• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2769-2792
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• 2013

In this paper, we propose an authenticated key agreement scheme, TinyIBAK, based on the identity-based cryptography and bilinear paring, for large scale sensor networks. We prove the security of our proposal in the random oracle model. According to the formal security validation using AVISPA, the proposed scheme is strongly secure against the passive and active attacks, such as replay, man-in-the middle and node compromise attacks, etc. We implemented our proposal for TinyOS-2.1, analyzed the memory occupation, and evaluated the time and energy performance on the MICAz motes using the Avrora toolkits. Moreover, we deployed our proposal within the TOSSIM simulation framework, and investigated the effect of node density on the performance of our scheme. Experimental results indicate that our proposal consumes an acceptable amount of resources, and is feasible for infrequent key distribution and rekeying in large scale sensor networks. Compared with other ID-based key agreement approaches, TinyIBAK is much more efficient or comparable in performance but provides rekeying. Compared with the traditional key pre-distribution schemes, TinyIBAK achieves significant improvements in terms of security strength, key connectivity, scalability, communication and storage overhead, and enables efficient secure rekeying.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• The Journal of Korean Physical Therapy
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• v.27 no.4
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• pp.214-220
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• 2015

Purpose: The purpose of this study was to investigate the availability of software for rehabilitation with the Kinect sensor by presenting an efficient algorithm based on machine learning when classifying the motion data of the PNF pattern if the subjects were wearing a patient gown. Methods: The motion data of the PNF pattern for upper extremities were collected by Kinect sensor. The data were obtained from 8 normal university students without the limitation of upper extremities. The subjects, wearing a T-shirt, performed the PNF patterns, D1 and D2 flexion, extensions, 30 times; the same protocol was repeated while wearing a patient gown to compare the classification performance of algorithms. For comparison of performance, we chose four algorithms, Naive Bayes Classifier, C4.5, Multilayer Perceptron, and Hidden Markov Model. The motion data for wearing a T-shirt were used for the training set, and 10 fold cross-validation test was performed. The motion data for wearing a gown were used for the test set. Results: The results showed that all of the algorithms performed well with 10 fold cross-validation test. However, when classifying the data with a hospital gown, Hidden Markov model (HMM) was the best algorithm for classifying the motion of PNF. Conclusion: We showed that HMM is the most efficient algorithm that could handle the sequence data related to time. Thus, we suggested that the algorithm which considered the sequence of motion, such as HMM, would be selected when developing software for rehabilitation which required determining the correctness of the motion.

• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.397-403
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• 2002

Urine glucose monitoring system is a self-monitoring system that display the glucose level by non-invasive measurement method. In this paper, We developed a noninvasive urine glucose monitoring system that improved defects of urine glucose measurement with a colorimeter method and invasive blood glucose measurement method. This system consist of bio-chemical sensor for urine glucose measurements, signal detecting part, digital and signal analysis part, display part and power supplying part. The developed bio-chemical sensor for the measurement of urine glucose has good reproducibility, convenience of handing and can be mass-produced with cheap price. To evaluate the performance of the developed system, We performed the evaluation of confidence about the detection of glucose level by a comparison between a standard instrument in measuring glucose level and the developed system using standard glucose solutions mixed with urine. Standard error was 2.85282 from the evaluation of confidence based on regression analysis. Also, In analysis of S.D(standard deviation) and C.V(coefficient of validation) that are important parameters to evaluate system using bio-chemical sensor, S.D was 10% which falls under clinically valid value, 15%, and C.V was under 5%. Consequently from the above results, compared to blood glucose measurement, the system performance is satisfactory.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.394-399
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• 2012

In recent years, MEMS sensors show huge attraction in machine condition monitoring, which have advantages in power, size, cost, mobility and flexibility. They can integrate with smart sensors and MEMS sensors are batch product. So the prices are cheap. And the suitability of it for condition monitoring is researched by experimental study. This paper presents a comparative study and performance test of classification of MEMS sensors in target machine fault classification by 3 intelligent classifiers. We attempt to signal validation of MEMS sensor accuracy and reliability and performance comparisons of classifiers are conducted. MEMS accelerometer and MEMS current sensors are employed for experiment test. In addition, a simple feature extraction and cross validation methods were applied to make sure MEMS sensors availabilities. The result of application is good for using fault classification.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.2
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• pp.21-32
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• 2013

This is a preliminary study for the real-time feedback vibration control of building structures. The study developed a wireless acceleration sensor system based on authentic technology capacities, to integrate with the Prototype AMD system and ultimately construct the feedback vibration control system. These systems were used to evaluate the basic performance levels of the control systems within model building structures. For this purpose, the study first developed a wireless acceleration sensor unit that integrates an MEMS sensor device and bluetooth communication module. Also, the study developed an operating program that enables control output based on real-time acceleration response measurement and control law. Furthermore, the Prototype AMD and motor driver system were constructed to be maneuvered by the AC servo-motor. Eventually, all these compositions were used to evaluate the real-time feedback vibration control system of a 2-story model building, and qualitatively measure the extent of vibrational reduction of the target structure within the laboratory validation tests. As a result of the tests, there was a definite vibrational reduction effect within the laboratory validation tests. As a result of the tests, there was a definite vibrational reduction effect within 1st and 2nd resonance frequency as well as the random frequency of the model building structure. Ultimately, this study confirmed the potential of its wireless acceleration sensor system and AMD system as an effective tool that can be applied to the active vibration control of other structures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.6
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• pp.63-71
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• 2006

In this paper, we propose a secure solution for user authentication by using fingerprint verification on the sensor-client-server model, even with the client that is not necessarily trusted by the sensor holder or the server. To protect possible attacks launched at the untrusted client, our solution makes the fingerprint sensor validate the result computed by the client for the feature extraction. However, the validation should be simple so that the resource-constrained fingerprint sensor can validate it in real-time. To solve this problem, we separate the feature extraction into binarization and minutiae extraction, and assign the time-consuming binarization to the client. After receiving the result of binarization from the client, the sensor conducts a simple validation to check the result, performs the minutiae extraction with the received binary image from the client, and then sends the extracted minutiae to the server. Based on the experimental results, the proposed solution for fingerprint verification can be performed on the sensor-client-server model securely and in real-time with the aid of an untrusted client.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.329-336
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• 2016

Deaf people using sign language are experiencing social inequalities and financial losses due to communication restrictions. In this paper, real-time pattern recognition algorithm was applied to distinguish American Sign Language using an armband sensor(8-channel EMG sensors and one IMU) to enable communication between the deaf and the hearing people. The validation test was carried out with 11 people. Learning pattern classifier was established by gradually increasing the number of training database. Results showed that the recognition accuracy was over 97% with 20 training samples and over 99% with 30 training samples. The present study shows that sign language recognition using armband sensor is more convenient and well-performed.

• Journal of Auto-vehicle Safety Association
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• v.12 no.1
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• pp.52-61
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• 2020

In recent years, the increasing interest in health-care requires the industrial products to be well-designed ergonomically. In the commercial vehicle industry, several researchers have demonstrated the driver's posture has great effect on the orthopedic desease such as fatigue, back pain, scoliosis, and so on. However, the existing sensor systems developed for measuring the driver posture in real time have suffered from inaccuracy and low reliability issues. Here, we suggest our smart vehicle seat system capable of real-time driver posture monitoring by using the air bag sensor package with high sensitivity and reliability. The ergonomic numerical model which can evaluate a driver's posture has been developed on the basis of the human body segmentation method followed by simulation-based validation. Our experimental analysis of obtained pressure distribution of a vehicle seat under the different driver's postures revealed our smart vehicle system successfully achieved the driver's real-time posture data in great agreement with our numerical model.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.133-154
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• 2023

Obscured structural members are mostly under-evaluated during condition assessment due to lack of visual inspection capability. Insufficient information about the integrity of these structural members poses a significant risk for public safety. Time domain reflectometry (TDR) is a novel approach in structural health monitoring (SHM). Ordinary coaxial cables "as is" without a major modification are not suitable for SHM with TDR. The objective of this study is to propose a practical and cost-effective modification approach to commercially available coaxial cables in order to use them as a "cable sensor" for damage detection with the TDR equipment for obscured structural members. The experimental validation and assessment of the proposed modification approach was achieved by conducting 3-point bending tests of the model piles as a representative obscured structural member. It can be noted that the RG59/U-6 and RG6/U-4 cable sensors expose higher strain sensitivity in comparison with non-modified "as is" versions of the cables used. As a result, the cable sensors have the capability of sensing both the presence and the location of a structural damage with a maximum aberration of 3 cm. Furthermore, the crack development can be monitored by the RG59/U-6 cable sensor with a simple calibration.