• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1074-1081
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• 2011

As robotics systems are becoming more complex there is the need to promote component based robot development, where systems can be constructed as the composition and integration of reusable building block. One of the most important challenges facing component based robot development is safeguarding against software component failures and malfunctions. The health monitoring of the robot software is most fundamental factors not only to manage system at runtime but also to analysis information of software component in design phase of the robot application. And also as a lot of monitoring events are occurred during the execution of the robot software components, a simple data treatment and efficient memory management method is required. In this paper, we propose an efficient events monitoring and data management method by modeling robot software component and monitoring factors based on robot software framework. The monitoring factors, such as component execution runtime exception, Input/Output data, execution time, checkpoint-rollback are deduced and the detail monitoring events are defined. Furthermore, we define event record and monitor record pool suitable for robot software components and propose a efficient data management method. To verify the effectiveness and usefulness of the proposed approach, a monitoring module and user interface has been implemented using OPRoS robot software framework. The proposed monitoring module can be used as monitoring tool to analysis the software components in robot design phase and plugged into self-healing system to monitor the system health status at runtime in robot systems.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.299-300
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• 2013

의료시장의 무한경쟁과 의료 경영환경을 극복하기 위한 최선의 방안은 병원 업무의 전산화를 통한 시스템 간의 효율적인 정보교환의 필요성이 대두되고 있다. 또한, 처방전달시스템, 전자의무기록시스템, 검사정보시스템, 의료영상 저장 및 전송시스템 등의 이기종간 의료정보 시스템의 통합 시스템을 구축하여 진료환경을 구축하고 진료의 효율성을 개선해야 할 것이다. 본 논문에서는 업무 시스템 간에 상호 연계가 보장된 표준정보연계체계 구축 및 최적화된 응용시스템 구축으로 환자 서비스 개선과 진료 및 경영 효율을 증대시킨 통합의료정보시스템의 구축방안에 대하여 연구하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.35-41
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• 2017

In This Paper, We Propose the Development of a Medical Questionnaire Recognition System using Vision Technology. The Proposed System is Able to Accurately Recognize and Effectively Process a Large Number of Questionnaires used in Community Health Surveys in the Medical and Health Fields. The System Consists of Questionnaire Scanning, Answer Recognition and Error Data Processing, Result Data Verification, Image Storage and DB Construction, and Analysis of Questionnaire Results. Unlike Existing Systems, This System is Free from the Form of Questionnaires used, and Enables Accurate Recognition by Processing Various Markings and Erroneous Markings. Experimental Results Show that the Proposed System has 98.9% Recognition rate.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.203-209
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• 2012

Objective: The aim of this paper is to introduce the roles of H&S(Health and Safety) department and its future directions in the shipbuilding industry. Background: It is necessary to improve the level and quality of Safety & Health department. Method: Various documents and performances involving a shipbuilding company have been reviewed to describe the job of the Safety & Health department. Results: The role of the Safety & Health department has increased and developed in recent domestic industry. Conclusion: The status of the Safety & Health department should be improved by introducing of new systems and skills. Application: These results can be used to provide information for establishing a more effective safety and health organization.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.9-10
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• 2017

본 논문에서 소음, 진동을 이용한 딥러닝 기반 기계 고장진단 임베디드 시스템을 제안하였다. 제안된 시스템은 기계로부터 취득된 소리와 진동을 바탕으로 학습한 DNN모델을 통해 실시간으로 기계 고장을 진단한다. 딥러닝 기술을 사용하여 학습에 따라 적용대상이 변경될 수 있도록 함으로써 특정 기계에 종속적이지 않고 가변적으로 다양한 기계에 대해 고장 예지 및 건전성 관리를 제공하도록 설계하였으며, 이를 증명하기 위해 액추에이터를 환풍기로 설정하여 정상상태와 4가지 비정상상태의 5가지상태를 학습하여 실험한 결과 93%의 정확도를 얻었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.5-6
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• 2021

본 논문에서는 Semi-supervised Learning 방식의 이상감지 방법을 제안한다. 취득한 소음 데이터를 이미지화 시킨 후 Convolution AutoEncoder 학습 방법을 이용하여 모델을 학습한다. 고장 데이터와 정상 데이터 간의 데이터 불균형 문제가 대두되기 때문에 정상 데이터만을 활용한 이상감지는 실제 산업현장의 상황에 알맞게 사용할 수 있을 것이라 기대한다.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.3
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• pp.322-335
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• 2019

Objectives: The goal of this study is to standardize industry, process, and job within work environment measurement information. Methods: We selected 180 work environment measurement reports on 30 industries from a database monitored from 2014 to 2016 by the Korea Industrial Health Association. Ten industrial hygienists, each with over five years of experience in measurement, conducted a primary standardization of 180 reports. Two professional industrial hygienists with more than 20 years of experience each reviewed and revised the results of the primary standardization. We also examined the validity on the usefulness of the standardized database by the two industrial hygienists. Results: The final standardization results were classified into eight major categories, 23 sub-major categories, 39 minor categories, 53 unit categories and 70 sub-unit categories in the Korean Standard Industrial Classification (KSIC) 10th revision. A total of 161 processes were standardized, and there were 148 processes with K2B codes. Standard job was coded into 13 job groups including operator, automobile maintenance, nurse, maintenance, manager, excavating machine operator, forklift driver, radiologist, clinical pathologist, signer, researcher, kitchen assistant, and concrete reinforcement ironworker. Conclusions: Although the standardized information in this study may be only a part of the total information, it can be useful for improvement of the K2B system. Additional research is needed for an ongoing clean-up of data in the K2B and re-calibration and reclassification of standard processes until the future national exposure monitoring system is fully established.

• Interdisciplinary Bio Central
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• v.1 no.2
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• pp.6.1-6.4
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• 2009

We stand at the brink of a fundamental change in how medicine will be practiced. Over the next 5-20 years medicine will move from being largely reactive to being predictive, personalized, preventive and participatory (P4). Technology and new scientific strategies have always been the drivers of revolutions and this is certainly the case for P4 medicine, where a systems approach to disease, new and emerging technologies and powerful computational tools will open new windows for the investigation of disease. Systems approaches are driving the emergence of fascinating new technologies that will permit billions of measurements on each individual patient. The challenge for health information technology will be how to reduce this enormous amount of data to simple hypotheses about health and disease. We predict that emerging technologies, together with the systems approaches to diagnosis, therapy and prevention will lead to a down turn in the escalating costs of healthcare. In time we will be able to export P4 medicine to the developing world and it will become the foundation of global medicine. The "democratization" of healthcare will come from P4 medicine. Its first real emergence will require the unprecedented integration of biology, medicine, technology and computation. as well as societal issues of major importance: ethical, regulatory, public policy, economic, and others. In order to effectively move the P4 scientific agenda forward new strategic partnerships are now being created with the large-scale integration of complementary skills, technologies, computational tools, patient records and samples and analysis of societal issues. It is evident that the business plans of every sector of the healthcare industry will need to be entirely transformed over the next 10 years.and the extent to which this will be done by existing companies as opposed to newly created companies is a fascinating question.

• Quality Improvement in Health Care
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• v.19 no.2
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• pp.14-34
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• 2013

Objectives: The purpose of this study is to provide comprehensive information of qualification systems of developed countries needed to establish our national system for QI(Quality improvement) specialists. Methods: All articles related to any applicable domestic or foreign countries' laws, operational status, and detailed programs for professional qualification system of QI were reviewed. Result: In the United States, a non-profit organization, Healthcare Quality Certification Commission (HQCC) has set the policies, procedures and standards in the field of health care quality. And qualification system of CPHQ (certified professional in healthcare quality) has been operated in order to authenticate the qualifications in the field of quality management. IBQH(international Board for quality in healthcare), a qualification system of experts in the United Kingdom, was designed to assist the qualification of professionals to improve the quality of healthcare. In addition, Health Research Center of Feinberg School of Medicine in Northwestern University has been operating Master's and doctoral degree programs in the field of the quality of care and patient safety and IHI (institute for healthcare improvement) open school was operating a professional training course related to the quality of care and patient safety. Conclusion: Quantity and complexity of information of the quality of care and patient safety have been increased. For reform of the health care system, a special training course of the expertise and leadership are needed. So far, there is no national professional certification courses in our nation. Therefore essential job skill should be acquired individually. For systematic and effective quality improvement activities, the educational and certification system with professional development model are needed.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.364-374
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• 2022

Health information systems (HIS) are facing security challenges on data privacy and confidentiality. These challenges are based on centralized system architecture creating a target for malicious attacks. Blockchain technology has emerged as a trending technology with the potential to improve data security. Despite the effectiveness of this technology, still HIS are suffering from a lack of data privacy and confidentiality. This paper presents a blockchain-based data storage security architecture integrated with an e-Health care system to improve its security. The study employed a qualitative research method where data were collected using interviews and document analysis. Execute-order-validate Fabric's storage security architecture was implemented through private data collection, which is the combination of the actual private data stored in a private state, and a hash of that private data to guarantee data privacy. The key findings of this research show that data privacy and confidentiality are attained through a private data policy. Network peers are decentralized with blockchain only for hash storage to avoid storage challenges. Cost-effectiveness is achieved through data storage within a database of a Hyperledger Fabric. The overall performance of Fabric is higher than Ethereum. Ethereum's low performance is due to its execute-validate architecture which has high computation power with transaction inconsistencies. E-Health care system administrators should be trained and engaged with blockchain architectural designs for health data storage security. Health policymakers should be aware of blockchain technology and make use of the findings. The scientific contribution of this study is based on; cost-effectiveness of secured data storage, the use of hashes of network data stored in each node, and low energy consumption of Fabric leading to high performance.