• The Korean Journal of Medicine
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• v.99 no.1
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• pp.37-49
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• 2024

Background/Aims: In Korea, the incidence of primary diffuse large B-cell lymphoma of the central nervous system (PCNSL) is increasing and autologous stem cell transplantation (ASCT) has improved the survival of younger patients. We explored our real-world experience with PCNSL at Asan Medical Center (AMC). Methods: We used the AMC lymphoma registry to collect patient data prospectively. We analyzed 279 patients diagnosed from 2002 until August 2019. Results: The PCNSL incidence at AMC increased progressively and comprised 7.4-8.9% of new non-Hodgkin lymphoma patients annually during the most recent 4 years. The median age was 60 years (range, 17-85) and males comprised 55%. Patients under 65 years of age (n = 183) had no significant differences in characteristics compared to those aged 65 years or over, with the exception of less occipital lobe involvement and lower beta-2 microglobulin levels. Rituximab, methotrexate, procarbazine, and vincristine (R-MPV) combination induction had the best overall response, of 95%. The median overall survival was 3.8 years with 5- and 10-year survival rates of 41.5% and 30.2%, respectively. Survival was better in younger patients and those treated with ASCT. Thiotepa, busulfan, and cytoxan (TBC) conditioning chemotherapy had better survival than other combinations. The International Extranodal Lymphoma Study Group and Memorial Sloan Kettering Cancer Center prognostic score systems were valid in this cohort. Age and performance status were independent prognostic factors. Exclusive extra-central nervous system failure occurred in six patients (5.6%) among 107 failures. Conclusions: The incidence of PCNSL is rising. R-MPV induction therapy followed by ASCT with TBC has improved the survival of young, fit PCNSL patients.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.45-46
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• 2015

Clubroot disease of crucifers has occurred since 1957. It has spread to the whole China, especially in the southwest and nourtheast where it causes 30-80% loss in some fields. The disease has being expanded in the recent years as seeds are imported and the floating seedling system practices. For its effective control, the Ministry of Agriculture of China set up a program in 2010 and a research team led by Dr. Yueqiu HE, Yunnan Agricultural University. The team includes 20 main reseachers of 11 universities and 5 institutions. After 5 years, the team has made a lot of progresses in disease occurrence regulation, resources collection, resistance identification and breeding, biological agent exploration, formulation, chemicals evaluation, and control strategy. About 1200 collections of local and commercial crucifers were identified in the field and by artificiall inoculation in the laboratories, 10 resistant cultivars were breeded including 7 Chinese cabbages and 3 cabbages. More than 800 antagostic strains were isolated including bacteria, stretomyces and fungi. Around 100 chemicals were evaluated in the field and greenhouse based on its control effect, among them, 6 showed high control effect, especially fluazinam and cyazofamid could control about 80% the disease. However, fluzinam has negative effect on soil microbes. Clubroot disease could not be controlled by bioagents and chemicals once when the pathogen Plasmodiophora brassicae infected its hosts and set up the parasitic relationship. We found the earlier the pathogent infected its host, the severer the disease was. Therefore, early control was the most effective. For Chinese cabbage, all controlling measures should be taken in the early 30 days because the new infection could not cause severe symptom after 30 days of seeding. For example, a biocontrol agent, Bacillus subtilis Strain XF-1 could control the disease 70%-85% averagely when it mixed with seedling substrate and was drenching 3 times after transplanting, i.e. immediately, 7 days, 14 days. XF-1 has been deeply researched in control mechanisms, its genome, and development and application of biocontrol formulate. It could produce antagonistic protein, enzyme, antibiotics and IAA, which promoted rhizogenesis and growth. Its The genome was sequenced by Illumina/Solexa Genome Analyzer to assembled into 20 scaffolds then the gaps between scaffolds were filled by long fragment PCR amplification to obtain complet genmone with 4,061,186 bp in size. The whole genome was found to have 43.8% GC, 108 tandem repeats with an average of 2.65 copies and 84 transposons. The CDSs were predicted as 3,853 in which 112 CDSs were predicted to secondary metabolite biosynthesis, transport and catabolism. Among those, five NRPS/PKS giant gene clusters being responsible for the biosynthesis of polyketide (pksABCDEFHJLMNRS in size 72.9 kb), surfactin(srfABCD, 26.148 kb, bacilysin(bacABCDE 5.903 kb), bacillibactin(dhbABCEF, 11.774 kb) and fengycin(ppsABCDE, 37.799 kb) have high homolgous to fuction confirmed biosynthesis gene in other strain. Moreover, there are many of key regulatory genes for secondary metabolites from XF-1, such as comABPQKX Z, degQ, sfp, yczE, degU, ycxABCD and ywfG. were also predicted. Therefore, XF-1 has potential of biosynthesis for secondary metabolites surfactin, fengycin, bacillibactin, bacilysin and Bacillaene. Thirty two compounds were detected from cell extracts of XF-1 by MALDI-TOF-MS, including one Macrolactin (m/z 441.06), two fusaricidin (m/z 850.493 and 968.515), one circulocin (m/z 852.509), nine surfactin (m/z 1044.656~1102.652), five iturin (m/z 1096.631~1150.57) and forty fengycin (m/z 1449.79~1543.805). The top three compositions types (contening 56.67% of total extract) are surfactin, iturin and fengycin, in which the most abundant is the surfactin type composition 30.37% of total extract and in second place is the fengycin with 23.28% content with rich diversity of chemical structure, and the smallest one is the iturin with 3.02% content. Moreover, the same main compositions were detected in Bacillus sp.355 which is also a good effects biocontol bacterial for controlling the clubroot of crucifer. Wherefore those compounds surfactin, iturin and fengycin maybe the main active compositions of XF-1 against P. brassicae. Twenty one fengycin type compounds were evaluate by LC-ESI-MS/MS with antifungal activities, including fengycin A $C_{16{\sim}C19}$, fengycin B $C_{14{\sim}C17}$, fengycin C $C_{15{\sim}C18}$, fengycin D $C_{15{\sim}C18}$ and fengycin S $C_{15{\sim}C18}$. Furthermore, one novel compound was identified as Dehydroxyfengycin $C_{17}$ according its MS, 1D and 2D NMR spectral data, which molecular weight is 1488.8480 Da and formula $C_{75}H_{116}N_{12}O_{19}$. The fengycin type compounds (FTCPs $250{\mu}g/mL$) were used to treat the resting spores of P. brassicae ($10^7/mL$) by detecting leakage of the cytoplasm components and cell destruction. After 12 h treatment, the absorbencies at 260 nm (A260) and at 280 nm (A280) increased gradually to approaching the maximum of absorbance, accompanying the collapse of P. brassicae resting spores, and nearly no complete cells were observed at 24 h treatment. The results suggested that the cells could be lyzed by the FTCPs of XF-1, and the diversity of FTCPs was mainly attributed to a mechanism of clubroot disease biocontrol. In the five selected medium MOLP, PSA, LB, Landy and LD, the most suitable for growth of strain medium is MOLP, and the least for strains longevity is the Landy sucrose medium. However, the lipopeptide highest yield is in Landy sucrose medium. The lipopeptides in five medium were analyzed with HPLC, and the results showed that lipopeptides component were same, while their contents from B. subtilis XF-1 fermented in five medium were different. We found that it is the lipopeptides content but ingredients of XF-1 could be impacted by medium and lacking of nutrition seems promoting lipopeptides secretion from XF-1. The volatile components with inhibition fungal Cylindrocarpon spp. activity which were collect in sealed vesel were detected with metheds of HS-SPME-GC-MS in eight biocontrol Bacillus species and four positive mutant strains of XF-1 mutagenized with chemical mutagens, respectively. They have same main volatile components including pyrazine, aldehydes, oxazolidinone and sulfide which are composed of 91.62% in XF-1, in which, the most abundant is the pyrazine type composition with 47.03%, and in second place is the aldehydes with 23.84%, and the third place is oxazolidinone with 15.68%, and the smallest ones is the sulfide with 5.07%.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.165-183
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• 2016

Over the past decade, there has been a rapid diffusion of technological devices and a rising number of various devices, resulting in an escalation of virtual reality technology. Technological market has rapidly been changed from smartphone to wearable devices based on virtual reality. Virtual reality can make users feel real situation through sensing interaction, voice, motion capture and so on. Facebook.com, Google, Samsung, LG, Sony and so on have investigated developing platform of virtual reality. the pricing of virtual reality devices also had decreased into 30% from their launched period. Thus market infrastructure in virtual reality have rapidly been developed to crease marketplace. However, most consumers recognize that virtual reality is not ease to purchase or use. That could not lead consumers to positive attitude for devices and purchase the related devices in the early market. Through previous studies related to virtual reality, there are few studies focusing on why the devices for virtual reality stayed in early stage in adoption & diffusion context in the market. Almost previous studies considered the reasons of hard adoption for innovative products in the viewpoints of Typology of Innovation Resistance, MIR(Management of Innovation Resistant), UTAUT & UTAUT2. However, product-based antecedents also important to increase user intention to purchase and use products in the technological market. In this study, we focus on user acceptance and resistance for increasing purchase and usage promotions of wearable devices related to virtual reality based on headgear products like Galaxy Gear. Especially, we added a variables like attitude confidence as a dimension for user resistance. The research questions of this study are follows. First, how attitude confidence and innovativeness resistance affect user intention to use? Second, What factors related to content and brand contexts can affect user intention to use? This research collected data from the participants who have experiences using virtual rality headgears aged between 20s to 50s located in South Korea. In order to collect data, this study used a pilot test and through making face-to-face interviews on three specialists, face validity and content validity were evaluated for the questionnaire validity. Cleansing the data, we dropped some outliers and data of irrelevant papers. Totally, 156 responses were used for testing the suggested hypotheses. Through collecting data, demographics and the relationships among variables were analyzed through conducting structural equation modeling by PLS. The data showed that the sex of respondents who have experience using social commerce sites (male=86(55.1%), female=70(44.9%). The ages of respondents are mostly from 20s (74.4%) to 30s (16.7%). 126 respondents (80.8%) have used virtual reality devices. The results of our model estimation are as follows. With the exception of Hypothesis 1 and 7, which deals with the two relationships between brand awareness to attitude confidence, and quality of content to perceived enjoyment, all of our hypotheses were supported. In compliance with our hypotheses, perceived ease of use (H2) and use innovativeness (H3) were supported with its positively influence for the attitude confidence. This finding indicates that the more ease of use and innovativeness for devices increased, the more users' attitude confidence increased. Perceived price (H4), enjoyment (H5), Quantity of contents (H6) significantly increase user resistance. However, perceived price positively affect user innovativeness resistance meanwhile perceived enjoyment and quantity of contents negatively affect user innovativeness resistance. In addition, aesthetic exterior (H6) was also positively associated with perceived price (p<0.01). Also projection quality (H8) can increase perceived enjoyment (p<0.05). Finally, attitude confidence (H10) increased user intention to use virtual reality devices. however user resistance (H11) negatively affect user intention to use virtual reality devices. The findings of this study show that attitude confidence and user innovativeness resistance differently influence customer intention for using virtual reality devices. There are two distinct characteristic of attitude confidence: perceived ease of use and user innovativeness. This study identified the antecedents of different roles of perceived price (aesthetic exterior) and perceived enjoyment (quality of contents & projection quality). The findings indicated that brand awareness and quality of contents for virtual reality is not formed within virtual reality market yet. Therefore, firms should developed brand awareness for their product in the virtual market to increase market share.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

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

• Journal of Technologic Dentistry
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• v.17 no.1
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• pp.41-57
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• 1995

This study was conducted to collect and analyze previous information in order to manage efficience, improve experience effect and promote employment rate. The questionnaire interview with 27 chief of dental Laboratory refered clinical experience in technology department about clinical experience in 14 Jumior colleges were also investigated. The results were summarried as follows : The portion of age of 35-39 among chief of dental Laboratory was 40.7% which was the highest, that of male was 96.3%, that of junior college graduate was 97.5%, that of 10years experience was 92.6% and that of ceramic technician was 85.2%, 63.0% dental laboratory for clinical experience was a bore space of 30pyong. Aspect of dental laboratory management, manufacturing all part of prosthetic restoration was 29.6%, othodontic appliance and ceramic restoration was 7.4%, 3.8%, each. The percentage of 40.7 was having connection with 30-3a dental clinics and referring case per day was 10-19 cases(40.7%), manufacturing time of referred prosthetic restoration was 3-4 days(77.8%), places preparing seminar room for education was 29.6%, above a place of 40pyong was 11.1% 30-34 pyong and 35-39 pyong was 7.4% each. During training of 2 years education course student, 18.5% was rack of thorough occupational career. While 44.4% will want the more salary among 3years education course student, 74.1% will expect the more dental techmicians would engaged in their field, 51.9% will hope improve of their theory and practice, 29.6% be expected better skill and 14.8% be expected better theory. Attitude of clinical experience places was distributed by 59.3% of offering only experience chance, 25.9% of wasting time and 29.0% of annoying. The big emphasis of climical experience was thorough occupational career(44.4%). The clinical experience places of our college were selected after direct visiting, so their condition of management was not that bad but most of dental laboratory were poor in management state and working environment. Therefore it is difficult to choose appropriate places and dental Laboratory are also limited manpower and time as suppliers. So that it recommended to induce flexible management of experience period by interval and rotation of experience places among college and to applicate intern-system for employment ant industry-college cooperation aspect.

• Journal of Embryo Transfer
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• v.25 no.1
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• pp.15-20
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• 2010

This study was performed to identify the optimal timing for oocyte donor replacement during OPU procedure. OPU was carried out to collect oocytes from every donor at an interval of $3{\sim}4$ days (2 times a week). The collected oocytes were matured in vitro in TCM-199 supplemented with 10% FBS, 10 mg/ml of FSH and 1 mg/ml of estradiol for 24 h. After 24 h of exposure to sperm, the presumptive zygotes were cultured in CR1aa medium supplemented with 4 mg/ml of BSA for 3 days before being changed to CR1aa medium with 10% of FBS for another $3{\sim}4$ days. The mean numbers of retrieved oocytes were remained constantly up to 3 months ($6.0{\pm}0.5$, $6.2{\pm}0.7$, $5.2{\pm}0.6$), but significantly decreased at over 4 to 6 months ($3.7{\pm}0.5$, $2.8{\pm}0.4$, $1.2{\pm}0.2$) (p<0.05). The blastocyst development potential was also very similar rate from 1 to 3 months (37.2%, 40.4% and 44.6%), but significantly decreased from 4 to 6 months (24.8%, 29.3% and 28.6%, respectively) (p<0.05). The production of OPU derived embryos in periods of 1 to 3 months ($2.2{\pm}0.3$, $2.5{\pm}0.3$ and $2.3{\pm}0.4$) were significantly higher than those in 4 to 6 months ($0.9{\pm}0.2$, $0.8{\pm}0.2$ and $0.3{\pm}0.2$, respectively) (p<0.05). In conclusion, the efficient periods for the production of OPU derived embryos was until 4 months, twice per week to produce over 64 transferable embryos and then replace new donor after 3 months use. The best replacement time is 3 months and could be maximized production of OPU derived embryos.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.77-82
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• 2010

Purpose: As PET/CT come into wide use, it caused increasing of expose in clinical use. Therefore, Korea Food and Drug Administration issued Patient DRL (Diagnostic Reference Level) in CT scan. In this study, to build the basis of patient dose reduction, we analyzed effective dose in transmission scan with CT scan. Materials and Methods: From February, 2010 to March 180 patients (age: $55{\pm}16$, weight: $61.0{\pm}10.4$ kg) who examined $^{18}F$-FDG PET/CT in Asan Medical Center. Biograph Truepoint 40 (SIEMENS, GERMANY), Biograph Sensation 16 (SIEMENS, GERMANY) and Discovery STe8 (GE healthcare, USA) were used in this study. Per each male and female average of 30 patients doses were analyzed by one. Automatic exposure control system for controlling the dose can affect the largest by a patient's body weight less than 50 kg, 50-60 kg less, 60 kg more than the average of the three groups were divided doses. We compared that measured value of CT-expo v1.7 and ImPACT v1.0. The relationship between body weight and the effective dose were analyzed. Results: When using CT-Expo V1.7, effective dose with BIO40, BIO16 and DSTe8 respectably were $6.46{\pm}1.18$ mSv, $9.36{\pm}1.96 $mSv and $9.36{\pm}1.96$ mSv for 30 male patients respectably $6.29{\pm}0.97$ mSv, $10.02{\pm}2.42$ mSv and $9.05{\pm}2.27$ mSv for 30 female patients respectably. When using ImPACT v1.0, effective dose with BIO40, BIO16 and DSTe8 respectably were $6.54{\pm}1.21$ mSv, $8.36{\pm}1.69$ mSv and $9.74{\pm}2.55$Sv for 30 male patients respectably $5.87{\pm}1.09$ mSv, $8.43{\pm}1.89$ mSv and $9.19{\pm}2.29$ mSv for female patients respectably. When divided three groups which were under 50 kg, 50~60 kg and over 60 kg respectably were 6.27 mSv, 7.67 mSv and 9.33 mSv respectably using CT-Expo V1.7, 5.62 mSv, 7.22 mSv and 8.91 mSv respectably using ImPACT v1.0. Weight and the effective dose coefficient analysis showed a very strong positive correlation(r=743, r=0.693). Conclusion: Using such a dose evaluation programs, easier to predict and evaluate the effective dose possible without performing phantom study and such dose evaluation programs could be used to collect basic data for CT dose management.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.12
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• pp.1880-1892
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• 2010

The purposes of this study were to: a) provide evidence concerning the effects of emotional intelligence on job outcomes, b) examine the impacts of emotional intelligence on employee-related variables such as 'job satisfaction', 'organizational commitment', 'organizational performance', and 'turnover intention' c) identify the conceptual framework underlying emotional intelligence. A survey was conducted to collect data from foodservice managers (N=231). Statistical analyses were completed using SPSS Win (16.0) for descriptive analysis, reliability analysis, factor analysis, t-test, correlation analysis, cluster analysis and AMOS (16.0) for confirmatory factor analysis and structural equation modeling. The concept of emotional intelligence (EI) has been on the radar screens of many leaders and managers over the last several decades. The emotional intelligence is generally accepted to be a combination of emotional and interpersonal competencies that influence behavior, thinking and interaction with others. The main results of this study were as follows. The four EI (Emotional Intelligence) dimensions correlated significantly with age. The means of job satisfaction score were above the midpoint (3.04 point) scale. The organizational commitment score was above the midpoint (3.41 point) scale and was higher at 'loyalty' factor than 'commitment' factor. The means of organizational performance score were above the midpoint (3.34) scale. The correlations among the four EI (emotional intelligence) factors were significant with job satisfaction; organizational commitment, organizational performance and turnover intention. The test of hypothesis using structural equation modeling found that emotional intelligence produced positive effects on job attitude and job performance. Emotional intelligence enhanced organizational commitment, and in turn, managers' attitude produced positive effects on organizational performance; emotional intelligence also had a direct impact on organizational performance. This study has identified the effect of emotional intelligence on organizational performance and attitudes toward one's job.