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IPA Analysis of the Components of the Scale-up Entrepreneurial Ecosystem of Startups (스타트업의 스케일업 창업생태계 구성요소의 IPA 분석)

  • Hey-Mi, Yun;Jung-Min, Nam
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.6
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    • pp.25-37
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    • 2022
  • The purpose of this study is to survey startup founders within 7 years of founding the importance and satisfaction of the components of the scale-up entrepreneurial ecosystem at the national level in Korea and analyze the direction of scale-up policy by component using IPA (importance-performance analysis). Since the perception of founders, who are the subjects of the entrepreneurial ecosystem, affects the quantity and quality of start-ups, research is needed to analyze and diagnose the perception of scale-up components. For the development of the national economy and entrepreneurial ecosystem, companies that emerge from startups to scale-up and unicorns must be produced, and for this, elements for the scale-up entrepreneurial ecosystem are needed. The results of this study are as follows. First, the importance ranking of the components of the scale-up entrepreneurial ecosystem recognized by founders was in the order of "Financial support by growth stage," "Support for customized scale-up for enterprises," "Improvement of regulations," "Funds dedicated to scale-up," "large-scale investment," and "nurturing technical talents." Second, the factors that should be intensively improved in the importance-satisfaction matrix in the future were 'Pan-Government Integration Promotion Plan', 'Scale-Up Specialized Organization Operation', 'Company Customized Scale-Up Support', 'Regulatory Improvement', and 'Building a Korean Scale-Up Model'. As a result, various and large financial capital for the scale-up entrepreneurial ecosystem, diversification of scale-up programs by business sector, linkage of start-ups and scale-up support, deregulation of new technologies and new industries, strengthening corporate-tailored scale-up growth capabilities, and providing overseas networking opportunities can be derived. In addition, it is expected to contribute to policy practice and academic work with research that derives the components of the domestic scale-up entrepreneurial ecosystem and diagnoses its perception.

Exploring the Model of Social Enterprise in Sport: Focused on Organization Form(Type) and Task (스포츠 분야 사회적기업의 모델 탐색: 조직형태 및 과제)

  • Sang-Hyun Park;Joo-Young Park
    • Journal of Industrial Convergence
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    • v.22 no.2
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    • pp.73-83
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    • 2024
  • The purpose of this study is to diagnose various problems arising around social enterprises in the sport field from the perspective of the organization and derive necessary tasks and implications. In order to achieve the purpose of the study, the study was largely divided into three stages, and the results were derived. First, the main status and characteristics of social enterprises in the sport field were examined. The current status was analyzed focusing on aspects such as background and origin, legislation and policy, organizational goals, organizational structure and procedures, and organizational characteristics. Social enterprises in the sport sector were in their early stages, and the government's social enterprise policy goal tended to focus on increasing the number of social enterprises in a short period of time through financial input. In addition, it was found that most individual companies rely on government subsidy support due to insufficient profit generation capacity. In the second stage, we focused on the situational factors that affect the functional performance of social enterprises in the sport field. As a result of reviewing the value, ideology, technology, and history of the organization, which are situational factors, it was derived that when certified as a social enterprise in the sport field and supported by the central government or local governments, political control is strong to some extent and exposure to the market is not severe. In the last third step, tasks and implications were derived to form an appropriate organization for social enterprises in the sport field. After the social enterprise ecosystem in the sport sector has been established to some extent, it is necessary to gradually move from the current "government-type" organization to the "national enterprise" organization. This is true in light of the government's limited financial level, not in the short term, but in order for the organization of social enterprises in the sports sector to survive in the long term.

Usefulness of volumetric BMD measurement by using low dose CT image acquired on L-spine Bone SPECT/CT (L-spine Bone SPECT/CT에서 획득된 저선량 CT 영상을 이용한 용적 골밀도 결과의 유용성)

  • Hyunsoo Ko;Soonki Park;Eunhye Kim;Jongsook Choi;Wooyoung Jung;Dongyun Lee
    • The Korean Journal of Nuclear Medicine Technology
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    • v.27 no.2
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    • pp.99-109
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    • 2023
  • Purpose: CT scan makes up for the weak point of the nuclear medicine image having a low resolution and also were used for attenuation correction on image reconstruction. Recently, many studies try to make use of CT images additionally, one of them is to measure the bone mineral density(BMD) using Quantitative CT(QCT) software. BMD exams are performed to scan lumbar and femur with DXA(Dual-Energy X-Ray Absorptiometry) in order to diagnose bone disease such as osteopenia, osteoporosis. The purpose of this study is to identify the usefulness of QCT_BMD analyzed with low dose CT images on L-spine Bone SPECT/CT comparing with DXA_BMD. Materials and Methods: Fifty five women over 50 years old (mean 66.4 ± 9.1) who took the both examinations(L-spine Bone SPECT/CT with SIEMENS Intevo 16 and DXA scan with GE Lunar prodigy advance) within 90 days from April 2017 to July 2022, BMD, T-score and disease classification were analyzed. Three-dimensional BMD was analyzed with low dose CT images acquired on L-spine Bone SPECT/CT scan on Mindways QCT PROTM software and two-dimensional BMD was analyzed on DXA scan. Basically, Lumbar 1-4 were analyzed and the patients who has lesion or spine implants on L-spine were excluded for this study. Pearson's correlation analysis was performed in BMD and T-score, chi-square test was performed in disease classification between QCT and DXA. Results: On 55 patients, the minimum of QCT_BMD was 18.10, maximum was 166.50, average was 82.71 ± 31.5 mg/cm3. And the minimum of DXA-BMD was 0.540, maximum was 1.302, average was 0.902 ± 0.201 g/cm2, respectively. The result shows a strong statistical correlation between QCT_BMD and DXA_BMD(p<0.001, r=0.76). The minimum of QCT_T-score was -5.7, maximum was -0.1, average was -3.2 ± 1.3 and the minimum of DXA_T-score was -5.0, maximum was 1.7, average was -2.0 ± 1.3, respectively. The result shows a statistical correlation between QCT T-score and DXA T-score (p<0.001, r=0.66). On the disease classification, normal was 5, osteopenia was 25, osteoporosis was 25 in QCT and normal was 10, osteopenia was 25, osteoporosis was 20 in DXA. There was under-estimation of bone decrease relatively on DXA than QCT, but there was no significant differences statistically by chi-square test between QCT and DXA. Conclusion: Through this study, we could identify that the QCT measurement with low dose CT images QCT from L-Spine Bone SPECT/CT was reliable because of a strong statistical correlation between QCT_BMD and DXA_BMD. Bone SPECT/CT scan can provide three-dimensional information also BMD measurement with CT images. In the future, rather than various exams such as CT, BMD, Bone scan are performed, it will be possible to provide multipurpose information via only SPECT/CT scan. In addition, it will be very helpful clinically in the sense that we can provide a diagnosis of potential osteoporosis, especially in middle-aged patients.

An Analysis of Web Services in the Legal Works of the Metropolitan Representative Library (광역대표도서관 법정업무의 웹서비스 분석)

  • Seon-Kyung Oh
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.2
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    • pp.177-198
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    • 2024
  • Article 22(1) of the Library Act, which was completely revised in December 2006, stipulated that regional representative libraries are statutory organizations, and Article 25(1) of the Library Act, which was revised again in late 2021, renamed them as metropolitan representative libraries and expanded their duties. The reason why cities and provinces are required to specify or establish and operate metropolitan representative libraries is that in addition to their role as public libraries for public information use, cultural activities, and lifelong learning as stipulated in Article 23 of the Act, they are also responsible for the legal works of metropolitan representative libraries as stipulated in Article 26, and lead the development of libraries and knowledge culture by serving as policy libraries, comprehensive knowledge information centers, support and cooperation centers, research centers, and joint preservation libraries for all public libraries in the city or province. Therefore, it is necessary to analyze and diagnose whether the metropolitan representative library has been faithfully fulfilling its legal works for the past 15 years(2009-2023), and whether it is properly providing the results of its statutory planning and implementation on its website to meet the digital and mobile era. Therefore, this study investigated and analyzed the performance of the metropolitan representative library for the last two years based on the current statutory tasks and evaluated the extent to which it provides them through its website, and suggested complementary measures to strengthen its web services. As a result, it was analyzed that the web services for legal works that the metropolitan representative library should perform are quite insufficient and inadequate, so it suggested complementary measures such as building a website for legal works on the homepage, enhancing accessibility and visibility through providing an independent website, providing various policy information and web services (portal search, inter-library loan, one-to-one consultation, joint DB construction, data transfer and preservation, etc.), and ensuring digital accessibility of knowledge information for the vulnerable.

Exploring the Meaning of Church Lifelong Education Participation Experience through Coaching of Middle-Aged female lay Ministers (중년여성 평신도 사역자의 코칭을 통한 교회평생교육 참여경험 의미탐색)

  • Eunyoung Jeong
    • Journal of Christian Education in Korea
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    • v.77
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    • pp.29-46
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    • 2024
  • Research Purpose : This study originated from a request for education and counseling to reassess the role of middle-aged lay women in the church. The research purpose is to analyze the significance, transformation, and impact of learning participation by investigating how individuals' needs are addressed through a lifelong education program designed as a pilot course. The study aims to examine how middle-aged women who have actively participated in church activities, reflect on their faith, ministry, and life through the church's lifelong education program. Research content and method : The study examines the process in which middle-aged women who have actively collaborated in church activities reflect on their faith, ministry, and lives through church lifelong education programs. The research method involves qualitative research focused on observation journals and interviews. Participants are selected through preliminary interviews based on having over 13 years of church ministry experience and an interest in lifelong education. Data is collected primarily through stories experienced in ministry. The research results are categorized into motivation for participation, learning experiences, and the meaning of participation. Firstly, the motivation for participation was seeking better self through identity restoration and challenges. Secondly, learning experiences were moments of healing and restoration in redesigning oneself. Thirdly, the meaning of participation was relational restoration and expansion. Ultimately, it was found that coaching through church lifelong education facilitated the recovery and transformation of participants' faith and ministry. Conclusion and Recommendation : Church lifelong education through coaching restored and brought about change in the faith and ministry of the research participants. To summarize the meaning of the experience of participating in lifelong learning, it involves: first, 'recognizing the meaning and possibility of one's own development,' second, 'healing and restoration of self-esteem,' third, 'restoration and expansion of relationships,' and finally, 'the discovery of one's true self.' Middle-aged women who have lived a role-centered life rather than focusing on individual faith have a strong desire to live as their complete selves. Therefore, a program should be developed that provides time for individuals to reflect on and diagnose their lives, while also seeking new visions. Therefore, we propose follow-up research with the hope that a variety of coaching-related church lifelong education will be developed and provide practical assistance to numerous lay ministers.

Usefulness of LIFE in diagnosis of bronchogenic carcinoma (기관지 암의 진단에서 형광기관지 내시경검사의 유용성)

  • Lee, Sang Hwa;Shim, Jae Jeong;Lee, So Ra;Lee, Sang Youb;Suh, Jung Kyung;Cho, Jae Yun;Kim, Han Gyum;In, Kwang Ho;Choi, Young Ho;Kim, Hark Jei;Yoo, Se Hwa;Kang, Kyung Ho
    • Tuberculosis and Respiratory Diseases
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    • v.44 no.1
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    • pp.69-84
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    • 1997
  • Background : Although the overall prognosis of patients with lung cancer is poor, highly effective treatment exists for the small subset of patients with early lung cancer(carcinoma in situ/micro- invasive cancer). But very few patients have benefit from them because these lesions are difficult to detect and localize with conventional white-light bronchoscopy. To overcome this problem, a Lung Imaging Fluorescence Endoscopic device(LIFE) was developed to detect and clearly delineate the exact location and extent of premalignant and early lung cancer lesions using differences in tissue autofluorescence. Purpose : The purpose of this study was to determine the difference of sensitivity and specificity in detecting dysplasia and carcinoma between fluorescence imaging and conventional white light bronchoscopy. Material and Methods : 35 patients (16 with abnormal chest X-ray, 2 with positive sputum study, 2 with undiagnosed pleural effusion, 15 with respiratory symptom) have been examined by LIFE imaging system. After a white light bronchoscopy, the patients were submitted to fluorescence bronchoscopy and the findings of both examinations have been classified in 3 categories(class I, II, III). From of all class n and III sites, 79 biopsy specimens have been collected for histologic examination: a comparison between histologic results and white light or fluorescence bronchoscopy has been performed for assessing sensitivity and specificity of the two methods. Results : 1) Total 79 sires in 35 patients were examined. Histology demonstrated 8 normal mucosa, 21 hyperplasia, 23 dysplasia, and 27 microinvasive and invasive carcinoma. 2) The sensitivity of white light or fluorescence bronchoscopy in detecting dysplasia was 60.9% and 82.6%, respectively. 3) The results of this study showed 70.3 % sensitivity for microinvasive or invasive carcinoma with LIFE system, versus 100% sensitivity for white light in 27 cases of carcinoma. The false negative study of LIFE system was 8 cases(3 adenocarcinoma and 5 small cell carcinoma), which were infiltrated in submucosal area and had normal epithelium. Conclusion : To improve the ability 10 diagnose and stage more accurately, fluorescence imaging may become an important adjunct to conventional bronchoscopic examination because of its high detection rate of premalignant and malignant epithelial lesion. But. it has limitation to detect in submucosal infiltrating carcinoma.

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Development of smart education-based teaching and learning plans and a smart textbook for 'healthy diet and meal plans' unit in 「Technology·Home Economics」 (중학교 「기술·가정」의 '건강한 식생활과 식사 구성' 단원에 적용한 스마트 교수·학습 과정안과 교재 개발)

  • Choi, Song Eun;Chae, Jung-Hyun
    • Journal of Korean Home Economics Education Association
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    • v.26 no.4
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    • pp.85-114
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    • 2014
  • The main purpose of this study was to develop teaching and learning plans and a smart textbook for food and nutrition education in Home Economics focusing on 'healthy diet and meal plans' unit in "Technology home Economics" textbooks for 7th graders to evaluate the effectiveness of the instruction conducted with the smart textbook. The content of the study to achieve the purpose is as follows: First, design a smart education-based teaching and learning curriculum for food and nutrition education in Home Economics, focusing on 'healthy diet and meal plans' unit. Second, develop a smart textbook for food and nutrition education based on the teaching and learning curriculum, using a smart content authoring tool. Third, evaluate the effectiveness of the instruction after applying the curriculum in real classroom situations. The results of this study were as follows: First, teaching and learning plans and materials were developed for two units, 'issues regarding teenagers' diet' and 'implementation of a healthy and balanced diet', under 'teenagers' life'. The first unit, 'issues regarding teenagers' diet', dealt with topics such as teenagers' dietary behaviors, nutrition, and health. Learning objectives for this unit were to help students identify and evaluate their own dietary behaviors. The second unit, 'implementation of a healthy and balanced diet', encouraged students to diagnose problems with their diet and plan nutrient rich meals. The objectives for this unit were to help students implement a healthy and balanced diet by providing them with nutrition and dietary guidelines for Koreans, sample meal plans, and guidelines for developing healthy eating habits for teenagers. In order to develop a teaching and learning plans to achieve these objectives, teaching and learning materials including inquiry tasks, materials for group activities, multimedia, applications and various pop-up learning materials were developed. Second, a smart textbook using DocZoom, which was a smart content authoring tool was developed. The textbook dealt with issues regarding teenagers' diet and implementation of a healthy and balanced diet. Multimedia material used in the textbook come from the Ministry of Food and Drug Safety's food and nutrition education web sites and other sources. To develop student-oriented material, relevant video clips were added to the smart textbook to motivate students and enhance their interest in the course. Third, the outcome of this study indicated that the instruction using teaching and learning plans and learning materials with the smart textbook was effective for enhancing students' interest in Home Economics classes (t-value=-3.99, p<.001), creating enthusiasm for learning(t-value = -2.61, p<.05), encouraging self-directed and independent learning(t-value = -4.77, p<.001), and improving students' interest in food and nutrition courses(t-value = -3.83, p<.001). The students' evaluation of the instruction were as follows: the instruction using teaching and learning plans and learning materials with smart textbooks, instead of paper textbooks, helped them save time looking for learning materials; students evaluated that it was easier for them to see and understand video clips and charts. In addition, most students answered that instruction with smart textbooks were more fun and convenient, and they agreed that the courses enhanced their learning experience.

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An Intelligence Support System Research on KTX Rolling Stock Failure Using Case-based Reasoning and Text Mining (사례기반추론과 텍스트마이닝 기법을 활용한 KTX 차량고장 지능형 조치지원시스템 연구)

  • Lee, Hyung Il;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.1
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    • pp.47-73
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    • 2020
  • KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

Customer Behavior Prediction of Binary Classification Model Using Unstructured Information and Convolution Neural Network: The Case of Online Storefront (비정형 정보와 CNN 기법을 활용한 이진 분류 모델의 고객 행태 예측: 전자상거래 사례를 중심으로)

  • Kim, Seungsoo;Kim, Jongwoo
    • 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.

Diagnosis of Obstructive Sleep Apnea Syndrome Using Overnight Oximetry Measurement (혈중산소포화도검사를 이용한 폐쇄성 수면무호흡증의 흡증의 진단)

  • Youn, Tak;Park, Doo-Heum;Choi, Kwang-Ho;Kim, Yong-Sik;Woo, Jong-Inn;Kwon, Jun-Soo;Ha, Kyoo-Seob;Jeong, Do-Un
    • Sleep Medicine and Psychophysiology
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    • v.9 no.1
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    • pp.34-40
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    • 2002
  • Objectives: The gold standard for diagnosing obstructive sleep apnea syndrome (OSAS) is nocturnal polysomnography (NPSG). This is rather expensive and somewhat inconvenient, however, and consequently simpler and cheaper alternatives to NPSG have been proposed. Oximetry is appealing because of its widespread availability and ease of application. In this study, we have evaluated whether oximetry alone can be used to diagnose or screen OSAS. The diagnostic performance of an analysis algorithm using arterial oxygen saturation ($SaO_2$) base on 'dip index', mean of $SaO_2$, and CT90 (the percentage of time spent at $SaO_2$<90%) was compared with that of NPSG. Methods: Fifty-six patients referred for NPSG to the Division of Sleep Studies at Seoul National University Hospital, were randomly selected. For each patient, NPSG with oximetry was carried out. We obtained three variables from the oximetry data such as the dip index most linearly correlated with respiratory disturbance index (RDI) from NPSG, mean $SaO_2$, and CT90 with diagnosis from NPSG. In each case, sensitivity, specificity and positive and negative predictive values of oximetry data were calculated. Results: Thirty-nine patients out of fifty-six patients were diagnosed as OSAS with NPSG. Mean RDI was 17.5, mean $SaO_2$ was 94.9%, and mean CT90 was 5.1%. The dip index [4%-4sec] was most linearly correlated with RDI (r=0.861). With dip index [4%-4sec]${\geq}2$ as diagnostic criteria, we obtained sensitivity of 0.95, specificity of 0.71, positive predictive value of 0.88, and negative predictive value of 0.86. Using mean $SaO_2{\leq}97%$, we obtained sensitivity of 0.95, specificity of 0.41, positive predictive value of 0.79, and negative predictive value of 0.78. Using $CT90{\geq}5%$, we obtained sensitivity of 0.28, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of 0.38. Conclusions: The dip index [4%-4sec] and mean $SaO_2{\leq}97%$ obtained from nocturnal oximetry data are helpful in diagnosis of OSAS. CT90${\leq}$5% can be also used in excluding OSAS.

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