• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1494-1499
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• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can be used to identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.387-394
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• 1996

This paper presents a Neural Network Identification(NNI) method for modeling of highly complicated nonlinear and time varing human system with a pneumatically driven mock circulatory system of Left Ventricular Assist Device(LVAD). This system consists of electronic circuits and pneumatic driving circuits. The initiation of systole and the pumping duration can be determined by the computer program. The line pressure from a pressure transducer inserted in the pneumatic line was recorded System modeling is completed using the adaptively trained backpropagation learning algorithms with input variables, heart rate(HR), systole-diastole rate(SDR), which can vary state of system. Output parameters are preload, afterload which indicate the systemic dynamic characteristics. Consequently, the neural network shows good approximation of nonlinearity, and characteristics of left Ventricular Assist Device. Our results show that the neural network leads to a significant improvement in the modeling of highly nonlinear Left Ventricular Assist Device.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.134-140
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• 2021

This study relates to the development of a wearable device that can identify a personal location using low-power GPS and IMU based on energy harvesting. The energy harvesting technology using a piezoelectric device was applied for the development of personal location identification, and made it possible to acquire precise personal location data using GPS and IMU. As a result of the experiment, it was confirmed that GPS and IMU data were normally received. The personal location identification device can be prepared for an accident by identifying a personal location in a disaster area, etc., and the user will be able to use it easily regardless of time, place, and environment. It is expected that it can be used in various fields such as leisure and health care.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.260-266
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• 1996

In this paper, we presents neural network identification and control of highly complicated nonlinear Left Ventricular Assist Device(LVAD) system with a pneumatically driven mock circulation system. Generally the LVAD system need to compensate nonlinearities. Hence, it is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with Neural Network Identification. Once the NNI has learned the dynamic model of LVAD system, the other network, called Neural Network Controller(NNC), is designed for control of a LVAD system. The ability and effectiveness of identifying and controlling a LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• Structural Engineering and Mechanics
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• v.15 no.6
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• pp.609-628
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• 2003

Mechanical anchorage devices are generally tested in the laboratory and may be analyzed using the finite element method. These devices are composed of many components interacting through diverse contact interfaces. Generally, a Coulomb friction law is sufficient to take into account friction between smooth surfaces. However, in the case of mechanical anchorages, a gripping system, named herein the wedge-tendon system, is used to anchor the prestressing tendon. The wedge inner surface is made of a series of triangular notches designed to grip the tendon. In this particular case, the Coulomb law is not adapted to simulate the contact interface. The present paper deals with a new constitutive contact/gripping law to simulate the gripping effect. A parameter identification procedure, based on experimental results as well as on a finite element/neural network approach, is presented. It is demonstrated that all parameters have been selected in a satisfactory way and that the proposed constitutive law is well adapted to simulate the wedge gripping effect taking place in a mechanical anchorage device.

• Convergence Security Journal
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• v.19 no.3
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• pp.51-59
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• 2019

In this paper, we propose a device identification system for network visibility that can maintain the secure internal network environment in the IoT era. Recently, the area of enterprise network is getting huge and more complicated. Not only desktops and smartphones but also business pads, barcode scanners, APs, Video Surveillance, digital doors, security devices, and lots of Internet of Things (IoT) devices are rapidly pouring into the business network, and there are highly risk of security threats. Therefore, in this paper, we propose the device identification system that includes the process and module-specific functions to identify the exploding device in the IoT era. The proposed system provides in-depth visibility of the devices and their own vulnerabilities to the IT manager in company. These information help to mitigate the risk of the potential cyber security threats in the internal network and offer the unified security management against the business risks.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.15-21
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• 2008

In this paper, person monitoring and personal identification information management by using the location positioning device and the location management system based on GPS is analysed and developed. Mobile HTE(Mobile HTE : Mobile Home Terminal Equipment) of the developed system uses the module for transmitting PID(Personal Identification Device) information and the module based on GPS's location information. HTE transmits the received information from Mobile HTE to the Location Management System through the internet system. The Location Management System is developed for person location management and information management.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.333-348
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• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.39-46
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• 1998

In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.69-78
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• 2017

As the smartphone-based devices are diffused and developed rapidly, they provide the convenience to the users. The abovementioned sentence technologies are being used not only in the existing sensor and wireless network technology but also in the application services of the diverse fields application services such as smart appliance, smart car, smart health care, etc. and the new fusion paradigm from the industry is presented by undertaking the researches in diverse area by the enterprises and research institutions. However, the smart environment exposes its weaknesses in the mobile terminal area, existing wireless network and IT security area. In addition, due to new and variant ways of attack, not only the critical information are disclosed However also the financial damages occur. This paper proposed the protocol to perform the smartphone-based safe device monitoring and safe communication. The proposed protocol designed the management procedure of registration, identification, communication protocol and device update management protocol and the safety against the attack techniques such as the an-in-the-middle-attack, impersonation attack, credential threat, information leaks and privacy invasion was analyzed. It was observed that the proposed protocol showed the performance improved by approximately 52% in the communication process than the existing system.