about keeping the anonymity of the subjects name and confidentiality of the information provided by the study subjects. The subjects received in-depth interviews by the investigators. Each interview took about 40 minutes to 1 hour and 30 minutes, and each subject received interviews with the range of one to 3 times. All interviews were recorded under the permission of the subjects. The investigators formed field notes after finishing each interview. In the process of data analysis, 'realizing the difficulty due to physical handicap' was found to be the causal condition, whereas' acceptance of physical handicap' was identified as the context. Then, we identified' awaring as the valuable being' as the core phenomenon, 'support from family and social group and spiritual help' as the intervening condition, 'effort for adaptation' as the strategy, and' finding the meaning of life' as the consequence. Through the theoretical model derived from this study, an important aspect the lives of physically handicapped adolescences was identified that' awaring as the valuable being' help them cope better and find the meaning of life in spite of suffering they experience.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.190-204
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• 2008

Recently, it has been strongly required to establish a systematic and sustainable performance investigation and evaluation framework on governmental funding projects for IT small and medium-sized enterprises. In this paper, Data Envelopment Analysis (DEA) models are adopted for performance evaluation on governmental funding projects for IT small and medium-sized enterprises. A new data structure is proposed for the DEA performance evaluation. Generally, in using DEA models, DEA multipliers restriction is critical to achieve the reliability of DEA optimal solutions. Based on the outputs and inputs considered in this study, Acceptance Region (AR) constraints are generated and incorporated into the DEA models so as to improve the reliability of DEA efficiency scores. Associated with AR Type I (AR-I), AR Global Model (ARGM) constraints, DEA/ (AR-I, ARGM) models are designed and then sensitivity analysis follows investigating the robustness of DEA efficiency scores relating to AR constraints adjustment. Finally, a performance evaluation is illustrated regarding governmental direct funding projects from Ministry of Information and Communication (MIC) in Korea where each project unit (i.e. Decision Making Unit (DMU)) is determined whether it is efficient or not. By using DEA/(AR-I, ARGM) models designed in this paper, robustly efficient DMUs are gradually identified according to the successive AR constraints adjustment. Among 25 DMUs, results show that 6 DMUs such as B, E, G, Q, S, Y are determined as robustly efficient against AR constraints intermediate adjustment.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.153-162
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• 2004

Software development methodology using object-oriented analysis and design techniques for improving productivity and maintainability has acquired a substantial acceptance in both academia and industry as a fundamental paradigm. Enterprise Java Beans (EJB) is widely used in both academia and industry because it provides high unability and rapid application development. EJB supports object-oriented paradigm, but there are several things to consider when designing detail model of object-oriented model or implementing object-oriented model with EJB model. One of them is inheritance problem. In this paper, we classify the types of class inheritance which is shown upon in object-oriented model into three types and identify the problems which can happen when implementing the inheritance mechanism with EJB model. And this paper proposes three patterns for realizing the inheritance in EJB. Moreover, applicable patterns and guidelines for each object-oriented inheritance types for the proposed patterns are suggested.

• Journal of Information Technology Services
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• v.19 no.1
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• pp.103-112
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• 2020

Job seekers are making various efforts to find a good company and companies attempt to recruit good people. Job search activities through self-introduction essay are nowadays one of the most active processes. Companies spend time and cost to reviewing all of the numerous self-introduction essays of job seekers. Job seekers are also worried about the possibility of acceptance of their self-introduction essays by companies. This research builds a classification model and conducted an experiments to classify self-introduction essays into pass or fail using deep learning and decision tree techniques. Real world data were classified using stratified sampling to alleviate the data imbalance problem between passed self-introduction essays and failed essays. Documents were embedded using Doc2Vec method developed from existing Word2Vec, and they were classified using logistic regression analysis. The decision tree model was chosen as a benchmark model, and K-fold cross-validation was conducted for the performance evaluation. As a result of several experiments, the area under curve (AUC) value of PV-DM results better than that of other models of Doc2Vec, i.e., PV-DBOW and Concatenate. Furthmore PV-DM classifies passed essays as well as failed essays, while PV_DBOW can not classify passed essays even though it classifies well failed essays. In addition, the classification performance of the logistic regression model embedded using the PV-DM model is better than the decision tree-based classification model. The implication of the experimental results is that company can reduce the cost of recruiting good d job seekers. In addition, our suggested model can help job candidates for pre-evaluating their self-introduction essays.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.43-53
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• 2004

Component-based development(CBD) has acquired a substantial acceptance in both academia and industry as an effective inter-organizational reuse technology. A component framework in product line engineering(PLE) which consists of related components, connectors and their semantics has a greater potential for reusability than components. In frameworks, components are glued with association, dependency and connections. Problems occur like affecting the implementation code of components when they are glued and replaced because the association and dependency relationships between COTS components which are acquired for application development do not match exactly. Especially, a connector may not only connect related components, but also mate partially-matched COTS components fit together. However, little has been studied to date about connectors that can be used practically. In this paper, we present a meta-model for connectors and show how a connector can be designed and implemented in practice. We propose five main patterns of connectors. Proposed major patterns Provide design guidelines for practical and efficient connector configuration based on component framework. And also, applying techniques and applied case studies of the major patterns show greatly increased applicability and reusability of the component without component modification.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.143-153
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• 2014

The purpose of this study is to investigate the effect of factors related to consumer lifestyle and media usage on the adoption of Nscreen service, which is fundamentally changing both the competitive landscape for business and the daily lives of consumers. The data of 8,524 consumers used in this study were drawn from the first Korea Media Panel Study in 2012 of Korea Information Society Development Institute and the characteristics of adopters and non-adopters were compared. The study also aims to explore the usage pattern of Nscreen as well as antecedent variables that affect the innovative service usage. Logistic regression analysis shows various factors affects the acceptance of this innovation. This is only a first step in the important process of understanding the nature of relationship between consumer lifestyle and the adoption of Nscreen service. Gaining a comprehensive understanding of the drivers of Nscreen usage will help engineers and marketers to develop effective strategies that meet consumer needs for innovative services.

• Journal of Satellite, Information and Communications
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• v.1 no.2
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• pp.56-62
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• 2006

This paper describes the MMIC product qualification of the Ka band satellite transponder for the COMS(Communication, Ocean and Meteorological Satellite). Ka-band active equipment for the COMS communications transponder are being developed by using 12 kinds of MMICs which include low noise amplifiers, medium power amplifiers, frequency mixers, frequency multipliers, RF switch, and HEMT attenuator MMIC, Those MMICs had been fabricated at the MMIC production foundry of northrop Grumman Space Technology (Velocium) which is qualified for space application, and experienced in various space programs during past decades. For the MMIC product qualification, Visual inspection and SEM inspection had been performed, and burn-in test for 240 hours and accelerated life-test for 1000 hours had been done on test fixtures of individual MMIC products at $125^{\circ}C$. Additionally, infrared temperature scanning and finite element simulation were performed to analyze and confirm the channel temperature of semiconductor devices on several representatives of those MMIC products that os one of the most important factors in performance degradation and life reduction.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2587-2592
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• 2012

Background: Limited human papillomavirus (HPV) related knowledge might be a barrier to future vaccine acceptance. From 2008-2010, PATH conducted an HPV vaccination demonstration project in partnership with the government immunization program in Vietnam, which included awareness campaigns prior to vaccination. Objective: To assess and compare knowledge and attitudes about cervical cancer and HPV vaccines between mothers and daughters, and whether knowledge was associated with vaccination status. Methods: We analyzed HPV-related knowledge and attitude data from mother-daughter paired responses to a cross-sectional household survey. After parents completed the survey, daughters were asked the same questions. We calculated the frequency of responses for each question and devised a scaled composite measure for knowledge. Results: Participants believed they had received enough information about cervical cancer and HPV vaccines and it was sufficient to make a decision about vaccination. Fifty percent of the participants knew HPV causes cervical cancer and 80% knew the HPV vaccine prevented cervical cancer. Mothers had more knowledge about cervical cancer and HPV infection (p<0.01), compared to daughters, who had more vaccine specific knowledge (p<0.01). However, the total mean knowledge score was similar for the groups. Girls not fully vaccinated had a lower mean knowledge score than fully vaccinated girls (p<0.001). Conclusions: Our results suggest that the purpose of the HPV vaccine was clearly messaged; however, some misconceptions about cervical cancer and HPV still exist. Limited knowledge about the magnitude of cervical cancer, HPV as a cause of cervical cancer, and HPV vaccines may have contributed to incomplete vaccination.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.591-600
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• 2016

Computing technologies are increasingly applied to most casual human environment networks, as computing technologies are further developed. In addition, the rapidly increasing interest in IoT has led to the wide acceptance of speech recognition as a means of HCI. In this study, we present a novel method for recognizing the Korean vowel 'ㅜ', as a part of a phoneme based Korean speech recognition system. The proposed method involves analyses of bulk indicators calculated in the time domain instead of analysis in the frequency domain, with consequent reduction in the computational cost. Four elementary algorithms for detecting typical waveform patterns of 'ㅜ' using bulk indicators are presented and combined to make final decisions. The experimental results show that the proposed method can achieve 90.1% recognition accuracy, and recognition speed of 0.68 msec per syllable.