• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.78-84
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• 2017

Because the 'Internet of Things' and sensor network technology have become a new generation industry competitiveness with a development of Information Communication Technology, each local autonomous entity is trying to adopt a Smart City quickly. This requires an integrated platform inside of a smart city operation center. Established Smart City platform provides various services using CCTV information and ITS transportation information based on a two-dimensional map. The provision of advanced Smart City services will necessitate three-dimensional map information, building and facilities unit information, linked information with public data portal for service to the public. In this paper, the authors reviewed development trends of Smart City integrated platform and proposed mashup methods between BIM/GIS interoperability platform and external open data. BIM/GIS platform can provide spatial information services for indoor and outdoor seamlessly because it was developed based on GIS spatial data with BIM data. The linked external open data are V-World data, Seoul Open Data, and Architectural Data Open. Finally, the authors proposed the direction of development for BIM/GIS integrated platform to provide advanced Smart City services.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.608-611
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• 2003

선진국입을 목전에 둔 한국경제의 발전을 위해서 지식과 기술을 기반으로 한 벤처기업의 생성과 발전은 매우 중요한 요소라 할 수 있다. 민과 관의 적절한 벤처 투자는 미래의 기업가들에게 신지식 창조의 동기를 부여하고 성장, 발전단계에 있는 기업들에게 자본을 공급함으로써 미래의 산업을 창조하는 매우 중요한 활동이다. 국내외적으로 벤처 투자자본에 대한 연구가 활발히 진행되어 왔으나 재무론을 바탕으로 한 벤처투자에 관한 연구와 다양한 벤처투자자본들의 유형과 투자행태 등을 설문지를 통해 밝혀내는 탐색적 연구들에 국한되어 연구, 발표되고 있는 실정이다. 본 연구에서는 벤처자본시장의 대표적 투자자본인 사적 창업투자회사와 정부 벤처정책투자 간의 전략적 상호작용을 가격모델을 통해 고찰하였다. Bertrand paradox의 가정에서 기술한 바와 같이 정부 벤처정책투자간 민간 창업투자회사들과 같은 투자전략을 구사하면 민간 창업투자회사들은 시장에서 살아남기 어렵고 결과적으로 정부는 벤처기업의 생성 및 발전지원이라는 목적에 부합되지 않은 투자를 한 것이 된다. Hotelling(1929)의 위치차별모델이 역설하는 바와 같이 정부 벤처정책투자는 사적 창업투자회사가 지향하는 투자와는 다른 투자정책을 구사할 때만 벤처기업 육성이라는 목표를 효율적으로 수행할 수가 있을 것이다. 이 연구 논문에서는 다양한 투자변수에 대한 Nash Equibrium이 존재함을 증명함으로써 사적 창업투자회사와 정부의 벤처정책투자가 벤처기업의 육성이라는 목적에 맞는 효율적 투자를 하기 위해 취해야 할 투자 전략들을 밝혀내었다.가 있는 것 같다. 따라서 본 연구에서는 웹기반 쇼핑시스템의 확산에 관련된 균형된 분석을 수행하기 위하여 경영(management)과 기술 (technology)을 조화롭게 고려한 관점에서 연구를 수행하고자 한다. 즉, 본 논문에서는 기술적 측면(technical aspect)과 경영적 측면(management aspect)을 동시에 고려하여 웹기반 쇼핑시스템의 주요만 특성을 살펴보고, 향후 정보통신 기술(ICT)의 확산에 관한 연구에서 두 가지 관점의 통합적 중요성에 대하여 강조하고자 한다. 그에 덧붙여 웹기반 쇼핑시스템과 다른 정보시스템을 비교하여 전자상거래 환경에서 웹기반 쇼핑시스템의 주요만 특성들이 두가지 연구관점에서 어떻게 개념화 될 수 있는지를 고찰하고자 한다. 이러만 분석에 기반하여 본 연구에서는 기술적 측면과 경영적인 측면을 동시에 고려한 웹기반 쇼핑시스템의 특성을 제시하고자 한다. 결론적으로 본 연구의 목적은 본 논문에서 적용한 기술(technical)과 경영(management)의 조화로운 연구관점이 향후 정보통신 기술이나 시스템, 그리고 전자상거래에 관련된 일련의 연구에 적응되어 보다 균형잡힌 논의와 분석이 이루어 질 수 있는 시발점이 되길 기대한다.생된 $CH_{4}$를 회수하여 이용하면 대체에너지원으로 활용 가치가 높은 것으로 판단된다./207), $99.2\%$(238/240), $98.5\%$(133/135) 및 $100\%$ (313)였다. 각각 두 개의 요골동맥과 우내흉동맥에서 부

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.426-435
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• 2017

Since online betting occurs on online where anybody can access through internet, thus, the online gambling market has been expanding. Domestic illegal gambling market size is 4 times bigger than that of legal gambling market, and illegal online betting market is rapidly growing as well. Currently online gambling does exist domestically in form of Sports promotion voting rights, also known as, Toto and Proto and internet lottery. However, the need for other types of online gambling to be permitted, expanded and managed has been suggested. This research has analyzed online gambling users, online gambling addicts and general population's awareness on expansion and operation of online gambling, contraction measures of illegal online gambling and operation measures in case of permitted expansion of online gambling. The result of this research's analysis showed that each group has significantly different awareness level on positive and negative effects of permitting online gambling's expansion. Also, it showed that each group has significantly different awareness on permitting expansion of racing betting as a legal gambling item. Since it is the proven fact that illegal online gambling users could turn into legal users and that users could use the service more positively if online gambling is legalized through allowance and expansion process; one could expect the positive effects from permitting expansion of online gambling.

• Knowledge Management Research
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• v.22 no.1
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• pp.309-330
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• 2021

The information security disclosure system (ISDS) has been implemented since 2016 to ensure the protection of stakeholders and the right to know, and to promote voluntary investment in information protection by companies. Regarding the information security disclosure system, there have been studies that urge the implementation of the system, but studies that analyze the contents disclosed after the implementation of the system or suggest improvement directions are few. In this study, the contents of the information security disclosure system that had been announced on the information security industry promotion portal until 2019 were analyzed, the current status was summarized, and the direction of system improvement was suggested. In some cases, companies that disclosed information through the disclosure system increased the number of personnel in charge and obtained certifications related to information security, but did not find any effect on the increase/decrease in investment. The current disclosure system has not been activated because it has difficulty in giving individual companies incentives to disclose. Thus, this study suggests the inclusion of ISDS to information security management system (ISMS), which is currently mandatory for certain companies. In the current disclosure system, it is difficult for the company's stakeholders or customers to check the contents of the disclosure. As a way to do this, a method of including in the contents of the personal information processing policy or the notification of the use of personal information was suggested.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.103-112
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• 2021

In recent years, public bicycle systems are widely spread over the world according to the development of ICT technology. Since the public bicycle systems in large cities need to secure both publicity and convenience for citizens, analysis of various their issues from introduction to operation is required. In addition, it is also necessary to prepare for various scenarios for coexistence with the PM business, which is recently in the spotlight as a last mile means and normally managed privately. This paper introduces modeling and simulation for efficient operations of public bicycle systems. In particular, the proposed method was developed in a form that can be easily used in other cities by modeling the general structure and behavior of the public bicycle system, and it was developed to facilitate modification and expansion of the future model with a component-based model configuration. This paper provides a case study of the propose method, which is the public bicycle simulation in Sejong City. The simulation results were derived by applying the data from the public bicycle system of Sejong City, and they were verified with the associated real data of Sejong City. Using the verified model, it is expected that it can be used as a tool to design and analyze various services on the public bicycle systems, which were especially suitable for Sejong City.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.67-78
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• 2022

Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.

• Science of Emotion and Sensibility
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• v.25 no.2
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• pp.71-78
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• 2022

This study investigates the recommendation for tax accounting services used in many companies. In particular, it aims to create guidelines for small businesses with fewer than 100 employees, which are relatively difficult to manage in terms of cost or time. We surveyed 100 corporate officials on basic business information, such as the number of employees, job titles, and business type, as well as the type of tax accounting service, the recommended score for the service, the reason for the score, and other opinions related to tax accounting services. In particular, the recommendation score seeks to obtain more effective results by using the Net Promoter Score method, which is known to be more effective in understanding customer opinions than general customer satisfaction surveys. The survey revealed a Net Promoter Score for a recommendation of -33 points, lower than the general Net Promoter Score. It also indicated that tax accounting services need improvement. Specifically, the opinions of the respondents who gave a non-recommendation score were as follows: "Not inconvenient or comfortable," "It was just okay," "I don't know if it would be helpful," and "There is no differentiation and there are no special alternatives." We concluded that an improved service for raising recommendation scores was necessary. This survey focused on recommendations for companies with fewer than 100 employees; future studies should incorporate larger companies and more variables.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.