• Journal of Korean Home Economics Education Association
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• v.19 no.3
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• pp.149-168
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• 2007

The purpose of this study was to analyze the home economics education items in the teacher recruitment examination for secondary school. To achieve the purpose, all the home economics education items, which were carried out for seven times from the school year 2001 to the most recent year 2007, were compared and analyzed. The form of items was analyzed by frequency and rate. Behavioral domain of items was analyzed by content analysis. In this study, some recommendations were suggested for the quality of home economics education items through discussion of science education and society education items, which were abstracted from the school year 2001 to the most recent year 2007. The results of this study were as follows. First, the score ratio of home economics education items was fluid as 20-30% from the school year 2001 to 2004 but it fixed as 30-35% since the school year 2005. In subcategory of home economics education, curriculum items accounted for highest ratio(43%). In the next thing, items of teaching-learning method(35%), evaluation(19%) and philosophy(3%) related to home economics education were followed in order. Second, the form of home economics education items was coexistent form of single item and subordinate item from the school year 2001 to 2004. But it was changed into form of single item by 100% since the school year 2005. Third, regarding the content of home economics education items, most of the curriculum items were related to the content of the 7th National Curriculum. Teaching-learning method items were taken mostly from model of teaching-learning. Evaluation items were taken mostly from performance assessment. Philosophy items related to home economics education were taken only from Habermas's three systems of action on the school year 2005. Fourth, about behavioral domain of home economics education items, most of the curriculum items were level of 'simple knowledge or memory'. Therefore, it was suggested that behavioral domain of curriculum items had to be changed into 'complex knowledge or comprehension and application'. The behavioral domain of teaching-learning method items and education evaluation items was mostly 'complex knowledge or comprehension and application'. However, to bettering the items it was suggested that the behavioral domain of them has to be changed 'comprehension' into more 'application'. Fifth, regarding the coverage of home economics education items, curriculum items were limited only superficial content of the 7th National Curriculum. Therefore, it was suggested that coverage of curriculum items had to be extended to theoretical content, which was philosophical background and various principles of curriculum. It was suggested that coverage of teaching-learning method items had to be extended to the content including various teaching-learning theories and the practical reasoning home economics instruction proved effective as home economics instruction recently. Evaluation items were taken mostly from performance assessment. Therefore, it was suggested that coverage of evaluation items had to be extended to analysis of evaluation result, item validity and reliability, and evaluator's philosophical perspective.

• Radiation Oncology Journal
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• v.26 no.4
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• pp.237-246
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• 2008

Purpose: Three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) were found to reduce the incidence of acute and late rectal toxicity compared with conventional radiation therapy (RT), although acute and late urinary toxicities were not reduced significantly. Acute urinary toxicity, even at a low-grade, not only has an impact on a patient's quality of life, but also can be used as a predictor for chronic urinary toxicity. With bladder filling, part of the bladder moves away from the radiation field, resulting in a small irradiated bladder volume; hence, urinary toxicity can be decreased. The purpose of this study is to evaluate the impact of bladder volume on acute urinary toxicity during RT in patients with prostate cancer. Materials and Methods: Forty two patients diagnosed with prostate cancer were treated by 3DCRT and of these, 21 patients made up a control group treated without any instruction to control the bladder volume. The remaining 21 patients in the experimental group were treated with a full bladder after drinking 450 mL of water an hour before treatment. We measured the bladder volume by CT and ultrasound at simulation to validate the accuracy of ultrasound. During the treatment period, we measured bladder volume weekly by ultrasound, for the experimental group, to evaluate the variation of the bladder volume. Results: A significant correlation between the bladder volume measured by CT and ultrasound was observed. The bladder volume in the experimental group varied with each patient despite drinking the same amount of water. Although weekly variations of the bladder volume were very high, larger initial CT volumes were associated with larger mean weekly bladder volumes. The mean bladder volume was $299{\pm}155\;mL$ in the experimental group, as opposed to $187{\pm}155\;mL$ in the control group. Patients in experimental group experienced less acute urinary toxicities than in control group, but the difference was not statistically significant. A trend of reduced toxicity was observed with the increase of CT bladder volume. In patients with bladder volumes greater than 150 mL at simulation, toxicity rates of all grades were significantly lower than in patients with bladder volume less than 150 mL. Also, patients with a mean bladder volume larger than 100 mL during treatment showed a slightly reduced Grade 1 urinary toxicity rate compared to patients with a mean bladder volume smaller than 100 mL. Conclusion: Despite the large variability in bladder volume during the treatment period, treating patients with a full bladder reduced acute urinary toxicities in patients with prostate cancer. We recommend that patients with prostate cancer undergo treatment with a full bladder.

• Journal of Korean Home Economics Education Association
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• v.20 no.4
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• pp.19-42
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• 2008

The purpose of this study was to develop practical problem-based home economics teaching.learning process plans about a unit 'the youth and consumer life' of middle school eighth-grade Technology and Home Economics by applying blended learning(BL) strategy. According to ADDIE instructional design model, this study was conducted in the following procedure: analysis, design/development, implementation, and evaluation. In the stage of design and development, the selected unit was converted into a practical problem-based unit, and practical problem-based teaching. learning process plans were designed in detail by using BL strategy. An online study room for practical problem-based home economics instruction grounded in BL strategy was prepared by using Edunet(http://community.edunet4u.net/${\sim}$consumer2). Eight-session lesson plans were mapped out, and study aids for students and materials for teachers were prepared. In the implementation stage, the first-session teaching plans that dealt with a minor question 'what preparations should be made to become a wise consumer' were utilized when instruction was provided to 115 eighth graders who were in three different province, and the other one was in a middle school in the city of Daejeon. The experimental teaching was implemented for two weeks in the following procedure: preliminary program, pre-online learning, main instruction and post- online learning. The preliminary program was carried out in a session in the classroom, and pre-online learning was provided before the main instruction was given in a session in the classroom. After the main instruction was completed, post-online learning was offered. In the evaluation stage, a survey was conducted on all the learners and teachers to find out their opinions and suggestions.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.