• Journal of Korean Academy of Nursing
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• v.7 no.1
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• pp.88-98
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• 1977

This study was designed to identify a more effective method of nursing interview in gathering informations by comparing the two, the structured and unstructured methods. May through October, 1976, 40patients on psychiatric wards of Korea University Hospital and National Mental Hospital, Seoul, were sampled and interviewed on their admission/within one week of admission. Both methods were used simultaneously by different interviewers ; 48 hour interval were kept between the two approaches of interview. Contents of informations gathered were grouped according to the criteria developed by the researcher, frequency, percentile score and the means were scored, and the two methods were compared; the amount of information gathered, number of questions used, time spent and the general response towards the methodologies. Results of the study are summarized as follows ; 1. 1. 5 times as many informations were gathered through the structured interview. (1366 ; 849) 2. 68.32% of informations gathered through the unstructured interview and 42.46% of the structured interview revealed to be overlapping; through structured interview, more unique informations (57.54%) were gathered. 3. The average of 33.25 minutes were consumed for the structured interview while 95, 50 minutes for the unstructured. Much higher time consumption is revealed in the unstructured. 4. Majority of patients showed positive response towards both approaches of interview (90% each), however, interviewers responded to experience of certain degree of tension (stress) in the unstructured method (35%) 5. The average of 0.88 question were used to gather one information in the structured while 1.87questions for the unstructctured were used. 6. The average of 0.97 minutes were consumed to gather one information in the structured while 4.50minutes for the unstructured. 7. The average of 1.11 minutes were consumed for one question for the structured while 2.41 minutes for the unstructured. The results of the study revealed that the structured interview were more effective in gathering informations; a larger quantity of informations were gathered in shorter time. Recommendations for further in investigations are as follows ; 1. Comparative analysis of informations gathered through the two methods by experienced professional nurse- interviewers is recommended. 2. Comparative analysis of the quality of informations is recommended. 3. Comparative analysis of the interviewing process (interactions) in relation to the characteristics of patients'health problems is recommended.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.2
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• pp.83-89
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• 2017

Numerical simulations of ship resistance have been performed to compare spatial characteristics of Courant number when using structured and unstructured meshes. When Euler scheme was used for time integration, the structured mesh provided a more efficient calculation because the calculation time interval was larger than that of unstructured mesh. The automatic generation of very small meshes in the unstructured mesh was mainly responsible for the limitation of calculation time interval. When local time stepping Euler scheme was applied, however, the ship resistance of unstructured mesh showed a rapid convergence while a slow convergence of ship resistance in structured mesh was caused by the small time interval in bulbous bow.

• The Journal of Bigdata
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• v.6 no.2
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• pp.169-179
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• 2021

Consumers' food consumption behavior is likely to be affected not only by structured data such as consumer panel data but also by unstructured data such as mass media and social media. In this study, a deep learning-based consumption prediction model is generated and verified for the fusion data set linking structured data and unstructured data related to food consumption. The results of the study showed that model accuracy was improved when combining structured data and unstructured data. In addition, unstructured data were found to improve model predictability. As a result of using the SHAP technique to identify the importance of variables, it was found that variables related to blog and video data were on the top list and had a positive correlation with the amount of paprika purchased. In addition, according to the experimental results, it was confirmed that the machine learning model showed higher accuracy than the deep learning model and could be an efficient alternative to the existing time series analysis modeling.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.299-300
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• 2006

• Hwankyungkyoyuk
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• v.20 no.2
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• pp.1-15
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• 2007

The Environmental problem solving model is an instructional strategy to accomplish the aim of environmental education through investigation of environmental problems and issues of the community. This study is intended to compare the instructional effect of the structured model with the unstructured model of environmental problem solving. The experimental group received the structured instruction and the control group received the unstructured instruction. There did not appear to be any significant difference between the groups in regard to knowledge but in regard to knowledge of environmental issues, the experimental group was more effective than the control group. No significant differences existed between the groups in attitude. In regard to investigating skill and evaluation of environmental issues, the experimental group was significantly more effective than the control group. The experimental group was significantly more effective than the control group in regard to environmental action skills. To foster responsible environmental behavior, environmental education a number of methodologies must be considered and learners must be trained to become problem-solving citizens. It was noted that the structured instruction was more effective than the unstructured instruction in middle school where environmental issues were not taught as an independent subject. We conclude that environmental education must be systematically constructed and taught in a manner which takes into account both its goals and the characteristics of the various learners. We conclude that environmental education must be systematically constructed and taught in a manner which takes into account both its internal goals and the situations within which various types of learners explore environmental issues and solutions.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.342-348
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• 2004

As the advent of the Internet, B2B negotiation process on the Internet has been given attention from both researchers and practitioners. However, literature still shows that only structured conditions have been explicitly considered, despite the fact that unstructured conditions should be rendered as well. In this sense, this paper proposes a new negotiation support mechanism to incorporate causal relationships between structured and unstructured conditions in the process of B2B negotiation. Fuzzy cognitive map was used as a main source of causal knowledge as well causal inference engine. A prototype named CAKES-NEGO was developed to perform experiments with an illustrative example. Results revealed the robustness of our proposed negotiation support mechanism.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.66-73
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• 2017

Due to the recent rapid changes in society and wide spread of information devices, diverse digital information is utilized in a variety of economic and social analysis. Information related to the crime statistics by type of crime has been used as a major factor in crime. However, statistical analysis using only the structured data has the difficulty in the investigation by providing limited information to investigators and users. In this paper, structured data and unstructured data are analyzed by applying Korean Natural Language Processing (Ko-NLP) and the Latent Semantic Analysis (LSA) technique. It will provide a crime profile optimum system that can be applied to the crime profiling system or statistical analysis.

• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.42-47
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• 1998

The pressure-based methods are very popular in CFD because it requires less computer core memory compared to other coupled or density-based solvers. Currently structured-mesh methodology based on pressure-based algorithm is quite mature to apply to the practical problems. The unstructured mesh method needs much more computer memory than the structured-mesh method. However the pressure-based method utilizing the sequential approach does not require very large memory used for unstructured-mesh density-based solvers. The present study has developed the unstructured grid pressure-based method. Cell-centered finite volume method was selected due to robustness for imposing various boundary conditions and easy implementation of higher-order upwind scheme. The predictive capability of present method has validated against several benchmark problems.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.197-210
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• 2016

With the advent of text analytics, VOC (Voice of Customer) data become an important resource which provides the managers and marketing practitioners with consumer's veiled opinion and requirements. In other words, making relevant use of VOC data potentially improves the customer responsiveness and satisfaction, each of which eventually improves business performance. However, unstructured data set such as customers' complaints in VOC data have seldom used in marketing practices such as predicting service time as an index of service quality. Because the VOC data which contains unstructured data is too complicated form. Also that needs convert unstructured data from structure data which difficult process. Hence, this study aims to propose a prediction model to improve the estimation accuracy of the level of customer satisfaction by combining unstructured from textmining with structured data features in VOC. Also the relationship between the unstructured, structured data and service processing time through the regression analysis. Text mining techniques, sentiment analysis, keyword extraction, classification algorithms, decision tree and multiple regression are considered and compared. For the experiment, we used actual VOC data in a company.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.67-73
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• 2018

Researchers have increased their interest in effectively managing the disaster that appear in large scale and complex form. There are two types of disaster information, which are unstructured text data and structured data. Unstructured text data usually refers to text documents that have been referenced by disaster management personnel such as disaster manuals and related regulations, while structured data refers to various disaster information build in the disaster related organization system. This paper proposes a methodology of constructing a disaster information sharing system that enables joint use of disaster related organizations through the establishment of a mutual linkage system by utilizing both unstructured and structured form of disaster information. Especially, Based on the linkage information between structured earthquake information in earthquake related system and earthquake manuals and countermeasures against earthquake disaster, we propose a service that provides the necessary information for earthquake management. It is expected that the task manager will perform effective earthquake state management by acquiring the integrated structured and unstructured earthquake information of the ministries and related organizations.