• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.142-150
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• 2024

A conceptual model represents an understanding of a system that is going to be developed, which in this research, a driving simulation software to study driver behavior at signalised intersections. Therefore, video observation was conducted to study driver compliance behaviour within the dilemma zone at signalised intersection, with regards to driver's distance from the stop line during yellow light interval. The video was analysed using Thematic Analysis and the data extracted from it was analysed using Chi-Square Independent Test. The Thematic Analysis revealed two major themes which were traffic situation and driver compliance behaviour. Traffic situation is defined as traffic surrounding the driver, such as no car in front and behind, car in front, and car behind. Meanwhile, the Chi-Square Test result indicates that within the dilemma zone, there was a significant relationship between driver compliance behaviour and driver's distance from the stop line during yellow light interval. The closer the drivers were to the stop line, the more likely they were going to comply. In contrast, drivers showed higher non-compliant behavior when further away from stop line. This finding could help in the development of conceptual model of driving simulation with purpose in studying driver behavior.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.155-162
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• 2021

The expansion of the world wide web has led to a huge amount of user generated content over different forums and social media platforms, these rich data resources offer the opportunity to reflect, and track changing public sentiments and help to develop proactive reactions strategies for decision and policy makers. Analysis of public emotions and opinions towards events and sentimental trends can help to address unforeseen areas of public concerns. The need of developing systems to analyze these sentiments and the topics behind them has emerged tremendously. While most existing works reported in the literature have been carried out in English, this paper, in contrast, aims to review recent research works in Arabic language in the field of thematic sentiment analysis and which techniques they have utilized to accomplish this task. The findings show that the prevailing techniques in Arabic topic-based sentiment analysis are based on traditional approaches and machine learning methods. In addition, it has been found that considerably limited recent studies have utilized deep learning approaches to build high performance models.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.725-734
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• 2003

In this paper, we propose the text summarization method using PCA (Principal Component Analysis) and SVD (Singular Value Decomposition). The proposed method presents a summary by extracting significant sentences based on the distances between thematic words and sentences. To extract thematic words, we use both word frequency and co-occurence information that result from performing PCA. To extract significant sentences, we exploit Euclidean distances between thematic word vectors and sentence vectors that result from carrying out SVD. Experimental results using newspaper articles show that the proposed method is superior to the method using either word frequency or only PCA.

• Spatial Information Research
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• v.10 no.2
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• pp.331-343
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• 2002

Recently, as various fields of applications using space-borne imagery have been emphasized, interests on integrated analysis or fusion using multi-sources are also increasing. In this study, to investigate applicability of multiple imageries for further regional-scaled application, DN value analysis and multi-resolution classification by using KOMPSAT EOC imagery and Landsat 7 ETM+image data in the Namyangju-city area were performed, and then this classified results were compared to land-use thematic data at the same area. In case of classified results by using muff-resolution image data, it is shown that linear-type features can be easily extracted. furthermore, it is expected that multi-resolution classified image can be effectively utilized to urban environment analysis, according to results of similar pattern by comparative study based on multi-buffered zone analysis or so-called distance analysis along main road features in the study area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.357-366
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• 2016

This study analyzed the strengths and weaknesses for enneagram types 3, 6 and 9, which are the center types among the different centers of intelligence, in order to provide college students with meaningful knowledge that can improve their self-understanding. To conduct this study, thematic analysis was used to discover the strength and weakness keywords using NodeXL and contents analysis was used for the case analysis of types 3, 6, and 9. The results showed that the strengths were objectiveness and confidence for type 3, responsibility and premeditation for type 6 and pacifism and consideration for type 9. The weaknesses were self-consciousness and consequentialism for type 3, indecision and worry for type 6, and evading conflict and laziness for type 9. The results obtained by contents analysis showed that type 3 was goal-oriented and placed value on gaining the recognition of other people, type 6 had a sense of responsibility and was well prepared beforehand, and type 9 was considerate of others's feelings and evaded conflicts. This can help college students to better understand themselves.

• Cross-Cultural Studies
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• v.23
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• pp.321-349
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• 2011

The purpose of this study is to examine slangs used in contemporary Russian. In any kind of social group, there are special jargons used to satisfy special needs of verbal communication and express individual affiliation compared with neighboring parties, apart from standard languages popularized in each society. Some of these jargons belong to a category of common usual language, while others are temporarily popularized but disappear. It is undeniable that these languages are a product of our social language phenomena in addition to the presence of standard language. Thus, it is very essential to investigate and understand these linguistic phenomena as well as standard languages. In this study, Chapter 1 examines the definition of slang as one of most important topic with a view to achieve desired goals hereof. Next, Chapter 2 sets the scope of subjects for this study. Chapter 3 subdivides subjects into each group by topic for analysis within the scope as set in the previous chapter. This analysis gives a basis on which we can understand linguistic phenomena and identify any psychological conditions of people who use languages. This study comes to its conclusions with summary of findings from data collection and analysis.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.661-670
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• 2018

This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.626-637
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• 2021

This study was conducted to describe the image of nurses in the context of COVID-19 pandemic by reviewing newspaper articles (n=451) from 11 major domestic daily newspapers. Analysis of monthly prevalence, favorability towards nurses, proportion of nurse coverage, and thematic analysis was conducted. Five themes and 9 sub-themes were derived from thematic analysis, and major themes are as follows: "Poor work environment"; "Nursing, 'The job of calling'"; "Prominent as a medical profession"; "Strict standards"; and "Expanding the realm of nursing" in order of frequency. In conclusion, media is still reporting a limited role of nurses. Therefore, in order to widen public perspective towards nurses, further academic activities that highlight various roles and positive aspects of nursing profession are needed.

• Journal of Engineering Education Research
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• v.21 no.1
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• pp.14-26
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• 2018

The goal of this study was to explore topic defining patterns of students in interdisciplinary Capstone Design Class. Thematic analysis methodology was used to examine 85 Korean college students' lived experience of project topic generation which is for interdisciplinary capstone design class and Individual open-ended survey for constituted the data sources. Findings show four contexts of student's topic defining patterns using thematic analysis including (a) one leader's directed problem representation, (b) team common decision making after brainstorming, (c) empathy with professor proposed issue, (d) problems offered to students by corporate or research competitions. Based on research result, I could suggest instructional strategies of Capstone Design Class of teacher for helping their students' topic defining. It was necessary to minimize the opinions of the instructors at the beginning of class and minimize the number of team members. And also it provided a lot of opportunities to collaborate with companies in the topic selection process, it will help to develop the students' ability to determine the valuable topic in project.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.35-43
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• 2003

Currently, the government has been driving numerous projects to build the e-government which can enable limitless access and utilization of the information through the accomplishment of the real time based various administrative services. In water resource field, a project to generate digital river thematic maps has been undergoing as a part of the computerization projects. As a partial results, the RIMGIS project has been completed and generation of the various river thematic maps has been required to fully utilize the DB built from RIMGIS project. For the effective generation of the thematic maps, a data model needs to be developed. A data model has been developed in this study to provide more efficient method to generate the thematic maps utilizing existing DB. The data model proposed from this study has defined the relationships between core feature data and framework Data along with relationships among data elements to represent the rivers in the real world more accurately. The core feature data and framework layers have been defined based on the survey of the domestic and foreign case studies along with requirement analysis of the users in the water resource field. The proposed core feature data has been defined based on the minimum unit of 'class', and the relationship between classes has been established based on the ArcGIS Hydro Data Model for the integrated processing of the river information. The proposed spatial data model can be judged to contribute establishing more efficient generation methodology of the river thematic maps.