• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1986-1991
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• 2007

In this paper, we discussed, intelligent soft filter for MR(magnetoresistive) sensor. Most navigation systems today use some type of compass to determine heading direction. Using the earth's magnetic field, electronic compass based on MR(magnetoresistive) sensors can electrically resolve better then 0.1 degree rotation. Intelligent methode for soft building a one degree compass using MR(magnetoresistive) sensors will also be discussed. Compensation techniques are shown to correct for compass tilt angels and nearby ferrous material disturbances. we proved the fuzzy logic that based on the way the ham deals with inexact information is useful for MR sensors.

• Journal of Biomedical Engineering Research
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• v.31 no.2
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• pp.141-150
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• 2010

The purpose of this study was to analyze the golf swing motion for a soft golf clubs and regular golf club. Soft golf is a newly developed recreational sports for all ages, including the elderly and the beginners of golf. To quantify the effect of using soft golf club, which much lighter club than regular clubs, a motion analysis has been performed using a 3D optoelectric motion tracking system that utilizes active infrared LEDs and near-infrared sensors. The subject performed swing motion using a regular golf club and a soft golf club in turn. The obtained motion capture data was used to build a 3D computer simulation model to obtain left wrist, elbow shoulder and lumbar joint force and torque using inverse and forward dynamics calculations. The joint force and torque during soft golf swing were lower than regular golf swing. The analysis gave better understanding of the effectiveness of the soft golf club.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4774-4796
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• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.51-54
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• 2000

We are concerned with processing methods of the measurement values of sensors in the control system. When some faults happen to sensor components, the measurement value of sensors cause the malfunction of the plant. So it is necessary to detect and reduce the influence of faults to control with reliability for the overall system. The sensor status must be always good for best demonstration of the controller performance. A self-validating sensor detects the sensor state from the measurement value, reconstruct a soft sensor and can improve reliability of the sensor. If sensor faults, the sensor is detected and reconstructed with the best estimate from its correlation to other sensors and historical data. It is applied to the control of a flexible link system with the sensor fault problems in the light sensor module for position to show the applicability. In this paper, we propose a digital controller which reduces deflection of the moving set-point by reconstructing output of a sensor when the sensor fault is detected.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.257-260
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• 2007

인간의 행위에는 외부환경으로부터 감각정보가 입력되어 반응되는 무의식적인 행동과 뇌에 의한 추론과 인지에 의한 행동으로 분류할 수 있다. 동일한 환경 조건하에서의 인간 행위분류의 통해 활용 적합한 응용프로그램을 개발하여 적용하여 본다. 본 논문에서는 인간의 몸에 부착하여 움직임을 데이터로 분석할 수 있도록 행동인식 시스템을 개발하였다. 인간행동의 인식패턴을 분류하기 위해 Soft-Computing Algorithm을 행위 추출센서에 적용시킨 단독 시스템을 개발하여 센서모듈로부터 인간의 행동 패턴을 분류할 수 있도록 한다. 이러한 센서모듈은 3축 각속도 및 가속도 센서를 부착시킨 모듈로 Micro-Processor를 사용하여 모듈을 구성하였으며, 구축된 모듈은 인간의 몸에 착용하여 인간의 움직임을 디지털 데이터로 변환된다. 변환된 데이터를 무선통신을 통해 워크스테이션에 전달되어 인간행위에 대한 패턴분류 알고리즘 처리가 가능하며, 추출된 데이터를 기반으로 인간의 행동분석과 교정이 이루어 질 수 있도록 한다. 본 논문에서의 최종 시나리오는 운전자의 행동패턴을 이용한 행동 감지 및 서비스 시스템을 구성하는 데에 목적을 둔다.

• Ceramist
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• v.22 no.1
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• pp.4-16
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• 2019

Recently, wearable sensors have received considerable attention in a variety of research fields and industries as the importance of wearable healthcare systems, soft robotics and bio-integrated devices increased. However, expensive and complex processes are hindering the commercialization of wearable sensors. Nanoparticle presents some of solutions to these problems as its adjustable for processability and tunable properties. In this paper, the recent development of nanoparticle based pressure and strain sensors was reviewed, and a discussion on their strategies to overcome the conventional limitation and operating principles is presented.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.403-410
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• 2022

Flexible and wearable sensing technologies have emerged as a result of developments in interdisciplinary research across several fields, bringing together various subjects such as biology, physics, chemistry, and information technology. Moreover, various types of flexible wearable biocompatible devices, such customized medical equipment, soft robotics, bio-batteries, and electronic skin patches, have been developed over the last several years that are extensively employed to monitor biological signals. As a result, we present an updated overview of new bio-implantable sensor technologies for various applications and a brief review of the state-of-the-art technologies.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.389-393
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• 2007

Soft ferromagnetic materials are very useful for many sensors using magnetic materials demanding high permeability, low coercivity and low hysteresis loss. Among them, FeCoSiBNi amorphous magnetic films show a good impedance change (about 5.01 %/Oe, at 10 MHz) by the exterinal magnetic field in this experiment. The magnetic films are produced by melt-spun method, one of the rapid solidification process. Ribbon shape wires were made from the films, and let them annealed in DC magnetic field to increase the maximum Giant Magneto Impedance ratio. Field annealing decreases the stress and changes the effective anisotropy. Thus, we can find that the impedance change (200.47 %) is improved and the fabricated magnetic wire has characteristics of good sensor element.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.5
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• pp.320-331
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• 2023

In this study, a model test was conducted using the soft-mooring technique to evaluate the added resistance of the ship in waves. The study also examined the specific factors that should be considered during the soft-mooring test. The main purpose of soft-mooring is to prevent drifting caused by waves by providing horizontal restoring forces. However, it can also create undesired restoring forces in the vertical direction. Therefore, we examined the restoring force of the ship's 6-DOF motion based on the arrangement of the soft-mooring and the height of the mooring connection point. We also checked the corresponding resonance period and drift distance. The soft-mooring test was conducted twice, once with self-propulsion and once without self-propulsion, allowing us to review the advantages and disadvantages of each test technique. The main parameters measured in these model tests were 6DOF motion and added resistance on the ship. We compared these measurements obtained from two different techniques (with and without self-propulsion). Additionally, we also compared the measurements based on the types of measuring sensors used (2D load cells on FP, AP, and 1D load cells on each mooring line) as well as the height of the mooring connection point.