• Title/Summary/Keyword: Adaptive Computing

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Nonlinear Observer-based Control of Synchronous Machine Drive System

  • Sundrica, Marijo;Erceg, Igor;Maljkovic, Zlatko
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1035-1047
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    • 2015
  • Starting from a new dynamic system description novel synchronous machine deterministic observers are proposed. Reduced and full order adaptive observer variations are presented. Based on the feedback linearization control law and the use of deterministic observer a novel control system is built. It meets the requirements of high performance tracking system. Adaptivity to stator and rotor resistance and the torque sensorless application is included. The comparison of the proposed novel control with conventional linear and nonlinear control systems is discussed. The given simulational study includes complete drive system integration.

An U-Healthcare Implementation for Diabetes Patient based on Context Awareness

  • Kim, Jeong-Won
    • Journal of information and communication convergence engineering
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    • v.7 no.3
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    • pp.412-417
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    • 2009
  • With ubiquitous computing aid, it can improve human being's life quality if all people have more convenient medical service under pervasive computing environment. In this paper, for a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee-based sensor network. And as a backend, medical information server accumulates sensing data and performs back-end processing. To simply transfer these sensing values to a medical team may be a low level's medical service. So, we've designed a model with context awareness for more improved medical service which is based on ART(adaptive resonance theory) neural network. Our experiments show that a proposed healthcare system can provide improved medical service because it can recognize current context of patient more concretely.

Detection for JPEG steganography based on evolutionary feature selection and classifier ensemble selection

  • Ma, Xiaofeng;Zhang, Yi;Song, Xiangfeng;Fan, Chao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5592-5609
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    • 2017
  • JPEG steganography detection is an active research topic in the field of information hiding due to the wide use of JPEG image in social network, image-sharing websites, and Internet communication, etc. In this paper, a new steganalysis method for content-adaptive JPEG steganography is proposed by integrating the evolutionary feature selection and classifier ensemble selection. First, the whole framework of the proposed steganalysis method is presented and then the characteristic of the proposed method is analyzed. Second, the feature selection method based on genetic algorithm is given and the implement process is described in detail. Third, the method of classifier ensemble selection is proposed based on Pareto evolutionary optimization. The experimental results indicate the proposed steganalysis method can achieve a competitive detection performance by compared with the state-of-the-art steganalysis methods when used for the detection of the latest content-adaptive JPEG steganography algorithms.

Adaptively Secure Anonymous Identity-based Broadcast Encryption for Data Access Control in Cloud Storage Service

  • Chen, Liqing;Li, Jiguo;Zhang, Yichen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1523-1545
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    • 2019
  • Cloud computing is now a widespread and economical option when data owners need to outsource or share their data. Designing secure and efficient data access control mechanism is one of the most challenging issues in cloud storage service. Anonymous broadcast encryption is a promising solution for its advantages in the respects of computation cost and communication overload. We bring forward an efficient anonymous identity-based broadcast encryption construction combined its application to the data access control mechanism in cloud storage service. The lengths for public parameters, user private key and ciphertext in the proposed scheme are all constant. Compared with the existing schemes, in terms of encrypting and decrypting computation cost, the construction of our scheme is more efficient. Furthermore, the proposed scheme is proved to achieve adaptive security against chosen-ciphertext attack adversaries in the standard model. Therefore, the proposed scheme is feasible for the system of data access control in cloud storage service.

Adaptive data hiding scheme based on magic matrix of flexible dimension

  • Wu, Hua;Horng, Ji-Hwei;Chang, Chin-Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3348-3364
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    • 2021
  • Magic matrix-based data hiding schemes are applied to transmit secret information through open communication channels safely. With the development of various magic matrices, some higher dimensional magic matrices are proposed for improving the security level. However, with the limitation of computing resource and the requirement of real time processing, these higher dimensional magic matrix-based methods are not advantageous. Hence, a kind of data hiding scheme based on a single or a group of multi-dimensional flexible magic matrices is proposed in this paper, whose magic matrix can be expanded to higher dimensional ones with less computing resource. Furthermore, an adaptive mechanism is proposed to reduce the embedding distortion. Adapting to the secret data, the magic matrix with least distortion is chosen to embed the data and a marker bit is exploited to record the choice. Experimental results confirm that the proposed scheme hides data with high security and a better visual quality.

Fault Diagnosis with Adaptive Control for Discrete Event Systems

  • El Touati, Yamen;Ayari, Mohamed
    • International Journal of Computer Science & Network Security
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    • v.21 no.11
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    • pp.165-170
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    • 2021
  • Discrete event systems interact with the external environment to decide which action plan is adequate. Some of these interactions are not predictable in the modelling phase and require consequently an adaptation of the system to the metamorphosed behavior of the environment. One of the challenging issues is to guarantee safety behavior when failures tend to derive the system from normal status. In this paper we propose a framework to combine diagnose technique with adaptive control to avoid unsafe sate an maintain the normal behavior as long as possible.

Network-Adaptive N-Screen Game System on Cloud Computing Environment (클라우드 컴퓨팅 환경에서의 네트워크 적응적 N-스크린 게임 시스템)

  • Ryu, Eun-Seok;Kang, Shin-Jin
    • Journal of Korea Game Society
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    • v.12 no.3
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    • pp.59-68
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    • 2012
  • This paper describes the design and implementation of a network-adaptive N-screen game system to be used in cloud computing. The system we are considering needs to generate game video in a cloud server and transmit the video to multiple game devices over an in-home wireless network via a home game server. It is difficult to support multiple screens which have different resolutions with a single bitstream of game video. Therefore, we developed a new network-adaptive game-video extraction and transmission method using (1) scalable video coding and (2) Raptor code techniques. The simulation, conducted with real game-video, verified the efficiency of the proposed video streaming system.

Information Sharing Model based on Adaptive Group Communication for Cloud-Enabled Robots (클라우드 로봇을 위한 적응형 그룹통신 기반 정보공유 모델)

  • Mateo, Romeo Mark;Lee, Jaewan
    • Journal of Internet Computing and Services
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    • v.14 no.4
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    • pp.53-62
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    • 2013
  • In cloud robotics, the model to share information efficiently is still a research challenge. This paper presents an information sharing model for cloud-enabled robots to collaborate and share intelligence. To provide the efficient message dissemination, an adaptive group communication based on multi-agent is proposed. The proposed algorithm uses a weight function for the link nodes to determine the significant links. The performance evaluation showed that the proposed algorithm produced minimal message overhead and was faster to answer queries because of the significant links compared to traditional group communication methods.

Design of Adaptive-Neuro Controller of SCARA Robot Using Digital Signal Processor (디지털 시그널 프로세서를 이용한 스카라 로봇의 적응-신경제어기 설계)

  • 한성현
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.6 no.1
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    • pp.7-17
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    • 1997
  • During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

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On Improving Convergence Speed and NET Detection Performance for Adaptive Echo Canceller (향상된 수렴 속도와 근단 화자 신호 검출능력을 갖는 적응 반향 제거기)

  • 김남선
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1992.06a
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    • pp.23-28
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    • 1992
  • The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

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