• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.163-169
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• 2016

To establish the equitable distribution of total energy load, a representative cluster based routing protocol LEACH selects cluster heads randomly in accordance with the pre-determined probability every round. But because the current energy level of sensor nodes is not considered, if a sensor node which has little residual energy is elected as a cluster head, it can not live to fulfil the role of cluster head which has big energy load. As a result, the first time of death of a node is quickened and the service quality of WSN gets worse. In this regard we propose a new routing method that, by considering the current energy of a cluster head and the distance between cluster heads and a base station, selects the sub cluster head for saving the energy of a cluster head. Simulation results show that the first time of death of a node prolongs, more data arrive at the base station and the service quality of WSN improves.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.93-110
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• 2022

The purpose of this study is to explore business investment and operation of O2O (Online-To-Offline) combined service. The study will analyze the necessary factors for growing the business by dividing the O2O service by industry. The Online-to-Offline is a method of inducing purchases of products and services by connecting between online and offline This research methodology organized the four stages of the analysis process. The analysis of all stages was performed with association rules in big data techniques. It is divided into the start-up period, growth period, maturity period, and decline period, and analysis is conducted on the business investment, expenditure cost, business operation, and conflict factors. As the research result, the first analysis has shown commonality with government subsidies, bank loans, and personal funds in all industries. The second analysis showed a lot of expenditure on labor costs of internal employees, marketing/sales, facility facilities, equipment, and equipment purchase costs. The third analysis showed difficulty in raising the investment resources necessary for business operations in all industries. The last analysis showed conflicts in the industry, businesses license, legal systems, and small business owners in all industries. This study contributed to the abundance and diversity of research methodologies in management information systems using association rules. In addition, the description of organizational development theory was updated while explaining the business investment and operation of O2O combined services. In practical implication, the O2O services include environmental factors that cause convergence between industries. Accordingly, this is required for new O2O services through new laws and systems and reorganization of existing laws and regulations.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.85-93
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• 2021

The government is pursuing plans to create new e-government services. In terms of improving business procedures, dBrain (finance), e-people (personnel), and Onnara (electronic payment and business management) have achieved considerable results, and are currently making efforts to improve existing administrative services using newly emerged ICT. Among them, this paper attempted to study whether self-learning-based intelligent administrative services are efficient in the work process of public officials promoting actual work and affect their continued use. Based on individual perceptions and attitudes toward advanced ICTs such as AI, big data, and blockchain, public officials' influences on administrative services were identified and verified using UTAUT variables. They believe that the establishment and introduction of innovative administrative services can be used more efficiently, and they have high expectations for the use and provision of services as ICT develops. In the future, a model will be also applied to citizens

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.168-175
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• 2011

Construction accidents are major problem in Turkish Construction industry and especially fatally rates are very high. Current legislative system on occupational safety in Turkey enforces employers to implement safety measures as well as safety management systems. However level of consciousness in the industry is unsatisfactory and safety are perceived as extra cost and unnecessary expenditure. Moreover, especially in small residential building constructions which have a big share in the industry and unfortunately safety measures to mitigate or abate construction risks do not exist. The study focuses on small residential building construction sites and in the scope of this study, thirty building projects are examined. For each building project, project cost including labour and material costs, service and consultancy costs for mechanical, electrical systems as well as architectural and structural services, costs for supervision and finally general expenditures for construction site facilities were calculated. On the other hand, occupational safety costs for personal protective equipment, collective protective measures, consultancy and training were determined. Work breakdown structures were established and for each work item firstly occupational risks were evaluated and furthermore according to risk scores safety measures to be implemented were defined and related costs were calculated. The study gave results for total safety cost on average, in terms of percentage of total project cost (3.73% of total project cost), safety cost per man-hour (0.40 USD) and safety cost in terms of unit construction area (11.60 USD per square meter). Since safety management is a part of whole project management process, study gives suggestions and techniques to calculate safety costs and implement safety measures as a part of project management service for professionals. Authors believe that suggested approach may easily developed by the usage of more data to establish a model for estimation not only for building construction sites but also for all construction projects.

• Information Systems Review
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• v.22 no.3
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• pp.15-30
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• 2020

In the real estate industry, the latest changes in the Fourth Industrial Revolution, such as big data analytics, machine learning, and VR (virtual reality), combine to bring about industry change. Proptech is a new term combining properties and technology. This study aims to derive and analyze from a comprehensive perspective the quality factors (systems, services, interfaces, information) for mobile real estate brokerage services that are well known and used in the domestic market. The surveys in this study were conducted online and offline and a total of 161 samples were used for statistical analysis. As a result, all hypotheses were approved to except system quality and service quality. The results show that the domestic proptech companies who are mostly focused on real estate brokerage services, peer-to-peer lending, advertising platforms and apartments need to grow in various fields of proptech business of other countries including Europe, USA and China.

• The Korean Journal of Pain
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• v.33 no.2
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• pp.153-165
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• 2020

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

• Journal of Sensor Science and Technology
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• v.21 no.4
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• pp.241-248
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• 2012

Recently healthcare industry such as pharmaceutical, medical device and healthcare service technology is growing significantly. Mobile healthcare has attracted big attention due to IT convergence technology. Paradigm of healthcare has been changed from the 1st generation(communicable disease prevention) and the 2nd generation(treatment of disease due to extended life expectancy) to the 3rd generation(extended life expectancy due to prevention and control). In our study, we suggest the 3rd generation mobile healthcare system using Bluetooth based wearable ECG monitoring system and smart phone technology. The mobile healthcare system consists of wearable shirts with Bluetooth communication module, ECG sensor, battery, and mobile phone. The ECG data is obtained by a miniaturized sensor and the data is transferred to a mobile phone using Bluetooth communication. Then, user can monitor his/her own ECG signal on an application using Android in mobile phone. The Bluetooth communication device is used due to highly reliable data transmission property and the Bluetooth chip is embedded in every mobile phone. The wearable shirts with chest belt of Bluetooth ECG module is designed with a focus on convenience in the daily life of a wearer. The ECG signal evaluation software in Android based mobile phone is developed for the health check and the ECG signal variation is tested according to the activities of the wearer such as walking, climbing stairs, stand up and sit down, and so on.

• Journal of Chest Surgery
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• v.49 no.sup1
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• pp.1-13
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• 2016

Background: The purpose of this study was to investigate longitudinal changes of the utilization of operational and surgical medical care inside and outside a metropolitan area over 10 years, analyzing the residential areas of patients and the locations of medical facilities for major cardiovascular surgery. Methods: Data analysis was conducted by classifying the addresses of patients and the locations of medical care facilities of metropolitan cities and provinces, using data from the National Health Insurance Corporation from January 2003 to December 2013. Results: There is serious concentration of major heart surgery to medical facilities in Seoul; this problem has not improved over time. There were differences in percentages of surgical procedures performed in the metropolitan areas according to major diseases. In the case of Busan and Daegu provinces, at least 50% of the patients underwent surgery in medical facilities in the city, but there are other regions where the percentage is less than 50%. In the case of provinces, the percentage of surgical procedures performed in medical facilities in Seoul or nearby metropolitan cities is very high. Conclusion: Policies to strengthen the regional capabilities of heart surgery and to secure human resources are required to mitigate the concentration of patients in the capital area. Many regional multi-centers must be designated to minimize unnecessary competition among regional university hospitals and activate a win-win partnership model for medical services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.453-462
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• 2016

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.