• Title/Summary/Keyword: 개인적 신뢰

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Development of Door Control Unit for the Electric Plug-in Door of Subway Train (전동차 전기식 플러그도어 출입문 제어 장치 개발)

  • Joung, Eui-Jin
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.4
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    • pp.47-53
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    • 2011
  • The Electric Multiple Unit (EMU) has many types of door system such as sliding door, plug door etc.al. according to customer's requirements. The sliding door is widely used in Korea but has weak point in the noise problem. In the low operation speed, the noise coming from outer side of the EMU is not an important factor. As the speed is higher than before, noise is increased and make a problem. The main cause of noise is the imperfect air tightness in the EMU. The plug door system has advantages for the noise reduction characteristic in the high speed area. We have been developing electric plug-in door. The door is controlled by Door Control Unit(DCU) following the order of Automatic Train Protection (ATP) that is a kind of train signalling system. DCU has to simultaneously open and close the doors and the operation of it is related to the passengers safety. So DCU is a safety device that is important to reliability and safety. DCU is composed of several devices of control, motor driving, Input/Output, communication and power. In this paper, we will describe the functions, characteristic, requirement, subsystem and test results of DCU used for the electric plug-in door.

A study of using quality for Radial Basis Function based score-level fusion in multimodal biometrics (RBF 기반 유사도 단계 융합 다중 생체 인식에서의 품질 활용 방안 연구)

  • Choi, Hyun-Soek;Shin, Mi-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.5
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    • pp.192-200
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    • 2008
  • Multimodal biometrics is a method for personal authentication and verification using more than two types of biometrics data. RBF based score-level fusion uses pattern recognition algorithm for multimodal biometrics, seeking the optimal decision boundary to classify score feature vectors each of which consists of matching scores obtained from several unimodal biometrics system for each sample. In this case, all matching scores are assumed to have the same reliability. However, in recent research it is reported that the quality of input sample affects the result of biometrics. Currently the matching scores having low reliability caused by low quality of samples are not currently considered for pattern recognition modelling in multimodal biometrics. To solve this problem, in this paper, we proposed the RBF based score-level fusion approach which employs quality information of input biometrics data to adjust decision boundary. As a result the proposed method with Qualify information showed better recognition performance than both the unimodal biometrics and the usual RBF based score-level fusion without using quality information.

Pedestrian Dead Reckoning based Position Estimation Scheme considering Pedestrian's Various Movement Type under Combat Environments (전장환경 하에서 보행자의 다양한 이동유형을 고려한 관성항법 기반의 위치인식 기법)

  • Park, SangHoon;Chae, Jongmok;Lee, Jang-Myung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.10
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    • pp.609-617
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    • 2016
  • In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

Effects of a Team Facilitation Program on Team Activities in Problem Based Learning (문제중심학습(PBL)에서 팀 활동을 촉진을 위한 퍼실리테이션 프로그램 적용에 대한 융합 연구)

  • Yang, Bok-Sun;Choi, Kyeong-Yoon;Sim, Jeoung-Ha
    • Journal of the Korea Convergence Society
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    • v.10 no.6
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    • pp.299-308
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    • 2019
  • This quasi-experimental study was conducted to develop and implement a team facilitation program as well as to evaluate the effects of the program on Problem Based Learning (PBL) and how these influence on team dynamics. Data were collected in a convenient sample of 126 nursing students (intervention group=69; control group=57). Data were analyzed using χ2 test, T-test, and ANCOVA. SPSS23 was used. The intervention group received the PBL team facilitation program, whereas the control group received a human interaction training. The intervention group than the control group demonstrated significantly higher scores in a team dynamic among team members(F=10.35,p<0.01), trust among team members(F=9.86,p<0.01), communication(F=5.69,p<0.05), learning behavior of a team(F=4.57,p<0.05), and individual capability evaluation(F=5.12,p<0.05). Team performance was not significantly different between groups. This study reveals that the team facilitation program is an effective strategy to maximize the effects of PBL. We propose the need for educational strategy to support team function.

An Efficient and Transparent Blockchain-based Electronic Voting and Survey System (효율성과 투명성을 확보한 블록체인 기반 전자투표 및 설문조사 시스템)

  • Kim, HyeonA;Na, YeonJu;Lee, JaeYun;Jeong, YuRi;Kim, Hyung-Jong
    • Journal of the Korea Society for Simulation
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    • v.30 no.4
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    • pp.9-19
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    • 2021
  • Electronic voting has been recognized as an alternative to complement the limitations of existing paper voting. At the same time, security concerns are being raised. This paper presents a blockchain-based electronic voting and survey system that can guarantee reliability. Our smart contract was created using Solidity on Ethereum which is a blockchain-based distributed computing platform, and the system was implemented in connection with the Javascript based user interface. In addition, in order to protect the personal information of participants, the system is generating hash of the personal data and storing the hash of users for the contract data. Since we exploited different kinds of languages for the system, we derived items of functionality testing and presented the functionality testing result. Moreover, we made use of the Chrome's performance evaluation functionality to see the response time of the blockchain-based system. In addition, we compared the performance with the system which has the same functionality on database. The contribution of this research is design and implementation of blockchain-based electronic voting system and presentation of the functionality and performance simulation result.

A Study on the Possibility of Blockchain Technology Adoption in the Logistics Industry (물류산업 내 블록체인 기술 도입 가능성 연구)

  • Kye, Dong Min;Hur, Sung Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.116-131
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    • 2022
  • With the recent progress of the 4th industrial revolution, the logistics industry is also making efforts to introduce smart logistics, and various attempts are being made to spread logistics informatization, which is the core of smart logistics. Among these, blockchain technology is considered as a technology that will contribute to the spread of logistics informatization and is being applied to various fields. Accordingly, in this study, to discuss the applicability of blockchain technology to the logistics industry, the characteristics of blockchain technology were defined, related cases were reviewed, and a survey was conducted on the possibility of application in the industry. Blockchain technology can be defined as having the characteristics of economic feasibility, speed, transparency in terms of work efficiency, and scalability, decentralization (decentralization), reliability (security) in terms of added value creation. It was confirmed that many are being introduced in the fields of distribution, finance, personal information, and public services. As a result of the survey on the logistics industry, it was confirmed that the level of informatization of the logistics industry had entered the stage of generating profits by using information, but the industry was passive in sharing and utilizing information due to concerns about information leakage. Nevertheless, the awareness and expectation of the need for informatization is high, and it is expected that the informatization of the logistics industry and realizing smart logistics based on it will advance one step further with the introduction of blockchain technology in the future.

Implementation of Responsive Web-based Vessel Auxiliary Equipment and Pipe Condition Diagnosis Monitoring System (반응형 웹 기반 선박 보조기기 및 배관 상태 진단 모니터링 시스템 구현)

  • Sun-Ho, Park;Woo-Geun, Choi;Kyung-Yeol, Choi;Sang-Hyuk, Kwon
    • Journal of Navigation and Port Research
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    • v.46 no.6
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    • pp.562-569
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    • 2022
  • The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

Analysis of Research Trends in New Drug Development with Artificial Intelligence Using Text Mining (텍스트 마이닝을 이용한 인공지능 활용 신약 개발 연구 동향 분석)

  • Jae Woo Nam;Young Jun Kim
    • Journal of Life Science
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    • v.33 no.8
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    • pp.663-679
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    • 2023
  • This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

A Study on the Application of Classic Astrology to Predict Occupational Integrity (직업적성 예측을 위한 고전 점성학 활용방안)

  • Do-Yeon Kim;Ki-Seung Kim
    • Industry Promotion Research
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    • v.8 no.4
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    • pp.221-227
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    • 2023
  • This study is a study to analyze Nativity's occupational aptitude by examining the functions and structures of the planets that make up the Nativity birth chart of Classic Astrology. If the occupation that appears in the birth chart is viewed as an individual's natural occupation, it is analyzed through the strength and weakness of the sign and planets, and the aspect (relationship with the planet). In Classic Astrology's nativity birth chart, there are three major planets when judging occupations: Venus (♀). Mars (♂). It was thought to be determined by Mercury (☿). However, in order to meet the diversity of jobs required in today's highly developed knowledge and information society, there are some shortcomings, so Saturn (♄), Jupiter (♃), Sun (☉), Moon (☽) was added to apply the aptitude for the job. Thus, the native's ASC vocational aptitude could be applied more diversely and broadly based on the relationship between planets and their aspects. As a result, Venus (♀. Venus) means enjoying artistic work that people think is beautiful and making it a pleasure in life, while Mars (♂) means work that requires physical strength and strength, such as working days. Mercury (☿) means using knowledge and brains, and the Sun (☉) plays a role in giving authority to jobs and talents. The Moon (☽) helps the native gain people's trust in his or her profession and talents, Jupiter (♃) helps the native to revive his or her profession and talents through faith, sincerity, fairness, and generosity, and Saturn (♄) can appear as an obstacle that blocks career and talent due to greed, sadness, poverty, etc. As a result of the study, it was found that the native's occupations vary depending on the strengths and weaknesses of the planets and their aspect relationships.

5G Network Resource Allocation and Traffic Prediction based on DDPG and Federated Learning (DDPG 및 연합학습 기반 5G 네트워크 자원 할당과 트래픽 예측)

  • Seok-Woo Park;Oh-Sung Lee;In-Ho Ra
    • Smart Media Journal
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    • v.13 no.4
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    • pp.33-48
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    • 2024
  • With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.