• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.308-317
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• 2009

In the present work, a sensor system composed of an oscillator sensor and a Lamb wave sensor is proposed for the purpose of structural health monitoring. The oscillator sensing system detecting the shift of a structural resonant frequency in proportion to the amount of defects in the structure is a pretty sensitive and simple device, but its detectable range is limited to its local zone. The Lamb wave sensor system, however, is applicable to global detection of the defects. This study is aimed at investigating the feasible combination of the two systems to exploits their merits simultaneously. The scheme to use PZT patches as the oscillator sensor as well as the Lamb wave sensor was proposed to identify the position, length and number of cracks by means of TOF and amplitude of signals, and its validity was confirmed through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2209-2212
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• 2003

In this paper, we propose the method to extract the important frequency bands from the EMG signal, and for generation of feature vector using the important frequency bands. The EMG signal is measured with 4 sensor and is recorded as 4 channel’s time series data. The same frequency bands from 4 channel’s frequency components are selected as the important frequency bands. The feature vector is calculated by the function formed using the combination of selected same important frequency bands. The EMG signals acquired from seven wrist motion type are recognized by changing into the feature vector formed. Then, the extraction and generation is performed by using the double combination of the genetic algorithm (GA) and the neural network (NN). Finally, in order to illustrate the effectiveness of the proposed method, computer simulations are done.

• Journal of KSNVE
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• v.5 no.4
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• pp.483-492
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• 1995

For evaluation of rotational accuracy performance of high speed machine tool spindle system, the characteristics of main spindle and tool motion behavior are presented by means of three point accuracy testing method. The results of experiments and analyses are as follows: (1) The high speed spindle rotational accuracy can be evaluated by the combination of the spindle and tool motion behavior. (2) The spindle motion behavior increases up to more that 4 times the tool motion behavior. (3) For the influence of oil viscosity on spindle and tool taper application, 32 cSt of oil viscosity showed the most satisfactory result for rotational accuracy. (4) In order to improve the rotational accuracy of high speed machine tool spindle system, it is needed to reduce the combination error. This can be achieved by improving the working accuracy and supplying the proper lubrication with contact area at the spindle and tool.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.7-13
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• 2017

We consider a distributed estimation where many nodes remotely placed at known locations collect the measurements of the parameter of interest, quantize these measurements, and transmit the quantized data to a fusion node; this fusion node performs the parameter estimation. Noting that quantizers at nodes should operate in a non-regular framework where multiple codewords or quantization partitions can be mapped from a single measurement to improve the system performance, we propose a low-weight estimation algorithm that finds the most feasible combination of codewords. This combination is found by computing the weighted sum of the possible combinations whose weights are obtained by counting their occurrence in a learning process. Otherwise, tremendous complexity will be inevitable due to multiple codewords or partitions interpreted from non-regular quantized data. We conduct extensive experiments to demonstrate that the proposed algorithm provides a statistically significant performance gain with low complexity as compared to typical estimation techniques.

• Journal of Plant Biotechnology
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• v.41 no.3
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• pp.123-126
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• 2014

This paper is suitable for household plant factory by design and using both energy-saving LED and solar technology. Conventional household plant factory only depending on natural sunlight is sensitive for the change of external environment. Another a big problem of conventional common household plant factory is large power consumption. Recently interest in wellbeing food such as chemical-free is increased abruptly. To solve these two problems, this paper describes hybrid type of household plant. In particular, reducing the power photosynthesis photon flux density (PPFD) is kept uniform to enhance the growth of the plant. Ambient light sensor is adopted for the control of proper combination of sunlight and LED to keep PPFD constant.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.383-386
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• 1993

In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.15-29
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• 2005

Superconducting Gravimeters (SG) are the most sensitive instruments for measuring temporal gravity variations. The gravimeter is an integrating sensor therefore the gravity variations caused by different sources must be separated for studying a special effect by applying different models and data analysis methods. The present reduction methods for gravity variations induced by atmosphere and hydrosphere including the ocean and the detection and determination of the most surface gravity effects are shown. Some examples demonstrate the combination of ground (SG) and space techniques especially the combination of SG with GRACE satellite derived temporal gravity variations. Resulting from the performance of the SG and the applied data analysis methods some proposals are made for future SG applications.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.110-117
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• 2022

This paper describes a localization algorithm utilizing relative observations for multiple autonomous underwater vehicles (Multiple-AUVs). In order to maximize the efficiency of operation and mission accomplishment and to prevent problems such as collision and interference, the locations and directions of Multiple-AUVs must be precisely estimated. To estimate the locations and directions, we designed a localization algorithm utilizing relative observations and verified it with simulations based on sensor data sets acquired through real sea experiments. Also, an optimal combination of relative observation information for efficient localization is figured out through combining various relative observations. The proposed method shows improved localization results compared to those only using the navigation algorithm. The performance of localization is improved up to 58% depending on the combination of relative observations.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.426-428
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• 2003

Optical and microwave remote sensing data have been widely used in land cover and land use classification. Thanks to the spectral absorption characteristics of ground object in visible and near infrared region, optical data enables to extract different land cover types according to their material composition like water body, vegetation cover or bare land. On the other hand, microwave sensor receives backscatter radiance which contains information on surface roughness, object density and their 3-D structure that are very important complementary information to interpret land use and land cover. Separate use of these data have brought many successful results in practice. However, the accuracy of the land use / land cover established by this methodology still has some problems. One of the way to improve accuracy of the land use / land cover classification is just combination of both optical and microwave data in analysis. In this paper for the research, the author used LANDSAT TM scene 127/45 acquired on October 21, 1992, JERS-1 SAR scene 119/265 acquired on October 27, 1992 and aerial photographs taken on October 21, 1992. The study area has been selected in Hanoi City and surrounding area, Vietnam. This is a flat agricultural area with various land use types as water rice, secondary crops like maize, cassava, vegetables cultivation as cucumber, tomato etc. mixed with human settlement and some manufacture facilities as brick and ceramic factories. The use of only optical or microwave data could result in misclassification among some land use features as settlement and vegetables cultivation using frame stages. By combination of multitemporal JERS-1 SAR and TM data these errors have been eliminated so that accuracy of the final land use / land cover map has been improved. The paper describes a methodology for data combination and presents results achieved by the proposed approach.