• The Journal of Korean Society for Radiation Therapy
• /
• v.29 no.1
• /
• pp.37-48
• /
• 2017

Purpose: The most basic conditions of radiation therapy is to prevent unnecessary exposure of normal tissue. The risk factors that are important o evaluate the dose emitted to the lung and heart from radiation therapy for breast cancer. Therefore, comparing the dose factors of a normal tissue according to the radion treatment position and Seeking an effective radiation treatment for breast cancer through the analysis of the correlation relationship. Materials and Methods: Computed tomography was conducted among 30 patients with left breast cancer in supine and prone position. Eclipse Treatment Planning System (Ver.11) was established by computerized treatment planning. Using the DVH compared the incident dose to normal tissue by position. Based on the result, Using the SPSS (ver.18) analyzed the dose in each normal tissue factors and Through the correlation analysis between variables, independent sample test examined the association. Finally The HI, CI value were compared Using the MIRADA RTx (ver. ad 1.6) in the supine, prone position Results: The results of computerized treatment planning of breast cancer in the supine position were V20, $16.5{\pm}2.6%$ and V30, $13.8{\pm}2.2%$ and Mean dose, $779.1{\pm}135.9cGy$ (absolute value). In the prone position it showed in the order $3.1{\pm}2.2%$, $1.8{\pm}1.7%$, $241.4{\pm}138.3cGy$. The prone position showed overall a lower dose. The average radiation dose 537.7 cGy less was exposured. In the case of heart, it showed that V30, $8.1{\pm}2.6%$ and $5.1{\pm}2.5%$, Mean dose, $594.9{\pm}225.3$ and $408{\pm}183.6cGy$ in the order supine, prone position. Results of statistical analysis, Cronbach's Alpha value of reliability analysis index is 0.563. The results of the correlation analysis between variables, position and dose factors of lung is about 0.89 or more, Which means a high correlation. For the heart, on the other hand it is less correlated to V30 (0.488), mean dose (0.418). Finally The results of independent samples t-test, position and dose factors of lung and heart were significantly higher in both the confidence level of 99 %. Conclusion: Radiation therapy is currently being developed state-of-the-art linear accelerator and a variety of treatment plan technology. The basic premise of the development think normal tissue protection around PTV. Of course, if you treat a breast cancer patient is in the prone position it take a lot of time and reproducibility of set-up problems. Nevertheless, As shown in the experiment results it is possible to reduce the dose to enter the lungs and the heart from the prone position. In conclusion, if a sufficient treatment time in the prone position and place correct confirmation will be more effective when the radiation treatment to patient.

• Journal of Technologic Dentistry
• /
• v.10 no.1
• /
• pp.11-24
• /
• 1988

The purpose of this study was to determine the concentration of cadmium, nickel and chromium in the air of the work-place, blood of and urine of workers and compare the level of those heavy metals by the duration of work, work-place, process of work, smoking and other factors. In this study, 48 male dental laboratory technicans and 72 office workers as the control group were subjected. The concentration of cadmium, nickel and chromium in their blood sand urine, and that of heavy metals in the air of their work-rooms were examined and analyzed from June I 1987 to September 30, 1987. The results were as follows : 1. The concentration of cadmium in the air was the highest in the porcelain part, $0.0087{\pm}0.0016mg/m^3$, that of nickel was the highest in the crown bridge part, $0.4253{\pm}0.0052mg/m^3$, and that of chrnmium was highest in the partial denture part, $0.1063{\pm}0.0024mg/m^3$. 2. cadmium, nickel and chromium concentrations in the blood and urine of dental laboratory techincians were higher that in the office workers'. Especially the concentration of cadmium in the blood($1.92{\pm}1.23{\mu}g$/100ml) of th dental laboratory techician was about two times as high as that in the office workers'($0.90{\pm}0.73{\mu}g$/100ml), and the concentration of nickel in the urine($48.53{\pm}38.83{\mu}g$/e) of the dental laboratory thchnician was about two times as high as that in the office worker's($20.24{\pm}15.35{\mu}g$/e). 3. there was no difference in the concentration of cadmium, nickel and chromium in the blood and urine with a longer duration of work. 4. The concentration of cadmium and chromium in the blood and urine differed significantly depending upon the place of work. The concentration of cadmium was the highest in the blood of dental laboratory technicians working kin the poreclain part marking at $2.53{\pm}1.08{\mu}g$/100ml. The chromium level was the heighest in the blood of partial denture park workers with a concentration of $3.60{\pm}1.02{\mu}g$/100ml. Concerning the level of cadmium in urine, it was the highest in the porcelain part workers with a concentration of $3.41{\pm}3.15{\mu}g$/e. 5. The concentration of cadmium in the urine of metal trimming and polishing group($2.64{\pm}2.41{\mu}g$/e) was higher than that of non-metal trimming and polishing group($1.39{\pm}1.18{\mu}g$/e). 6. The concentration of chromium in the blood of smoking group($2.46{\pm}1.54{\mu}g$/100ml)was higher than that lf non-smoking group($1.54{\pm}1.25{\mu}g$/100ml). 7. The height positive correlation coefficient was shown between the concentration of nickel and chromium in the blood among the all correlations between 3metals(Cd, Ni, Cr) in the blood and those in urine. The correlation coefficient was relatively high(r=0.605,,p<0.01). In general, the higher the concentration of heavy metals in the air of work places the higher the concention lf them in the blood and urine of workers, mere attention should be paid to the working environment of dental laboratory workers, Furthermore, continuous biological monitoring and further research are required for an efficient health management for dental laboratory workers.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.1-13
• /
• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
• /
• v.20 no.3
• /
• pp.133-149
• /
• 2014

One of the main purposes of universities is to create new intellectual resources that will increase social values. These intellectual resources include academic research papers, lecture notes, patents, and creative ideas produced by both professors and students. However, intellectual resources in universities are often not distributed to the actual users or companies; and moreover, they are not even systematically being managed inside of the universities. Therefore, it is almost impossible for companies to access the knowledge created by university students and professors to utilize them. Thus, the current level of knowledge sharing between universities and industries are very low. This causes a great extravagant with high-quality intellectual and human resources, and it leads to quite an amount of social loss in the modern society. In the 21st century, the creative ideas are the key growth powers for many industries. Many of the globally leading companies such as Fedex, Dell, and Facebook have established their business models based on the innovative ideas created by university students in undergraduate courses. This indicates that the unconventional ideas from young generations can create new growth power for companies and immensely increase social values. Therefore, this paper suggests of a new platform for intellectual properties distribution with university-industry cooperation. The suggested platform distributes intellectual resources of universities to industries. This platform has following characteristics. First, it distributes not only the intellectual resources, but also the human resources associated with the knowledge. Second, it diversifies the types of compensation for utilizing the intellectual properties, which are beneficial for both the university students and companies. For example, it extends the conventional monetary rewards to non-monetary rewards such as influencing on the participating internship programs or job interviews. Third, it suggests of a new knowledge map based on the relationships between key words, so that the various types of intellectual properties can be searched efficiently. In order to design the system platform, we surveyed 120 potential users to obtain the system requirements. First, 50 university students and 30 professors in humanities and social sciences departments were surveyed. We sent queries on what types of intellectual resources they produce per year, how many intellectual resources they produce, if they are willing to distribute their intellectual properties to the industries, and what types of compensations they expect in returns. Secondly, 40 entrepreneurs were surveyed, who are potential consumers of the intellectual properties of universities. We sent queries on what types of intellectual resources they want, what types of compensations they are willing to provide in returns, and what are the main factors they considered to be important when searching for the intellectual properties. The implications of this survey are as follows. First, entrepreneurs are willing to utilize intellectual properties created by both professors and students. They are more interested in creative ideas in universities rather than the academic papers or educational class materials. Second, non-monetary rewards, such as participating internship program or job interview, can be the appropriate types of compensations to replace monetary rewards. The results of the survey showed that majority of the university students were willing to provide their intellectual properties without any monetary rewards to earn the industrial networks with companies. Also, the entrepreneurs were willing to provide non-monetary compensation and hoped to have networks with university students for recruiting. Thus, the non-monetary rewards are mutually beneficial for both sides. Thirdly, classifying intellectual resources of universities based on the academic areas are inappropriate for efficient searching. Also, the various types of intellectual resources cannot be categorized into one standard. This paper suggests of a new platform for the distribution of intellectual materials and human resources, with university-industry cooperation based on these survey results. The suggested platform contains the four major components such as knowledge schema, knowledge map, system interface, and GUI (Graphic User Interface), and it presents the overall system architecture.

• Journal of Bio-Environment Control
• /
• v.14 no.2
• /
• pp.69-75
• /
• 2005

The storability of chicon was compared by packing it with PE box, wrap, LDPE (low density polyethylene) film that was 25 and 50um thickness, respectively and storing at 1 and $10^{\circ}C$ under light and dark conditions. The visual quality depending on dehydration was deteriorated at more than $2\%$ weight loss during storage. In packing treatments, chicon packed with PE box lost fresh weight to $3\%\;at\;10^{\circ}C\;and\;2\%\;at\;1^{\circ}C$, while non- penetrated film treatment, wrap, 25 and 50um thickness LDPE film, showed less than $1\%$ weight loss. The carbon dioxide concentration in package was $3\~4\%\;in\;50{\mu}m$ LDPE film at $1^{\circ}C\; and\;25um$ LDPE film at $10^{\circ}C$. The ethylene concentration in 50um LDPE film at $1^{\circ}C\;and\;25{\mu}m$ LDPE film at $10^{\circ}C$ was approximately 0.3 ppm and 0.5 ppm, respectively. Chiton stored in dark condition didn't turn to green, but it fumed green only in 3 days at $10^{\circ}C$ and in 6 days at $1^{\circ}C$ under light condition. The greening of chicon was less, the packing materials was thicker. The chlorophyll content represented the degree of greening showed less at $1^{\circ}C$ then at $10^{\circ}C$. The coefficient of correlation(r) between chlorophyll content and carbon dioxide concentration in package was 0.926 at $1^{\circ}C$ and 0.997 at $10^{\circ}C$. The visual quality except greening of packed chicon was maintained at $1^{\circ}C$ better than $10^{\circ}C$, and it was shown highest grade packed with $50{\mu}m$ LDPE film at $1^{\circ}C$ and packed with 25um LDPE film at $10^{\circ}C$. The vitamin C content in packed chicon was kept higher at $1^{\circ}C$ on storage temperatures, and 25um and 50um LDPE film on packing materials. According to these results, it can be proper condition for storage and marketing of chicon that 50um LDPE film at $1^{\circ}C$ and 25um LDPE film at $10^{\circ}C$. And dark condition is necessary to store chicon because it should turn green under tiny light condition.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.18 no.1
• /
• pp.40-46
• /
• 2013

The isotope ratios of $^{13}C/^{12}C$ and $^{18}O/^{16}O$ for a sample in a mass spectrometer are measured relative to those of a pure $CO_2$ reference gas (i.e., laboratory working standard). Thus, the calibration of a laboratory working standard gas to the international isotope scales (Pee Dee Belemnite (PDB) for ${\delta}^{13}C$ and Vienna Standard Mean Ocean Water (V-SMOW) for ${\delta}^{18}O$) is essential for comparisons between data sets obtained by other groups on other mass spectrometers. However, one often finds difficulties in getting well-calibrated standard gases, because of their production time and high price. Additional difficulty is that fractionation processes can occur inside the gas cylinder most likely due to pressure drop in long-term use. Therefore, studies on laboratory production of pure $CO_2$ isotope standard gas from stable solid calcium carbonate standard materials, have been performed. For this study, we propose a method to extract pure $CO_2$ gas without isotope fractionation from a solid calcium carbonate material. The method is similar to that suggested by Coplen et al., (1983), but is better optimized particularly to make a large amount of pure $CO_2$ gas from calcium carbonate material. The $CaCO_3$ releases $CO_2$ in reaction with 100% pure phosphoric acid at $25^{\circ}C$ in a custom designed, evacuated reaction vessel. Here we introduce optimal procedure, reaction conditions, and samples/reactants size for calcium carbonate-phosphoric acid reaction and also provide the details for extracting, purifying and collecting $CO_2$ gas out of the reaction vessel. The measurements for ${\delta}^{18}O$ and ${\delta}^{13}C$ of $CO_2$ were performed at Seoul National University using a stable isotope ratio mass spectrometer (VG Isotech, SIRA Series II) operated in dual-inlet mode. The entire analysis precisions for ${\delta}^{18}O$ and ${\delta}^{13}C$ were evaluated based on the standard deviations of multiple measurements on 15 separate samples of purified $CO_2$. The pure $CO_2$ samples were taken from 100-mg aliquots of a solid calcium carbonate (Solenhofen-ori $CaCO_3$) during 8-day experimental period. The multiple measurements yielded the $1{\sigma}$ precisions of ${\pm}0.01$‰ for ${\delta}^{13}C$ and ${\pm}0.05$‰ for ${\delta}^{18}O$, comparable to the internal instrumental precisions of SIRA. Therefore, we conclude the method proposed in this study can serve as a way to produce an accurate secondary and/or laboratory $CO_2$ standard gas. We hope this study helps resolve difficulties in placing a laboratory working standard onto the international isotope scales and does make accurate comparisons with other data sets from other groups.

• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.111-131
• /
• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Food Science and Preservation
• /
• v.23 no.5
• /
• pp.718-726
• /
• 2016

Sweet pumpkin paste (SPP) was fermented by Leuconostoc mesenteroides SM at $25^{\circ}C$ for 3 days for enhancing its physicochemical properties. SPPs with 5%, 10%, and 15% solid contents (SC) were fortified with 20% sucrose and 0.5% yeast extract. The unfermented SPP with 15% SC indicated L, a, and b color values of 25.02, 4.66, and 13.35, respectively, and a consistency index of $48.6Pa{\cdot}s^n$. During the 3 days of fermentation, both the a and b color values decreased slightly, whereas the consistency index increased to $188.8Pa{\cdot}s^n$, giving the fermented product a pudding-like consistency. This fermented SPP (15% SC) showed the highest acid production and viable cell counts among samples, indicating pH 3.85, 1.30% acidity and $9.2{\times}10^8CFU/mL$ respectively. The added sucrose was completely utilized after 1 day of fermentation. After 3 days, the insoluble and soluble dextran contents were 8.9% and 4.5%, respectively. Furthermore, the contents of mannitol and fructose were 3.11% and 1.76%, respectively. Regarding the sensory evaluation, this fermented sample also indicated the highest color, taste and texture scores, and was the overall preferred sample. In conclusion, the fermented SPP with 15% SC was carotinoid-rich a wholesome pumpkin-based product that is rich in probiotics and lactic bacteria-produced mannitol and dextran, which gave the product an acceptable viscous pudding-like consistency and good organoleptic properties.

• Current Research on Agriculture and Life Sciences
• /
• v.2
• /
• pp.9-14
• /
• 1984

This study was performed to obtain the effective selection informations for improvement of quality and increase of yield in red pepper. The eight parents and twenty eight crosses from partial diallel were used as materials for estimation of correlations among the pericarp characters, viz, fruit length, fruit width, pericarp thickness (fresh and dry) and pericarp weight (fresh and dry), between pericarp weight and seed weight and between pericarp weight and the percent of seed weight/pericarp weight and path coefficients on fresh and dry pericarp weight. Results were as follows. In $F_1s$, fresh and dry pericarp weight had positive correlations with fruit length, fruit width, and pericarp thickness. Fresh pericarp weight was also positively correlated with dry pericarp weight. Dry pericarp thickness had a negative correlation with fruit length but had positive correlations with fruit width and fresh pericarp thickness. Fresh pericarp thickness had a positive correlation with fruit width. Significantly positive correlations between $F_1s$ and mid-parents were observed in pericarp characters. Pericarp weight had a positive correlation with seed weight but had a negative correlation with the percent of seed weight/pericarp weight. In path coefficient analysis, it was found that fruit length, fruit width and pericarp thickness had direct effects on fresh and dry pericarp weight and that fruit length had the largest direct effect in $F_1s$.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.6
• /
• pp.757-772
• /
• 2019

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Artificial Neural Network, Social Network, and Tabu Search models on 38 Asian container ports over the period 2007-2016. The models consider number of cranes, depth, birth length, and total area as inputs and container throughput as output. Followings are the main empirical results. First, the variables ranking order which affects the clustering according to artificial neural network are TEU, birth length, depth, total area, and number of cranes. Second, social network analysis shows the same clustering in the benevolent and aggressive models. Third, the efficiency of domestic ports are worsened after clustering using social network analysis and tabu search models. Forth, social network and tabu search models can increase the efficiency by 37% compared to that of the general CCR model. Fifth, according to the social network analysis and tabu search models, 3 Korean ports could be clustered with Asian ports like Busan Port(Kobe, Osaka, Port Klang, Tanjung Pelepas, and Manila), Incheon Port(Shahid Rajaee, and Gwangyang), and Gwangyang Port(Aqaba, Port Sulatan Qaboos, Dammam, Khor Fakkan, and Incheon). Korean seaport authority should introduce port improvement plans by using the methods used in this paper.