• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Chest Surgery
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• v.39 no.9 s.266
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• pp.692-698
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• 2006

Background: Owing to the fact that the average life span has increased and the progress in medical science has been made, the number of patients with chronic renal failure (CRF) who have to take hemodialysis (HD) has been going up gradually. Accordingly, it is considered to be as a significant issue to obtain blood vessels which can be used repetitively and supply enough blood flows. Therefore, there have been various kinds of study on an inosculation rate andfactors influencing it following an arteriovenous fistula (AV fistula) and lots of studies are ongoing for the purpose of escalating the inosculation rate. The authors analyzed the effects of short-term result, age, sex, diabetes and hypertension on arteriovenous inosculations in 134 anatomical snuffbox operated subjects among the patients who have taken an AV fistula at this center. Material and Method: Based on 134 patients who underwent an AV fistula at the department of thoracic surgery of this center from July, 2000 to May, 2004, the difference in arteriovenous inosculation rate was compared and analyzed depending or age (discriminated by 65-year-old), sex and the condition of the presence or absence of diabetes and hypertension. Correlation analyses were conducted for each parameter and statistical tests were performed by using SPSS for windows Release 11.0.1, which were determined to be statistically significant if p value was below 0.05. Result: The total number of operations was 169 including 35 of re-operations. The male/female rate was 70 : 64 (52% : 48%). The average age was $56.3{\pm}12.26$ years and there were 33 (24%) old aged patients above 65-year-old; there were 103 (71%) patients with hypertension and 90 (67%) patients with diabetes. Overall arteriovenous inosculation rate was $93{\pm}2.4%,\;91{\pm}2.7%,\;89{\pm}3.0%$ at 6, 12, 24 months, respectively. The arteriovenous inosculation rate of above 65-year-old patient group was $85{\pm}4.8%,\;80{\pm}5.8%,\;80{\pm}5.8%$ and below 64-year-old patient group's was $85{\pm}4.8%,\;80{\pm}5.8%,\;80{\pm}5.8%$ at given time points, respectively, which showed higher inosculation rate in below 64-year-old patient group with a statistical significance (p=0.0034). However, no statistical significance was found between the patients with hypertension and diabetes and the patients with no complication. In addition, there was no statistical significance in inosculation rate between male and female. Conclusion: The arteriovenous inosculation ratewas higher in the treated patient below 64-year-old than in the treated patient above 65-year-old. Thus it is advantageous for increase in long-term inosculation rate to obtain hemodialysis routes at an early age. The conditions of sex and the presence or absence of diabetes and hyper- tension do not make statistically significant effect on the arteriovenous inosculation rate.

• Journal of the Korean Vacuum Society
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• v.15 no.6
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• pp.563-575
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• 2006

Ti(C,N) films are synthesized by pulsed DC plasma enhanced chemical vapor deposition (PEMOCVD) using metal-organic compounds of tetrakis diethylamide titanium at $200-300^{\circ}C$. To compare plasma parameter, in this study, $H_2$ and $He/H_2$ gases are used as carrier gas. The effect of $N_2\;and\;NH_3$ gases as reactive gas is also evaluated in reduction of C content of the films. Radical formation and ionization behaviors in plasma are analyzed in-situ by optical emission spectroscopy (OES) at various pulsed bias voltages and gas species. He and $H_2$ mixture is very effective in enhancing ionization of radicals, especially for the $N_2$. Ammonia $(NH_3)$ gas also highly reduces the formation of CN radical, thereby decreasing C content of Ti(C, N) films in a great deal. The microhardness of film is obtained to be $1,250\;Hk_{0.01}\;to\;1,760\;Hk_{0.01}$ depending on gas species and bias voltage. Higher hardness can be obtained under the conditions of $H_2\;and\;N_2$ gases as well as bias voltage of 600 V. Hf(C, N) films were also obtained by pulsed DC PEMOCYB from tetrakis diethyl-amide hafnium and $N_2/He-H_2$ mixture. The depositions were carried out at temperature of below $300^{\circ}C$, total chamber pressure of 1 Torr and varying the deposition parameters. Influences of the nitrogen contents in the plasma decreased the growth rate and attributed to amorphous components, to the high carbon content of the film. In XRD analysis the domain lattice plain was (111) direction and the maximum microhardness was observed to be $2,460\;Hk_{0.025}$ for a Hf(C,N) film grown under -600 V and 0.1 flow rate of nitrogen. The optical emission spectra measured during PEMOCVD processes of Hf(C, N) film growth were also discussed. $N_2,\;N_2^+$, H, He, CH, CN radicals and metal species(Hf) were detected and CH, CN radicals that make an important role of total PEMOCVD process increased carbon content.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.33-41
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• 2019

Purpose : To evaluate the effectiveness of Jaw-tracking(JT) technique in Intensity-modulated radiation therapy(IMRT) and Volumetric-modulated arc therapy(VMAT) for radiation therapy of esophageal cancer by analyzing volume dose of perimetrical normal organs along with the low-dose volume regions. Materials and Method: A total of 27 patients were selected who received radiation therapy for esophageal cancer with using $VitalBeam^{TM}$(Varian Medical System, U.S.A) in our hospital. Using Eclipse system(Ver. 13.6 Varian, U.S.A), radiation treatment planning was set up with Jaw-tracking technique(JT) and Non-Jaw-tracking technique(NJT), and was conducted for the patients with T-shaped Planning target volume(PTV), including Supraclavicular lymph nodes(SCL). PTV was classified into whether celiac area was included or not to identify the influence on the radiation field. To compare the treatment plans, Organ at risk(OAR) was defined to bilateral lung, heart, and spinal cord and evaluated for Conformity index(CI) and Homogeneity index(HI). Portal dosimetry was performed to verify a clinical application using Electronic portal imaging device(EPID) and Gamma analysis was performed with establishing thresholds of radiation field as a parameter, with various range of 0 %, 5 %, and 10 %. Results: All treatment plans were established on gamma pass rates of 95 % with 3 mm/3 % criteria. For a threshold of 10 %, both JT and NJT passed with rate of more than 95 % and both gamma passing rate decreased more than 1 % in IMRT as the low dose threshold decreased to 5 % and 0 %. For the case of JT in IMRT on PTV without celiac area, $V_5$ and $V_{10}$ of both lung showed a decrease by respectively 8.5 % and 5.3 % in average and up to 14.7 %. A $D_{mean}$ decreased by $72.3{\pm}51cGy$, while there was an increase in radiation dose reduction in PTV including celiac area. A $D_{mean}$ of heart decreased by $68.9{\pm}38.5cGy$ and that of spinal cord decreased by $39.7{\pm}30cGy$. For the case of JT in VMAT, $V_5$ decreased by 2.5 % in average in lungs, and also a little amount in heart and spinal cord. Radiation dose reduction of JT showed an increase when PTV includes celiac area in VMAT. Conclusion: In the radiation treatment planning for esophageal cancer, IMRT showed a significant decrease in $V_5$, and $V_{10}$ of both lungs when applying JT, and dose reduction was greater when the irradiated area in low-dose field is larger. Therefore, IMRT is more advantageous in applying JT than VMAT for radiation therapy of esophageal cancer and can protect the normal organs from MLC leakage and transmitted doses in low-dose field.

• Korean small business review
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• v.32 no.1
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• pp.65-87
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• 2010

With the advent of knowledge-based society, the revitalization of technological innovation type SMEs, termed "inno-biz" hereafter, has been globally recognized as a government policymakers' primary concern in strengthening national competitiveness, and much effort is being put into establishing polices of boosting the start-ups and innovation capability of SMEs. Especially, in that the inno-biz enables national economy to get vitalized by widening world markets with its superior technology, and thus, taking the initiative of extremely competitive world markets, its growth and development has greater significance. In the case of Korea, the government has been maintaining the policies since the late 1990s of stimulating the growth of SMEs as well as building various infrastructures to foster the start-ups of the SMEs such as venture businesses with high technology. In addition, since the enactment of "Innovation Promotion Law for SMEs" in 2001, the government has been accelerating the policies of prioritizing the growth and development of inno-biz. So, for the sound growth and development of Korean inno-biz, this paper intends to offer effective management strategies for SMEs and suggest proper policies for the government, by researching into the effect of technological innovation capability and technology commercialization capability as the primary business resources on business performance in Korean SMEs in the light of market information orientation. The research is carried out on Korean companies characterized as inno-biz. On the basis of OSLO manual and prior studies, the research categorizes their status. R&D capability, technology accumulation capability and technological innovation system are categorized into technological innovation capability; product development capability, manufacturing capability and marketing capability into technology commercialization capability; and increase in product competitiveness and merits for new technology and/or product development into business performance. Then the effect of each component on business performance is substantially analyzed. In addition, the mediation effect of technological innovation and technology commercialization capability on business performance is observed by the use of the market information orientation as a parameter. The following hypotheses are proposed. H1 : Technology innovation capability will positively influence business performance. H1-1 : R&D capability will positively influence product competitiveness. H1-2 : R&D capability will positively influence merits for new technology and/or product development into business performance. H1-3 : Technology accumulation capability will positively influence product competitiveness. H1-4 : Technology accumulation capability will positively influence merits for new technology and/or product development into business performance. H1-5 : Technological innovation system will positively influence product competitiveness. H1-6 : Technological innovation system will positively influence merits for new technology and/or product development into business performance. H2 : Technology commercializing capability will positively influence business performance. H2-1 : Product development capability will positively influence product competitiveness. H2-2 : Product development capability will positively influence merits for new technology and/or product development into business performance. H2-3 : Manufacturing capability will positively influence product competitiveness. H2-4 : Manufacturing capability will positively influence merits for new technology and/or product development into business performance. H2-5 : Marketing capability will positively influence product competitiveness. H2-6 : Marketing capability will positively influence merits for new technology and/or product development into business performance. H3 : Technology innovation capability will positively influence market information orientation. H3-1 : R&D capability will positively influence information generation. H3-2 : R&D capability will positively influence information diffusion. H3-3 : R&D capability will positively influence information response. H3-4 : Technology accumulation capability will positively influence information generation. H3-5 : Technology accumulation capability will positively influence information diffusion. H3-6 : Technology accumulation capability will positively influence information response. H3-7 : Technological innovation system will positively influence information generation. H3-8 : Technological innovation system will positively influence information diffusion. H3-9 : Technological innovation system will positively influence information response. H4 : Technology commercialization capability will positively influence market information orientation. H4-1 : Product development capability will positively influence information generation. H4-2 : Product development capability will positively influence information diffusion. H4-3 : Product development capability will positively influence information response. H4-4 : Manufacturing capability will positively influence information generation. H4-5 : Manufacturing capability will positively influence information diffusion. H4-6 : Manufacturing capability will positively influence information response. H4-7 : Marketing capability will positively influence information generation. H4-8 : Marketing capability will positively influence information diffusion. H4-9 : Marketing capability will positively influence information response. H5 : Market information orientation will positively influence business performance. H5-1 : Information generation will positively influence product competitiveness. H5-2 : Information generation will positively influence merits for new technology and/or product development into business performance. H5-3 : Information diffusion will positively influence product competitiveness. H5-4 : Information diffusion will positively influence merits for new technology and/or product development into business performance. H5-5 : Information response will positively influence product competitiveness. H5-6 : Information response will positively influence merits for new technology and/or product development into business performance. H6 : Market information orientation will mediate the relationship between technology innovation capability and business performance. H7 : Market information orientation will mediate the relationship between technology commercializing capability and business performance. The followings are the research results : First, as for the effect of technological innovation on business performance, the technology accumulation capability and technological innovating system have a positive effect on increase in product competitiveness and merits for new technology and/or product development, while R&D capability has little effect on business performance. Second, as for the effect of technology commercialization capability on business performance, the effect of manufacturing capability is relatively greater than that of merits for new technology and/or product development. Third, the mediation effect of market information orientation is identified to exist partially in information generation, information diffusion and information response. Judging from these results, the following analysis can be made : On Increase in product competitiveness, directly related to successful technology commercialization of technology, management capability including technological innovation system, manufacturing capability and marketing capability has a relatively strong effect. On merits for new technology and/or product development, on the other hand, capability in technological aspect including R&D capability, technology accumulation capability and product development capability has relatively strong effect. Besides, in the cast of market information orientation, the level of information diffusion within an organization plays and important role in new technology and/or product development. Also, for commercial success like increase in product competitiveness, the level of information response is primarily required. Accordingly, the following policies are suggested : First, as the effect of technological innovation capability and technology commercialization capability on business performance differs among SMEs; in order for SMEs to secure competitiveness, the government has to establish microscopic policies for SMEs which meet their needs and characteristics. Especially, the SMEs lacking in capital and labor are required to map out management strategies of focusing their resources primarily on their strengths. And the government needs to set up policies for SMEs, not from its macro-scaled standpoint, but from the selective and concentrative one that meets the needs and characteristics of respective SMEs. Second, systematic infrastructures are urgently required which lead technological success to commercial success. Namely, as technological merits at respective SME levels do not always guarantee commercial success, the government should make and effort to build systematic infrastructures including encouragement of M&A or technology trade, systematic support for protecting intellectual property, furtherance of business incubating and industrial clusters for strengthening academic-industrial network, and revitalization of technology financing, in order to make successful commercialization from technological success. Finally, the effort to innovate technology, R&D, for example, is essential to future national competitiveness, but its result is often prolonged. So the government needs continuous concern and funding for basic science, in order to maximize technological innovation capability. Indeed the government needs to examine continuously whether technological innovation capability or technological success leads satisfactorily to commercial success in market economic system. It is because, when the transition fails, it should be left to the government.