• Journal of Labour Economics
• /
• v.26 no.2
• /
• pp.1-30
• /
• 2003

The recent experience about self-employment shows three main trends: first, its share out of the total workers has steadily increased, recording 37.6% in 2001, implying its prevalence and importance; second, its share out of male workers has caught up female workers', implying its importance to males as well as females; and finally, during the recent Economic Crisis when there was mass layoff and large scale bankruptcy, its share rapidly increased, reflecting its role of a buffer to economic fluctuation. However, there have been few studies on self-employment, mainly focusing on what makes someone choose it as an alternative to being employed. This study analyzes the determinants of the duration to terminate self-employment, by applying the proportional hazard model to the Korea Labor and Income Panel Survey(KLIPS) by the Korea Labor Institute. The KLIPS started the first wave in 1998 with the 5,000 household sample (and about 12,000 individual sample of household members aged 15 and more). In this study, the first four waves are used for analysis. The average duration of 5,357 spells of self-employment is 130 months. It shows slight difference between males(124 months) and females(138 months) while it widely ranges over industries (296 months for agriculture industry while 50 months for restaurant and hotel industry). Estimates of the proportional hazard model of the self-employment duration show that females are more likely to terminate self-employment while it is not statistically significant. The effect of age at starting self-employment on the hazard shows the inverse V-shape, which implies that, until a certain age(47 years), the hazard become higher as aging while, since then, it become lower as aging. The level of education has a positive effect on the hazard, implying that more education is related to the higher probability to be employed. The measures of economic performances, annual sales and earnings, are positively related to continuing self-employment while hardship at the start of self-employment measured by several ways has a negative effect. Training before opening business has a positive effect on keeping on self-employment and its effects are different over its providers, significantly positive for public providers while insignificant for private providers. More and further research on self-employment is urgent in the rapidly ageing society. To help workers to be self-employed, more public assistance is necessary for education, training, financing, marketing, management, and human resource management in order to make the olders consider self-employment as a good alternative rather than an inevitable one.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.16 no.4
• /
• pp.455-472
• /
• 2018

It is important to study how to manage dry storage casks of spent nuclear fuels (SNF), because wet storage spaces for SNF will shortly be at full capacity in the Republic of Korea. The US has operated a dry storage cask system for several decades, and has carried out significant studies into how to successfully manage dry storage cask for SNF. This type of expertise and experience is currently lacking in the Republic of Korea. The degradation of dry casks is an important issue that must be considered. In particular, chloride-induced stress corrosion cracking (CISCC) is known to lead to the release of radioisotopes from canisters. The U.S. Department of Energy, U.S. Nuclear Regulatory Commission, and the Electric Power Research Institute have undertaken research into the CISCC mechanism. In addition, Sandia National Laboratories (SNL) has extensively researched CISCC and how to manage it in dry storage canisters. In this review paper, the probabilistic model proposed by the SNL is analyzed and, based on this model, US-based CISCC research is reviewed in detail. This paper will inform the management of dry cask storage of SNF from light water reactors in austenite stainless steel canisters in the Republic of Korea.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.189-200
• /
• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.125-148
• /
• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.8
• /
• pp.3444-3451
• /
• 2012

Safety and health related information for the proper use and handing of pesticides is usually printed on the surface of the pesticide products in the form of texts. But, the guidelines or standards for the appropriate presentation of the texts for the pesticide products are most vague or not practical. Thus, this study aimed to provide the preliminary guidelines for the text sizes based on the legibility experiments. To achieve the objective legibility evaluation experiments were conducted to test the effects of different near vision (0.6, ${\geq}0.8$), gender, font type(thick gothic-type and fine gothic-type), thickness of font(plain and bold), and number of syllables(2 and 3 syllables) in the same age group of 20s. The results showed that legibility was different according to the visual acuity (p<0.05), and no other main effects showed statistically significant effects. The 'maximum illegible size' to read at least one word correctly in all the text conditions was 2 pt when the near vision was ${\geq}0.8$, and 2 pt or 3 pt when the near vision was 0.6. The 'minimum legible size' for 100% correct answer was 9 pt for the near vision of 0.6, and 5.3 pt for ${\geq}0.8$, respectively. Mean character size does not read any discomfort in 0.6 was 15.5 pt in both male and female but male was mean 8.5 pt, female was 10 pt in ${\geq}0.8$. Considering these experimental results, it was recommended that the 16 pt or larger characters should be used the important information such as 'Pesticides' or toxicity, and the minimum character size was 9 pt for the less important information.

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

• Radiation Oncology Journal
• /
• v.25 no.1
• /
• pp.54-61
• /
• 2007

[ $\underline{Purpose}$ ]: The purpose of this study is to develop a practical method for determining accurate marker positions for prostate cancer radiotherapy using CT images and kV x-ray images obtained from the use of the on- board imager (OBI). $\underline{Materials\;and\;Methods}$: Three gold seed markers were implanted into the reference position inside a prostate gland by a urologist. Multiple digital image processing techniques were used to determine seed marker position and the center-of-mass (COM) technique was employed to determine a representative reference seed marker position. A setup discrepancy can be estimated by comparing a computed $COM_{OBI}$ with the reference $COM_{CT}$. A proposed algorithm was applied to a seed phantom and to four prostate cancer patients with seed implants treated in our clinic. $\underline{Results}$: In the phantom study, the calculated $COM_{CT}$ and $COM_{OBI}$ agreed with $COM_{actual}$ within a millimeter. The algorithm also could localize each seed marker correctly and calculated $COM_{CT}$ and $COM_{OBI}$ for all CT and kV x-ray image sets, respectively. Discrepancies of setup errors between 2D-2D matching results using the OBI application and results using the proposed algorithm were less than one millimeter for each axis. The setup error of each patient was in the range of $0.1{\pm}2.7{\sim}1.8{\pm}6.6\;mm$ in the AP direction, $0.8{\pm}1.6{\sim}2.0{\pm}2.7\;mm$ in the SI direction and $-0.9{\pm}1.5{\sim}2.8{\pm}3.0\;mm$ in the lateral direction, even though the setup error was quite patient dependent. $\underline{Conclusion}$: As it took less than 10 seconds to evaluate a setup discrepancy, it can be helpful to reduce the setup correction time while minimizing subjective factors that may be user dependent. However, the on-line correction process should be integrated into the treatment machine control system for a more reliable procedure.

• The Korean Journal of Air & Space Law and Policy
• /
• v.28 no.1
• /
• pp.97-114
• /
• 2013

The 6th Worldwide Air Transport Conference was held in Montreal in March 2013 under the auspices of ICAO. This conference, which has been held every ten years, is dealing with virtually every issue of international air transport, and aiming at updating ICAO policy in order to ensure long-term growth of international civil aviation. Last conference which took place in 2003 focused on the liberalization of air transport, and the 6th conference shifted its focus from whether to push for liberalization, to how to implement it. The main agenda items for the 6th conference was liberalization, safeguards, ownership, fair competition, airports and air navigation facilities, charges, and ICAO policy. The liberalization, and in particular progressive liberalization has been a main theme over the past decades. In the process leading to liberalization, there needs to be the expansion of market access, easing regulation on ownership and control of airlines. Furthermore, the provision of enough infrastructure such as airport and air navigation facilities may be contributing factor to remove impediments to liberalization. However, out of concern as for undermining interests of consumer and the weak, when liberalization is proceeding in a sudden and radical manner, there should be safeguards so as to ensure market participation by developing countries, consumer protection, and economical and transparent decision on taxes and charges. Fair competition which differs from promoting competition in the market, is a policy in order to protect the weak players and consumers from monopoly and oligopoly. The Korean delegation submitted 3 WPs (WP/85, 86 and 87) and 1 IP, and presented WPs, at the conference, which were a lot compared with previous occasions. A paradigm shift was emphasized to expedite the process of liberalization at the 6th conference. The reality is that with many previous recommendations to stress the importance of liberalization, and to urge States to change their attitudes, the pace of the liberalization has been very slow and staggering. The liberalization of air transport will contribute to the growth of air transport and related industry, to create new employment, promoting tourism and regional development, and further to facilitating mutual understanding and exchange, which will also lead to making a barrier-free world. In this context, it is expected that the next conference will also evaluate the on-going process of liberalization.

• Journal of Hospice and Palliative Care
• /
• v.7 no.2
• /
• pp.153-168
• /
• 2004

Purpose: The purpose of tile study was to identify types of care needs of hospice patients and those from the family caregivers' perspective and to compare these two groups in reporting patients' care needs through Q-methodology. Methods: Twenty three Q-statements concerning care needs were selected through in-depth interviews of hospice patients. Data were collected from 20 hospice patients as well as 20 family caregivers respectively by sorting 23 Q-statements into 9 points standard. Data analysis was performed by using PC QUANL program. Results: Principal component analysis identified four types of care needs of the hospice patients. Overall, the accuracy of family caregiver reports was 48% in all types of care needs. Type 1 was named 'physical care needs type' for those whose greatest need was physical care to be free of pain and comfortable. The accuracy in Type 1 was 62.5%. Type 2 was named 'emotional care needs type' for those who would like to share love and intimacy with their family members. The accuracy in Type 2 was 20%. Type 3 was named 'spiritual care needs type' for those who would like to receive forgiveness from their God and prayers and visitation of clergy. The accuracy in Type 3 was 60%. Type 4 was named 'social care needs type' for those who would like to complete their ongoing work and to give service to others. The accuracy in Type 4 was 50%. Conclusion: There was a great difference between hospice patients and the family caregivers in reporting patients' care needs. Thus, hospice nurses need to educate family caregivers to more accurately assess patients' care needs.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.113-125
• /
• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.