• Journal of Home Health Care Nursing
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• v.12 no.1
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• pp.136-154
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• 2005

Purpose : This study purposed to conduct a comprehensive survey of home care nursing clients' quality of life based on the PRECEDE model. Method : This study selected 74 home care nursing clients registered at a university hospital in Incheon and performed face-to-face interviews by structured questionnaire. The research period was two months from the $2^{nd}$ of February to the $30^{th}$ of March in 2004. Result : According to the result of assessment at each stage of the PRECEDE model, home care nursing clients' quality of life was 13.88 out of 25 points, health level 15.22 out of 21, abilities to perform activities of daily living 29.26 out of 100, cognitive abilities 16.00 out of 30, social support 13.68 out of 20, and satisfaction with home care nursing service 33.26 out of 40. According to the result of stepwise regression in order to identify factors influencing home care nursing clients' quality of life, social support and abilities of daily living were found to be significant variables among the characteristics of each assessment stage. Conclusion : It is necessary to develop nursing intervention strategies for strengthening social support and enhancing abilities to perform activities of daily living in order to improve home nursing clients' quality of life.

• Journal of Korean Society for Quality Management
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• v.39 no.1
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• pp.90-97
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• 2011

The purpose of this study is to analyze various factors comprising a job satisfaction; determine possible factors that affects job satisfaction. Job satisfaction model is designed to evaluate major factors, such as job stress and strength, and to assess relationship between these factors. Partial least squares algorithm is used to develop a job satisfaction measurement model. To evaluate validity of developed model, survey data of health insurance review and assessment service is to applied.

• Journal of Environmental Impact Assessment
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• v.21 no.6
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• pp.841-857
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• 2012

Preliminary ecological environmental assessments including physico-chemical constituents, water quality, fish fauna analysis, physical habitat health, and ecological health assessment were conducted as a primary step for Jeungchon micro-habitat ecosystem restoration in 2012. Water chemistry analysis of conductivity, dissolved oxygen, chlorophyll-a and etc. indicated that there were no significant differences(p < 0.05) among 6 sites between the headwaters and downstream. Multi-metric model analysis of Qualitative Habitat Evaluation Index(QHEI) showed that brooklets were at "good condition" as a mean QHEI of 158.7(n = 6) and the longitudinal differences of the model values between the sites were minor(QHEI range: 153 - 165). Total fish species and the number of individuals were 12 and 481, respectively, and dominant species were Zacco platypus(49.5%) and Zacco koreanus(36.8%). Tolerance guild analysis showed that the proportion of sensitive species($S_S$) had a negative linear function[$S_S=86.35-0.31(D_H)$; $R^2$ = 0.892, p < 0.01] with a distance from the headwaters, while the proportion of tolerant species($T_S$) had a positive linear function($R^2$ = 0.950, F = 90.28, p < 0.001) with the distance. Trophic feeding guild analysis showed that the proportion of insectivore species($I_n$) had a negative linear function($R^2$ = 0.934, p < 0.01) with a distance from the headwaters, while the proportion of omnivore species($O_m$) had a positive linear function($R^2$ = 0.958, p < 0.001) with the distance. Index of Biological Integrity(IBI) model, based on fish assemblages, showed a "fair condition" as a mean IBI of 23(n = 6), and there was a distinct differences of ecological health between the headwaters(S1 = 30; "good condition") and the downstreams(S6 = 14; "poor condition"). Overall, the preliminary environmental impact assessments suggest that water quality, physical habitat conditions(QHEI model), and ecological health(IBI model) were maintained well, even if the state was not an excellent conditions.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.89-95
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• 2008

In this paper, we propose a software reliability growth model based on the superposition cause in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.269-274
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• 2016

In this paper We focuses on suggestion to quality model for IoT infrastructure services for Internet of Things. Quality model is suggested on security set out in ISO25000 quality factors and assessment of the existing traditional software application of ISO 9126 quality model. We validated that the proposed model can be realized it was applied to evaluate the 4 elements and related security in Metrics.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.2
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• pp.251-264
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• 2003

Purpose : The expectations are defined as desired expectations in initial SERVQUAL scale(1985, 1988), but in modified SERVQUAL scale(1991), are defined as a feasible ideal point expectations. In assessment of nursing service quality by SERVQUAL scale, the definitions of expectations is important problem. The purpose of this study was to compare the feasible ideal point expectations with the desired expectations in assessment of nursing service quality using SERVQUAL scale. Methods : The subjects were 256 inpatients at 4 general hospitals in Jeju-do(123 for feasible ideal point and 133 for desired). The data were collected by two types of self-reporting questionnaires to measure the feasible ideal point and desired expectations. For data analysis, t-test, multiple regression, and comparative analysis of multiple Rs via Fishers Z transformation. Results : Compared with the SERVQUAL scores, the feasible ideal point expectations better explained the variations of the overall consumer satisfaction($R^2$=O.33) than the desired($R^2$=O.25). Conclusion : The feasible ideal point expectations were more suitable to the assessment of nursing service quality using SERVQUAL scale. It will be need to explore the conceptual definitions of expectations using SERVQUAL scale in different settings. Also, further study needs to be conducted to compare alternative service quality measurement scales.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.75-86
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• 2022

The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• Journal of Environmental Impact Assessment
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• v.9 no.1
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• pp.25-37
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• 2000

This paper presents a study of hydrological and hydraulic model applications in environmental impact statements which were submitted during recent years in Korea. In many cases (almost 70 %), the hydrological and hydraulic changes were neglected from the impact identification processes, even if the proposed actions would cause significant impacts on those environmental items. In most cases where the hydrological and hydraulic impacts were predicted, simple equations were used as an impact prediction tool. Computer models were used in very few cases(5%). Even in these few cases, models were improperly applied and thus the predicted impacts would not be reliable. The improper applications and the impact neglections are attributed to the fact that there are no available model application guidelines as well as no requirements by the review agency. The effects of mitigation measures were not analyzed in most cases. Again, these can be attributed to no formal guidelines available for impact predictions until now. A brief guideline is presented in this paper. This study suggested that the model application should be required and guided in detail by the review agency. It is also suggested that the hydrological and hydraulic items shoud be integrated with the water quality predictions in future, since the non-point source pollution runoff is based on the hydrologic phenomena and the water quality reactions on the hydraulic nature.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.