• Title/Summary/Keyword: Online data identification system

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A Novel Sensorless Low Speed Vector Control for Synchronous Reluctance Motors Using a Block Pulse Function-Based Parameter Identification

  • Ahmad Ghaderi;Tsuyoshi Hanamoto;Teruo Tsuji
    • Journal of Power Electronics
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    • v.6 no.3
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    • pp.235-244
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    • 2006
  • Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.

PGP Certification System in Blockchain Environments (블록체인 환경에서의 PGP 인증 시스템)

  • Kim, Daehan;Seo, Kyungryong
    • Journal of Korea Multimedia Society
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    • v.23 no.5
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    • pp.658-666
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    • 2020
  • PGP is an encryption software designed to provide information protection, security and authentication services for online communication systems. The characteristic of behavior done on the Internet is that you don't know the other person. It is very important to protect information from someone you cannot trust. So identification of the other person is an important task. PGP uses an digital signature algorithm to verify the identity of the other party. However, it is not accurate to check the other party's credibility. PGP increases trust as other users sign more on public keys of user. In other words, credibility is not perfect. In this paper, PGP certification system that key management in Ethereum blockchain, one of the blockchain platforms, is proposed. Key management in blockchain ensures data integrity, transparency and reliability.

Mechanical Parameter Identification of Servo Systems using Robust Support Vector Regression (Support Vector Regression을 이용한 서보 시스템의 기계적 상수 추정)

  • Cho Kyung-Rae;Seok Jul-Ki;Lee Dong-Choon
    • Proceedings of the KIPE Conference
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    • 2004.07b
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    • pp.738-741
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    • 2004
  • The overall performance of AC servo system is greatly affected by the uncertainties of unpredictable mechanical parameter variations and external load disturbances. Therefore, to compensate this problem, it is necessary to know different parameters and load disturbances subjected to position/speed control. This paper proposes an online identification method of mechanical parameters/load disturbances for AC servo system using Support Vector Regression (SVR). The proposed methodology advocates analytic parameter regression directly from the training data, rather than adaptive controller and observer approaches commonly used in motion control applications. The experimental results demonstrate that the proposed SVR algorithm is appropriate for control of unknown servo systems even with large measurement noise.

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A Study on Big Data Based Non-Face-to-Face Identity Proofing Technology (빅데이터 기반 비대면 본인확인 기술에 대한 연구)

  • Jung, Kwansoo;Yeom, Hee Gyun;Choi, Daeseon
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.10
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    • pp.421-428
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    • 2017
  • The need for various approaches to non-face-to-face identification technology for registering and authenticating users online is being required because of the growth of online financial services and the rapid development of financial technology. In general, non-face-to-face approaches can be exposed to a greater number of threats than face-to-face approaches. Therefore, identification policies and technologies to verify users by using various factors and channels are being studied in order to complement the risks and to be more reliable non-face-to-face identification methods. One of these new approaches is to collect and verify a large number of personal information of user. Therefore, we propose a big-data based non-face-to-face Identity Proofing method that verifies identity on online based on various and large amount of information of user. The proposed method also provides an identification information management scheme that collects and verifies only the user information required for the identity verification level required by the service. In addition, we propose an identity information sharing model that can provide the information to other service providers so that user can reuse verified identity information. Finally, we prove by implementing a system that verifies and manages only the identity assurance level required by the service through the enhanced user verification in the non-face-to-face identity proofing process.

Overview of Human Adaptive Mechatronics and Assist-control to Enhance Human's Proficiency

  • Suzuki, Satoshi;Furuta, Katsuhisa;Harashima, Fumio
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1759-1764
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    • 2005
  • Human Adaptive Mechatronics(HAM) is a new concept which was proposed in our university's research project sponsored by Japanese Ministry of Education, Sports, Culture, Science and Technology(MEXT), and is defined as "intelligent mechanical systems that adapt themselves to the user's skill under various environments, assist to improve the user's skill, and assist the human-machine system to achieve best performance". In this paper, the concept and key-items of HAM are mentioned. And the control strategy to realize a HAM human-machine system is explained in the case of physical-interface system, i.e. haptic system. The proposed assist-control of a force-feedback type haptic system includes online estimation of a operator's control characteristics, and a `force assist' function implemented as a change in the support ratio according to the identified skill level. We developed a HAM-haptic device test system, executed evaluation experiments with this apparatus, and analyzed the measured data. It was confirmed that the operator's skill could be estimated and that operator's performance was enhanced by the assist-control.

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Noble Approach of Linear Entropy based Image Identification (영상 인식자를 위한 선형 엔트로피 기반 방법론)

  • Park, Je-Ho
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.3
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    • pp.31-35
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    • 2019
  • Human beings have been fascinated by the applicability of the medium of photography since the device was first introduced in the thirteenth century to acquire images by attempting primitive and rudimentary approaches. In the 21st century, it has been developed as a wide range of technology that enables not only the application of artistic expression as a method of replacing the human-hand-painted screen but also the planar recording form in the format of video or image. It is more effective to use the information extracted from the image data rather than to use a randomly given file name in order to provide a variety of services in the offline or online system. When extracting an identifier from a region of an image, high cost cannot be avoided. This paper discusses the image entropy-based approach and proposes a linear methodology to measure the image entropy in an effort to devise a solution to this method.

The Design of Remote Monitoring and Warning System for Dangerous Chemicals Based on CPS

  • Kan, Zhe;Wang, Xiaolei
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.632-644
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    • 2019
  • The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

Online Flow Prediction by Kalman Filter (Kalman Filter에 의한 Online 유출예측(流出豫測))

  • Lee, Won Hwan;Rhee, Young Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.6 no.2
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    • pp.57-65
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    • 1986
  • The need of forecasting river flows arised whenever a river authority must make controls to protect the life and property from the flood and maintain the adequate flows for water use. This study is on the real time flood forecasting from the gauged and ungauged rainfall input and identification of second-order autoregressive(AR(2)) which is used as system model. A Kalman filter is used to obtain the values of the system parameters needed for the optimal control strategy. This system model was applied to the data at the Naiu gauging station in Young san river basin to check the accuracy and efficiency of prediction. One step ahead prediction is checked by stochastic analysis and the order of autoregressive model is proved to be satisfied, Discussions on interesting features of the model are presented.

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Estimating Personal and Social Information for Mobile User (모바일 사용자의 개인 및 소셜 정보 추정)

  • Son, Jeong-Woo;Han, Yong-Jin;Song, Hyun-Je;Park, Seong-Bae;Lee, Sang-Jo
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.9
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    • pp.603-614
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    • 2013
  • The popularity of mobile devices provides their users with a circumstance that services and information can be accessed wherever and whenever users need. Accordingly, various studies have been proposed personalized methods to improve accessibility of mobile users to information. However, since these personalized methods require users' private information, they gives rise to problems on security. An efficient way to resolve security problems is to estimate user information by using their online and offline behavior. In this paper, for this purpose, it is proposed a novel user information identification system that identifies users' personal and social information by using both his/her behavior on social network services and proximity patterns obtained from GPS data. In the proposed system, personal information of a user like age, gender, and so on is estimated by analyzing SNS texts and POI (Point of Interest) patterns, while social information between a pair of users like family and friend is predicted with proximity patterns between the users. Each identification module is efficiently designed to handle the characteristics of user data like much noise in SNS texts and missing signals in GPS data. In experiments to evaluate the proposed system, our system shows its superiority against ordinary identification methods. This result means that the proposed system can efficiently reflect the characteristics of user data.

Nonlinear intelligent control systems subjected to earthquakes by fuzzy tracking theory

  • Z.Y. Chen;Y.M. Meng;Ruei-Yuan Wang;Timothy Chen
    • Smart Structures and Systems
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    • v.33 no.4
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    • pp.291-300
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    • 2024
  • Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.