• Journal of Preventive Medicine and Public Health
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• v.32 no.1
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• pp.48-59
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• 1999

Objectives. This study was conducted to evaluate the association between upper extremity musculoskeletal symptoms and Rapid Upper Limb Assessment(RULA) in vehicle assembly line workers. The goal of this study is to show the feasibility of RULA as a checklist for work related musculoskeletal symptoms (WMSDs) in Korean workers. Methods. The total number of 199 people from the department of assembly and 115 people from the department of Quality Control(QC) in automotive plant were subjects for this cross sectional study. A standard symptom questionnaire survey has been used for the individual characteristics, work history, musculosketal symptoms and non-occupational covariates. The data were obtained by applying one-on-one interview for the all subjects. RULA has been applied for ergonomic work posture analysis and the primary ergonomic risk sure was computed by RULA method. Association between upper extremity musculoskeletal symptoms and RULA were assessed by multiple logistic regression analysis. Results. A total of 314 workers was examined. The prevalence of musculoskeletal symptoms by NIOSH case definition was 62.4%. The distribution of musculoskeletal symptoms by the part of the body turned out to be following; back:41.4%, neck: 32.8%, shoulder: 26.4%, arm: 10.5% and hand:29.3%. The relationship of the individual RULA scores were statistically significant for the prevalence of musculoskeletal symptoms. As the result of the multiple logistic regressioin analysis, grand final score (OR=2.250 95% CI: 1.402-3.612) was associated with musculoskeletal symptoms in any part of the body.; upper arm score(OR=1.786 95% CI: 1.036-3.079) and posture score A(OR=1.634 95% CI: 1.016-2.626) in neck; muscel use score(OR=3.076 95% CI:1.782-5.310) and posture score A(OR=1.798 95% CI: 1.072-3.017) in shoulder; upper arm score(OR=1.715 95% CI: 1.083-2.715) and muscel use score(OR=2.057 95% CI:1.303-3.248) in neck & shoulder; muscle use score(OR=10.662 95% CI: 3.180-35.742) in arm; writst/wist score(OR=2.068 95% CI: 1.130-3.786) and muscle use score(OR=2.215 95% CI: 1.284-3.819) in hand & wrist.; muscle use score of trunk (OR=2.601 95% CI: 1.147-5.901) in back. Conclusions. Musculoskeletal symptoms of the extremities were strongly associated with individual RULA body score. These results show that RULA can be used as a useful assessment tool for the evaluation of musculoskeletal loading which is known to contribute to work-related musculoskeletal disorders. RULA also can be used as a screening tool or incorporated into a wider ergonomic assessment of epidemiological, physical, mental, environmental and organizational factors. As shown in this study, complement of the analysis system for the other risk factors and characterizing between the upper limb and back part will be needed for future work.

• The Journal of Korean Society for Radiation Therapy
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• v.23 no.1
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• pp.31-39
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• 2011

Purpose: Helical Tomotherapy allows only coplanar beam delivery because it does not allow couch rotation. We investigated a method to introduce non-coplanar beam by tilting a patient's head for Tomotherapy. The aim of this study was to compare intrafractional movement during Tomotherapy between coplanar and non-coplanar patient's setup. Materials and Methods: Helical Tomotherapy was used for treating eight patients with intracranial tumor. The subjects were divided into three groups: one group (coplanar) of 2 patients who lay on S-plate with supine position and wore thermoplastic mask for immobilizing the head, second group (non-coplanar) of 3 patients who lay on S-plate with supine position and whose head was tilted with Variable Axis Baseplate and wore thermoplastic mask, and third group (non-coplanar plus mouthpiece) of 3 patients whose head was tilted and wore a mouthpiece immobilization device and thermoplastic mask. The patients were treated with Tomotherapy after treatment planning with Tomotherapy Planning System. Megavoltage computed tomography (MVCT) was performed before and after treatment, and the intrafractional error was measured with lateral(X), longitudinal(Y), vertical(Z) direction movements and vector ($\sqrt{x^2+y^2+z^2}$) value for assessing overall movement. Results: Intrafractional error was compared among three groups by taking the error of MVCT taken after the treatment. As the correction values (X, Y, Z) between MVCT image taken after treatment and CT-simulation image are close to zero, the patient movement is small. When the mean values of movement of each direction for non-coplanar setup were compared with coplanar setup group, X-axis movement was decreased by 13%, but Y-axis and Z-axis movement were increased by 109% and 88%, respectively. Movements of Y-axis and Z-axis with non-coplanar setup were relatively greater than that of X-axis since a tilted head tended to slip down. The mean of X-axis movement of the group who used a mouthpiece was greater by 9.4% than the group who did not use, but the mean of Y-axis movement was lower by at least 64%, and the mean of Z-axis was lower by at least 67%, and the mean of Z-axis was lower by at least 67%, and the vector was lower by at least 59% with the use of a mouthpiece. Among these 8 patients, one patient whose tumor was located on left frontal lobe and left basal ganglia received reduced radiation dose of 38% in right eye, 23% in left eye, 30% in optic chiasm, 27% in brain stem, and 8% in normal brain with non-coplanar method. Conclusion: Tomotherapy only allows coplanar delivery of IMRT treatment. To complement this shortcoming, Tomotherapy can be used with non-coplanar method by artificially tilting the patient's head and using an oral immobilization instrument to minimize the movement of patient, when intracranial tumor locates near critical organs or has to be treated with high dose radiation.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.29-35
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• 2014

Purpose : This study has already started commercial Gated RapidArc automation equipment which was not previously in the Gated radiation therapy can be performed simultaneously with the VMAT Gated RapidArc radiation therapy to the accuracy of the analysis to evaluate the usability, Amplitude mode applied to the patient. Materials and Methods : The analysis of the distribution of radiation dose equivalent quality solid water phantom and GafChromic film was used Film QA film analysis program using the Gamma factor (3%, 3 mm). Three-dimensional dose distribution in order to check the accuracy of Matrixx dosimetry equipment and Compass was used for dose analysis program. Periodic breathing synchronized with solid phantom signals Phantom 4D Phantom and Varian RPM was created by breathing synchronized system, free breathing and breath holding at each of the dose distribution was analyzed. In order to apply to four patients from February 2013 to August 2013 with liver cancer targets enough to get a picture of 4DCT respiratory cycle and then patients are pratice to meet patient's breathing cycle phase mode using the patient eye goggles to see the pattern of the respiratory cycle to be able to follow exactly in a while 4DCT images were acquired. Gated RapidArc treatment Amplitude mode in order to create the breathing cycle breathing performed three times, and then at intervals of 40% to 60% 5-6 seconds and breathing exercises that can not stand (Fig. 5), 40% While they are treated 60% in the interval Beam On hold your breath when you press the button in a way that was treated with semi-automatic. Results : Non-respiratory and respiratory rotational intensity modulated radiation therapy technique absolute calculation dose of using computerized treatment plan were shown a difference of less than 1%, the difference between treatment technique was also less than 1%. Gamma (3%, 3 mm) and showed 99% agreement, each organ-specific dose difference were generally greater than 95% agreement. The rotational intensity modulated radiation therapy, respiratory synchronized to the respiratory cycle created Amplitude mode and the actual patient's breathing cycle could be seen that a good agreement. Conclusion : When you are treated Non-respiratory and respiratory method between volumetric intensity modulated radiation therapy rotation of the absolute dose and dose distribution showed a very good agreement. This breathing technique tuning volumetric intensity modulated radiation therapy using a rotary moving along the thoracic or abdominal breathing can be applied to the treatment of tumors is considered. The actual treatment of patients through the goggles of the respiratory cycle to create Amplitude mode Gated RapidArc treatment equipment that does not automatically apply to the results about 5-6 seconds stopped breathing in breathing synchronized rotary volumetric intensity modulated radiation therapy facilitate could see complement.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.