• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.89-115
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• 2019

This study was conducted to present the stylistic differences between Arthur Conan Doyle and Agatha Christie, famous as writers of classical mystery novels, through data analysis, and further to present the analytical methodology of the study of style based on text mining. The reason why we chose mystery novels for our research is because the unique devices that exist in classical mystery novels have strong stylistic characteristics, and furthermore, by choosing Arthur Conan Doyle and Agatha Christie, who are also famous to the general reader, as subjects of analysis, so that people who are unfamiliar with the research can be familiar with them. The primary objective of this study is to identify how the differences exist within the text and to interpret the effects of these differences on the reader. Accordingly, in addition to events and characters, which are key elements of mystery novels, the writer's grammatical style of writing was defined in style and attempted to analyze it. Two series and four books were selected by each writer, and the text was divided into sentences to secure data. After measuring and granting the emotional score according to each sentence, the emotions of the page progress were visualized as a graph, and the trend of the event progress in the novel was identified under eight themes by applying Topic modeling according to the page. By organizing co-occurrence matrices and performing network analysis, we were able to visually see changes in relationships between people as events progressed. In addition, the entire sentence was divided into a grammatical system based on a total of six types of writing style to identify differences between writers and between works. This enabled us to identify not only the general grammatical writing style of the author, but also the inherent stylistic characteristics in their unconsciousness, and to interpret the effects of these characteristics on the reader. This series of research processes can help to understand the context of the entire text based on a defined understanding of the style, and furthermore, by integrating previously individually conducted stylistic studies. This prior understanding can also contribute to discovering and clarifying the existence of text in unstructured data, including online text. This could help enable more accurate recognition of emotions and delivery of commands on an interactive artificial intelligence platform that currently converts voice into natural language. In the face of increasing attempts to analyze online texts, including New Media, in many ways and discover social phenomena and managerial values, it is expected to contribute to more meaningful online text analysis and semantic interpretation through the links to these studies. However, the fact that the analysis data used in this study are two or four books by author can be considered as a limitation in that the data analysis was not attempted in sufficient quantities. The application of the writing characteristics applied to the Korean text even though it was an English text also could be limitation. The more diverse stylistic characteristics were limited to six, and the less likely interpretation was also considered as a limitation. In addition, it is also regrettable that the research was conducted by analyzing classical mystery novels rather than text that is commonly used today, and that various classical mystery novel writers were not compared. Subsequent research will attempt to increase the diversity of interpretations by taking into account a wider variety of grammatical systems and stylistic structures and will also be applied to the current frequently used online text analysis to assess the potential for interpretation. It is expected that this will enable the interpretation and definition of the specific structure of the style and that various usability can be considered.

• Journal of Life Science
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• v.15 no.5 s.72
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• pp.840-846
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• 2005

This study was carried out to investigate the effect of electron beam irradiation and cooking temperature on physico-chemical characteristics and lipid oxidation of beef. A total of six beef carcasses ($280\∼300 kg$) that were quality grade $1^{+}$(marbling score No.7, meat color No.4, maturity No.1, texture No.1) was purchased at the commercial slaughter house. The carcasses were transported and washed using high pressure water, and pasteulized with $ 50\% $ ethyl alcohol in the laboratory. After the carcasses were deboned and trimmed, loin and round were taken out to make steak (1.5cm thickness) or ground beef respectively. Samples were wrap or vacuum packaged and irradiated with 0, 3, 4.5, 6 and 7.5 kGy using electron-beam accelerator at Samsung Heavy Industries Ltd. Co. (in Taejun). Irradiated samples were cooked with different methods(electronic pan and gas oven) and temperatures ($ 60^{\circ}C, 70^{\circ}C and 80^{\circ}C$) and used to measure fatty acid composition, TBARS, cholesterol oxide products and panel test scores. The content of saturated fatty acids increased by increasing heating temperature in oven boiling steak (OBS) and pan boiling steak (PBS), and there was no difference by electron-beam irradiation. Both irradiated and non-irradiated treatment were high as the heating temperature increased in TBARS by heating temperature in PBS (p < 0.05) and the amount of Malonaldehyde (MA), standard of fat deterioration, was increased in OBS (p < 0.05). Non-irradiated and 3, 6 kGy treatment produced about 2 fold amount of MA at $ 60^{\circ}C $ compared with $ 80^{\circ}C $. In comparison with PBS, OBS produced much amount of MA and a bit different from non-irradiated treatment but did not show no tendency. As irradiation levels and heating temperature increased, the amount of cholesterol oxides products was increased and also pan-heating method, direct heating method, significantly increased the degree of oxidation compared with oven-heating method, indirect heating method (p < 0.05).

• The korean journal of orthodontics
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• v.28 no.4 s.69
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• pp.533-546
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• 1998

A Skeletal Class III malocclusion may be the result of a large mandible, a small maxilla or combination of the two. Protraction devices for the maxilla are used to promote the growth of a deficient maxilla by applying extraoral force to actively growing patients. This study has been performed to determine whether there are significant differences in skeletal and dental changes between FH/Pal 1 and FH/Pal 2 group, SNA 1 and SNA 2 group, SNB 1 and SNB 2 group, and LFH 1 and LFH 2 group after RME and facial mask therapy. The results of this study can be summarized and concluded as follows ; 1. In all patients after maxillary protraction, the maxilla and maxillary dentitions moved forward, and the mandible rotated backward and downward. In most of them, palatal plane is tends to have an upward inclination. 2. The FH/Pal group 1, having an upward inclination of the palatal plane as a result of Facial mast showed statistically significant maxillary forward movement compared to the FH/Pal group 2. 3. The SNA group 1 showed significantly less mandibular backward movement and there was a tendency for the palatal plane to upward inclination compared to SNA group 2. 4. The SNB group 1 showed significantly less maxillary forward movement, but the vertical dimension, especially the lower facial height increased by mandibular downward rotation compared to SNB group 2. 5. LFH group 1, which had large saddle angle and posterior positioned mandible in the pre-treatment stage, showed maxillary protraction effect without significant increase in lower facial height compared to LFH group 2.

• Journal of agricultural medicine and community health
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• v.30 no.1
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• pp.1-14
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• 2005

Objectives: This study attempts to analyze the length of hospital stay and expenses of frequent disease admitted in a Vaterans Hospital. Methods: Data was collected from January 1, 2001 to December 31, 2003 from the Claim records of 9,640 patients in a Vaterans Hospital. Results: The results were as follows: 1. In age & sex distribution, there was male 70.9%, female 29.1%, and 35.8% of them is 70 age group. Frequency by insurance program was Health insurance 78.1%, Medical aid 14.2%, no insurance 4.1%, others 3.6%. Distribution of each department was internal medicine 28.3%, orthopedic surgery 21.3%, surgery 16.6%, neurosurgey 7.1%, pediatrics 5.9%. Also, in the veterans group, male to female patient ratio was 99.3% male to 0.7% female, them over 70 years old was 51.6%, and them which live in daejeon was 43.5%. 2. In frequency of disease, there was gastroenteritis 4.8%, pneumonia 3.8%, cartaract 3.7%, cerebral infarct 3.2%, hyperplasia of prostate 3.0%. In frequency of korean standard classification of diseases, there was injury and poisoning and certain other consequences of external causes 17.1%, diseases of digestive system 16.1%, diseases of musculoskeletal system and connective tissue 13.9%, diseases of respiratory system 9.4%, diseases of genitourinary system 8.6%. Also, in veterans group, frequency of them was diseases of musculoskeletal system and connective tissue 19.4%, diseases of digestive system 16.8%, injury and poisoning and certain other consequences of external causes 15.7%, diseases of genitourinary system 9.7%, diseases of circuatory system 8.2%. 3. Average length of hospital stay was 29.0 days for total patients, 51.8 days for the veterans group, 15.7 days for the non-veterans one. Average total expenses was 3,669,579 won, the veterans group 7,263,877 won, the non-veterans one 1,560,333 won. The ratio of insurer to insuree was 55.2 : 44.8, the ratio of amount paid by patient in the veterans group 61.7%, in the non-veterans one 33.0%. 4. In items of medical expenses, fee for hospital accommodation was 34.7%, fee for medication 13.2%(injection 7.8%, drug 5.4%), fee for service 48.6%(physical therapy 26.3%, operation 9.7%, laboratory examination 5.2%, radiological examination 3.1%, etc), others 3.4%. In them for the veterans group, fee for physical therapy was 35.3%, fee for hospital accommodation 35.2%, fee for injection 6.2%, fee for operation 5.9%, for the non-veterans one, fee for hospital accommodation 35.7%, fee for operation 16.4%, fee for injection 11.4%, fee for laboratory examination 8.3%. 5. In the comparison of the frequency by Korean standard classification of diseases and distance between the hospital and home, the region under 21.5Km was more frequent in symptoms, signs an abnormal clinical and laboratory findings 56.0%, injury and poisoning and certain other consequences of external causes 55.6%, diseases of the eye and adnexa 52.9%, the one over 21.5Km was more frequent in neoplasms 57.4%, diseases of musculoskeletal system and connective tissue 55.9%, diseases of genitourinary system 53.5%.

• Journal of Yeungnam Medical Science
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• v.14 no.1
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• pp.245-261
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• 1997

Slipped capital femoral epiphysis(SCFE) is a disorder in which there is a gradual or acute disruption through the capital physeal plate. The physiolysis is through a widened zone of hypertrophy, which is weakened due to altered chondrocytic maturation and endochondral ossification. The cause or causes of SCFE remain uncertain. The association of obesity and adolescent age with growth rate are predisposing factors. The possibility that most patients with subclinical hormonal abnormality were proved. The goal of treatment of slipped capital femoral epiphysis is to restore the function of the hip and delay the development of degenerative osteoarthrosis by prevention of additional displacement of the epiphysis. We report 10 patients(12hips) with SCFE who were treated by surgical means and followed along for more than one year, at Yeungnam University Hospital, from 1989 to 1996. There were six boys and four girls. The average age at operation was 11.8 years. Seven cases occurred in the left hip, one case in the right and 2 cases had bilateral involvement, five cases had a history of minor trauma on affected hip. Among hormonally studied six patients, panhypopituitarism patient was one case; decreased testosterone, two; decreased growth hormone, two; and decreased thyroid hormone, one. According to clinical stage, two cases were the acute type; five cases, acute on chronic type; and three cases, chronic type. On the radiological grades of slipping, mild slippage were nine hips; moderate, one; and severe, two. The eleven hips were treated by pin fixation in situ, and one, by cuneiform osteotomy. On the average follow-up of 2.6 years, ten hips were excellent or good functional results, two hips were failure.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• Korean Journal of Food Science and Technology
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• v.34 no.6
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• pp.977-983
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• 2002

This study was performed to establish the precise and rapid method to distinguish croakers through the pigment analysis of colored imported white croakers for adultration. We surveyed the coloring behaviors, extraction test by water and organic solvent and using pigments such as targeting, curcumine, and azo dye products. The pigment of yellow croaker is not stained on wet cloth or tissue which is rubbed on epidermis of yellow croaker and was not eluted in water extraction test, while adulterated pigments were easily extracted by water and acetone, but edible diluted yellow, Yellow No. 4 and Yellow No. 5 were not extracted. Reactive pigment was detected easily by extraction with water and dispersed pigment was also detected by extraction test. As a result of discoloring characteristics of carotene having similar structure to yellow croaker and azo dye by oxidation and reduction, azo dyes were not discolored by oxidation with sodium percarbonate or peracetic acid but that were discolored by oxidation with Fenton reagent after 1hr and by hypochlorite promptly. On the other hand, carotenes were not discolored by sodium precarbonate and Fenton reagent but discolored by sodium hypochlorite after 2 hr and by peracetic acid promptly. Azo dyes were discolored by reduction with sodium hydrosulfite and sodium carbonate but carotenes were not discolored by these reagents. This discoloring test was applicable to detect adulterated pigments and other marine product.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.