• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.50-56
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• 2012

Purpose: Those who access to the nuclear medicine department are classified as radiation workers, temporarily access group, and occasional access group as defined by the atomic energy law. The radiation workers and temporarily access people wear a personal radiation dosimeter for checking their own radiation absorbed dose periodically. However, because of the sanitation workers, classified as temporarily access group, who are working in the nuclear medicine department are moved in a cycle with other departments and their works are changeful, it is hard to control their radiation absorbed dose. Thus, this study is going to examine the state of the sanitation worker's radiation absorbed dose, and then make sure whether they are classified as temporarily access group or not. Materials and methods: In the first instance, the first sanitation worker who works in vitro laboratory and PET room and the second sanitation worker who works in gamma camera rooms (invivo room) wore radiation dosimeter-OSL(Optically Stimulated Luminescence)- to measure their own radiation absorbed dose during work time from May to June 2011. Secondly, this study was taken place 5 places in gamma camera rooms, 2 places in PET bed room, operating room, waiting room and cyclotron room in PET and 4 places in vitro laboratory. And then to measure the radiation space dose rate, it is measured 10 times each of places as sanitation worker's work flow by using radiation survey meter. Results: The radiation absorbed dose on OSL of the first c who works in vitro laboratory and PET room and the second one who works in gamma camera rooms are 0.04, 0.02 mSv per month respectively. That means the estimated annual radiation absorbed doses are less than 1mSv as 0.48, 0.24 mSv/yr respectively. The radiation space dose rates as sanitation worker's work flow using survey meter are 0.0037, 0.0019 mSv/day, so the estimated annual radiation absorbed dose are 0.93, 0.47 mSv/yr respectively. The weighted exposure dose of first sanitation worker of each places are 1.62% in cyclotron room, 3.88% in waiting room, 2.39% in operating room, 81.01% in bed room of PET and 11.01% in vitro laboratory. The weighted exposure dose of second sanitation worker of each places are 45.22% in radiopharmaceutical laboratory, gamma 30.64% in camera rooms, 15.65% in waiting room, 8.49% in reading room. Conclusion: The annual radiation absorbed doses on OSL of both sanitation workers are less than 1 mSv per year and the annual radiation absorbed doses by using survey meter are less than 1mSv either, but close up to 1 mSv. Thus, to clarify whether the sanitation workers are temporarily access group or not, and to be lessen their s radiation absorbed dose, they should be educated about management of radiation and modified their work flow or work time appropriately, their radiation absorbed dose would be lessen certainly.

• Journal of The Korean Society of Grassland and Forage Science
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• v.23 no.1
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• pp.37-42
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• 2003

This study was conducted at a volcanic ash soil in the Experimental Farm of Cheju national university from May 1, 2000 to August 25, 2000 to determine the optimum frequency of split N application for. forage production of Jeju Italian millet(Setaria italica Beauvis). N .rate was applied with 200kg N/ha, and frequencies of the split application were 1. 2, 3, 4 and f times. Days to heading was 87 days in the N applied plot all at once, was delayed to 93 days at the five times split-applied plot. Plant height was the greatest (143cm) at the four times split-applied plot, but above o. below that was short. Leaf length, number of leaves and nodes were a similar tendency to plant height. SPAD(Soil Plant Analysis Development) reading values rose 34.3∼36.2 as N was split-applied from one to five times. Fresh forage, dry matter, crude Protein and TDN yield at the H split-applied to four times increased 33.08∼5l.50MT/ha, 9.94∼13.36MT/ha, 0.93∼1.70MT/ha and 5.06∼7.28MT/ha, respectively, but at the five tines split-applied plot decreased to 49.33MT/ha, 12.69MT/ha, 1.65MT/ha and 6.98 MT/ha, respectively. As the increasing of N split-applied. crude protein, crude fat NFE and TDN content increased 9.4∼13.0％, 1.5∼l.9％, 44.5∼45.5% and 50.9∼55.0％, respectively, whereas crude fiber and crude ash content decreased 35.3∼31.6% and 9.3∼8.3, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.14 no.2
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• pp.2634-2648
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• 1972

The aim of this Study is to bring Light on the effect of irrigation water temperature to the growth and harvest of Paddy rice in Various water Sources. 1. This research was completed in the writer's home nursery garden Located in Chungyoung-Ri, Hoeng sung-Myun, Hoengusung-Konn, Kangwan-Do. 2. The variety of Paddy rice was the IR667. 3. Practice was done by the treatment I .e river water, reservoir, tube well cold and tuke well warm with 3 riplications each. 4. The Paddy was transplanted in a pot 0.9 meter height and 1 meter Square without hottom filled with paddy soil to a planting depth 0.5 meter. The pot was laid underground and Covered with a film of polyethylene to keep of the rain. 5. The method of Cultivation was that used by the Filed Crops Experiment Station of the Office of Rural Development. 6. Atmospheric temperature was recorded every day of the growing period. The precipitation and Sun light was quoted by the KF-46 of Hoengsung. 7. The Soils in the test plots was relatively fortile, being Similar to ordinary paddy soils. 8. The charactor of irrigation water of surface and underground was both normal. 9. During the period of growth the average temperature of the underground water as $14.2^{\circ}C$ and that of the Surface was $24.1^{\circ}$. 10. The most useful water for the rice growing was that of river and reservoir while underground water was found to be generally injurious to the paddy growth because of low temperature. 11. In the case of underground water, there proved to be such harmful effects as reduction of culm length, rate of mature grain, panicle Length and grain weight and delay of tillering time, and heading time. Reading Therefore the writer conduded that the harvest of rice irrigated with underground water Showed a reduction of 15.8% compered with the rice irrigated by surface water.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.333-352
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• 2010

This study analyzed the services of libraries for babies and toddlers and the possibilities of service expansion through Bookstart program as a cooperative system for libraries. This study shows how users change their way of using libraries and their perceptions of the services of libraries for toddlers by implementing the questionnaire method and the analysis of library statistics. Results show that most of library users (98.8%) expressed the need for Bookstart program. Respondes also said that libraries, rather than other institutions, should be the place where the program is to be implemented. By analyzing the perceptions of library users, we also find that they think that the age of the first use of a library is more appropriate for toddlers than kindergarten-ages. We also found that library users who participated in a Bookstart program had a positive change in the way they used libraries. After participating in Bookstart programs, many changes occurred with respect to the perception of babies, reading habits of parents, and users' perception of libraries. After introducing Bookstart program, one city library's membership enrollment rates of babies and toddlers increased from 7.1% to 26.2%. But the rate for another city that did not participate in the program was shown at 4.3%. This study suggests that the introduction of Bookstart program would bring changes and expansions to the functions of libraries and the sometimes inflexible attitudes of library users. The study examined Bookstart program as a cooperative system for libraries by changing the perception of library users and activating the services of libraries for babies and toddlers.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.4
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• pp.253-259
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• 2013

The use of subsurface drip fertigation using slurry composting bio-filtration (SCB) as nitrogen (N) fertilizer source can be beneficial to improve fertilizer management decision. The objective of this study was to evaluate effects of SCB liquid fertilizer by subsurface drip fertigation on cucumber (Cucumis sativus L.) yield and soil nitrogen (N) distribution under greenhouse condition. Cucumber in greenhouse was transplanted on April $4^{th}$ and Aug $31^{st}$ in 2012. N sources were SCB and urea. Four N treatments with 3 replications consisted of control (No N fertilizer), SCB 0.5N + Urea 0.5N (50:50 split application), SCB 1.0N, Urea 1.0N. 100% of N recommendation rate from soil testing was denoted as 1.0N. The subsurface drip line and a tensiometer were installed at 30 cm soil depth. An irrigation was automatically started when the tensiometer reading was -15 kPa. The growth of cucumber at 85 days after transplanting was 5% higher in all N treatment than control. Semi-forcing culture produced more fruit yield than retarding culture. Fruit yields were 62.2, 76.3, 76.4, and 75.1 Mg $ha^{-1}$ for control, SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, respectively. Although fruit yields were similar under SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, 176 kg K $ha^{-1}$ can be over applied if cucumber is grown twice a year under SCB 1.0N that may result in K accumulation in soil. N uptake was 172, 209, 213, 207 kg $ha^{-1}$ for control, SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, respectively. N use efficiency was the highest (37%) at SCB 0.5N + Urea 0.5N under semi-forcing culture. Nitrate-N concentration in soil for all N treatments except control in semi-forcing culture was the highest between 15 and 30 cm soil depth at the 85 days after transplanting and between 0 and 15 cm soil depth after cucumber harvest. These results suggested that SCB 0.5N + Urea 0.5N can be used as an alternative N management for cucumber production in greenhouse if K accumulation is concerned.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.1
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• pp.32-36
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• 2016

Purpose In nuclear medicine examination, $^{131}I$ is widely used in nuclear medicine examination such as diagnosis, treatment, and others of thyroid cancer and other diseases. $^{131}I$ conducts examination and treatment through emission of ${\gamma}$ ray and ${\beta}^-$ ray. Since $^{131}I$ (364 keV) contains more energy compared to $^{99m}Tc$ (140 keV) although it displays high integrated rate and enables quick discharge through kidney, the objective of this study lies in comparing the difference in exposure dose of $^{131}I$ before and after wearing apron when handling $^{131}I$ with focus on 3 elements of external exposure protection that are distance, time, and shield in order to reduce the exposure to technicians in comparison with $^{99m}Tc$ during the handling and administration process. When wearing apron (in general, Pb 0.5 mm), $^{99m}Tc$ presents shield of over 90% but shielding effect of $^{131}I$ is relatively low as it is of high energy and there may be even more exposure due to influence of scattered ray (secondary) and bremsstrahlung in case of high dose. However, there is no special report or guideline for low dose (74 MBq) high energy thus quantitative analysis on exposure dose of technicians will be conducted based on apron wearing during the handling of $^{131}I$. Materials and Methods With patients who visited Department of Nuclear Medicine of our hospital for low dose $^{131}I$ administration for thyroid cancer and diagnosis for 7 months from Jun 2014 to Dec 2014 as its subject, total 6 pieces of TLD was attached to interior and exterior of apron placed on thyroid, chest, and testicle from preparation to administration. Then, radiation exposure dose from $^{131}I$ examination to administration was measured. Total procedure time was set as within 5 min per person including 3 min of explanation, 1 min of distribution, and 1 min of administration. In regards to TLD location selection, chest at which exposure dose is generally measured and thyroid and testicle with high sensitivity were selected. For preparation, 74 MBq of $^{131}I$ shall be distributed with the use of $2m{\ell}$ syringe and then it shall be distributed after making it into dose of $2m{\ell}$ though dilution with normal saline. When distributing $^{131}I$ and administering it to the patient, $100m{\ell}$ of water shall be put into a cup, distributed $^{131}I$ shall be diluted, and then oral administration to patients shall be conducted with the distance of 1m from the patient. The process of withdrawing $2m{\ell}$ syringe and cup used for oral administration was conducted while wearing apron and TLD. Apron and TLD were stored at storage room without influence of radiation exposure and the exposure dose was measured with request to Seoul Radiology Services. Results With the result of monthly accumulated exposure dose of TLD worn inside and outside of apron placed on thyroid, chest, and testicle during low dose $^{131}I$ examination during the research period divided by number of people, statistics processing was conducted with Wilcoxon Signed Rank Test using SPSS Version. 12.0K. As a result, it was revealed that there was no significant difference since all of thyroid (p = 0.345), chest (p = 0.686), and testicle (p = 0.715) were presented to be p > 0.05. Also, when converting the change in total exposure dose during research period into percentage, it was revealed to be -23.5%, -8.3%, and 19.0% for thyroid, chest, and testicle respectively. Conclusion As a result of conducting Wilcoxon Signed Rank Test, it was revealed that there is no statistically significant difference (p > 0.05). Also, in case of calculating shielding rate with accumulate exposure dose during 7 months, it was revealed that there is irregular change in exposure dose for inside and outside of apron. Although the degree of change seems to be high when it is expressed in percentage, it cannot be considered a big change since the unit of accumulated exposure dose is in decimal points. Therefore, regardless of wearing apron during high energy low dose $^{131}I$ administration, placing certain distance and terminating the administration as soon as possible would be of great assistance in reducing the exposure dose. Although this study restricted $^{131}I$ administration time to be within 5 min per person and distance for oral administration to be 1m, there was a shortcoming to acquire accurate result as there was insufficient number of N for statistics and it could be processed only through non-parametric method. Also, exposure dose per person during lose dose $^{131}I$ administration was measured with accumulated exposure dose using TLD rather than through direct-reading exposure dose thus more accurate result could be acquired when measurement is conducted using electronic dosimeter and pocket dosimeter.