• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.110-119
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• 2005

In this paper, a new detection algorithm was proposed for finding the position of lenslet array spot pattern used to acquire laser wavefront. Based on the analysis of the required signal processing characteristics, we categorized into and designed four main signal processing functions. The proposed was designed in order to have robust feature against a variation of geometrical form of the spot and also implemented to have semi-automatic thresholding capability based on CCD noise analysis. For performance evaluation, we made qualitative and quantitative comparisons with Carvalho's algorithm which has been published in recent. In the given experimental spot images, the proposed could detect the spots which has 1/3 times lower than the least S/N of which Carvalho's can detect and could reach to a detection precision of 0.1 pixel at the S/N. In functional aspect, the proposed could separate all valid spots locally. From these results, the proposed could have a superior precision of location detection of spot pattern in wider S/N range.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.441-444
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• 2008

This paper describes the development of a circularly polarized microstrip antenna, as a part of the Circularly Polarized Synthetic Aperture Radar (CP-SAR) sensor which is currently under developed at the Microwave Remote Sensing Laboratory (MRSL) in Chiba University. CP-SAR is a new type of sensor developed for the purpose of remote sensing. With this sensor, lower-noise data/image will be obtained due to the absence of depolarization problems from propagation encounter in linearly polarized synthetic aperture radar. As well the data/images obtained will be investigated as the Axial Ratio Image (ARI), which is a new data that hopefully will reveal unique various backscattering characteristics. The sensor will be mounted on an Unmanned Aerial Vehicle (UAV) which will be aimed for fundamental research and applications. The microstrip antenna works in the frequency of 1.27 GHz (L-Band). The microstrip antenna utilized the proximity-coupled method of feeding. Initially, the optimization process of the single patch antenna design involving modifying the microstrip line feed to yield a high gain (above 5 dBi) and low return loss (below -10 dB). A minimum of 10 MHz bandwidth is targeted at below 3 dB of Axial Ratio for the circularly polarized antenna. A planar array from the single patch is formed next. Consideration for the array design is the beam radiation pattern in the azimuth and elevation plane which is specified based on the electrical and mechanical constraints of the UAV CP-SAR system. This research will contribute in the field of radar for remote sensing technology. The potential application is for landcover, disaster monitoring, snow cover, and oceanography mapping.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.1
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• pp.1-6
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• 2024

Spiders detect even tiny vibrations through their vibrational sensory organs. Leveraging their exceptional vibration sensing abilities, they can detect vibrations caused by prey or predators to plan attacks or perceive threats, utilizing them for survival. This paper introduces a nanoscale crack-based sensor mimicking the spider's sensory organ. Inspired by the slit sensory organ used by spiders to detect vibrations, the sensor with the cracks detects vibrations and pressure with high sensitivity. By controlling the depth of these cracks, they developed a sensor capable of detecting external mechanical signals with remarkable sensitivity. This sensor achieves a gauge factor of 16,000 at 2% strain with an applied tensile stress of 10 N. With high signal-to-noise ratio, it accurately recognizes desired vibrations, as confirmed through various evaluations of external force and biological signals (speech pattern, heart rate, etc.). This underscores the potential of utilizing biomimetic technology for the development of new sensors and their application across diverse industrial fields.

• Journal of the Microelectronics and Packaging Society
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• v.19 no.1
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• pp.81-87
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• 2012

This paper focuses on three-dimensional measurement system of micro balls on micro Ball-Grid-Array(BGA) packages in-line. Most of visual inspection system still suffers from sophisticate reflection characteristics of micro balls. For accurate shape measurement of them, a specially designed visual sensor system is proposed under the sensing principle of phase shifting moire interferometry. The system consists of a pattern projection system with four projection subsystems and an imaging system. In the projection system, four subsystems have spatially different projection directions to make target objects experience the pattern illuminations with different incident directions. For the phase shifting, each grating pattern of subsystem is regularly moved by PZT actuator. To remove specular noise and shadow area of BGA balls efficiently, a compact multiple-pattern projection and imaging system is implemented and tested. Especially, a sensor fusion algorithm to integrate four information sets, acquired from multiple projections, into one is proposed with the basis of Bayesian sensor fusion theory. To see how the proposed system works, a series of experiments is performed and the results are analyzed in detail.

• Journal of Magnetics
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• v.11 no.2
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• pp.83-86
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• 2006

Controlling magnetic domains in soft underlayer (SUL) of perpendicular magnetic recording (PMR) is an important issue for the application of PMR in HDD. We studied the magnetic domain structures in SUL using the finite element based micromagnetic simulation (FEMM) for the SUL models with different thicknesses. The purpose is to simulate the magnetic domain wall noise when the SUL thickness and saturation magnetization are changed. The simulation results show that a 15 nm SUL forms simpler Neel wall domain wall pattern and 40 nm SUL forms complex Bloch wall. To visualize the effect of these domain walls stray field at a read sensor position, the magnetic stray field of the domain walls at air bearing surface (ABS) which is 50 nm above the SUL was simulated and the results imply that Bloch walls have stronger stray field with more complicated field patterns than Neel walls and this becomes a significant noise source. Therefore, the thickness of the SUL should be controlled to avoid the formation of Bloch walls.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.132-139
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• 2008

The blade vibration problem of bladed disk is the most critical subject to consider since it directly affects the stable performance of the engine as well as life of the engine. Especially, due to complicated vibration pattern of the bladed disk, more effort was required for vibration analysis and test. The research of measuring the vibration of the bladed disk, using NSMS(Non-intrusive stress measurement) instead of Aeromechanics testing method requiring slip ring or telemetry system with strain gauge, was successful. These testing can report the actual stresses seen on the blades; detect synchronous resonances that are the source of high cycle fatigue (HCF) in blades; measure individual blade mis-tuning and coupled resonances in bladed disks. In order to minimize the error being created due to heat expansion, the tip timing sensor is installed parallel to the blade trailing edge, yielding optimal result. Also, when working on finite element analysis, the whole bladed disk has gone through three-dimensional analysis, evaluating the family mode. The result of the analysis matched well with the test result.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.318-320
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localitzation technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• The Journal of Korean Physical Therapy
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• v.25 no.6
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• pp.374-378
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• 2013

Purpose: Human body have biological rhythmic pattern in a day, which is affected by internal and external environmental factors. We investigated whether respiratory function was fluctuated according to the influence of time-of-day (around at 9 am, 1 pm, and 6 pm) in health subjects, using pulmonary function test (PFT). Methods: Eighteen healthy volunteers (8 men, mean ages; $22.4{\pm}1.6$, mean heights; $166.61{\pm}9.60$, mean weight; $59.3{\pm}10.3$) were recruited. Pulmonary function test (PFT) was measured at three time points in day, around 9 am, 1 pm, and 6 pm in calm research room with condition of under 55dB noise level, using a spirometer (Vmax 229, SensorMecis, USA). Forced vital capacity (FVC), forced expiratory volume at one second (FEV1), FVC/FEV1, and peak expiratory flow (PEF) were acquired. Results: In comparison of raw value of PFT among three time points, subjects showed generally better respiratory function at 9 am, than at other points, although no significance was found. In comparison of distribution of ranking for respiratory function in each individual, only PEF showed significant difference. In general, distributional ratio of subjects who showed best performance of respiratory function in a day was high. Conclusion: These findings showed that circadian rhythm by diurnal pattern was not detected on respiratory function throughout all day. But, best performance on respiratory function was observed mostly in the morning, although statistical significance did not exist.