• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Korean Journal of Optics and Photonics
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• v.12 no.2
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• pp.135-142
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• 2001

Recently, plastic optical fiber draws a lot of attention as a new transmission medium for local area network (LAN) and home network applications. As PMMA based GI-POF (Graded Index Plastic Optical Fiber) has very low loss at about 500 nm and 650 nm wavelengths, it is very important to have a compact ultra short optical pulse source at these wavelength windows. In this paper, we have investigated detailed characteristics of gain switched laser system by using a commercially available low cost RF devices and an InGaAlP Fabry Perot semiconductor laser operating at 650 nm wavelength. The shortest optical 'pulse obtained was 33 psec with 1 GHz repetition rate. Depending on the DC bias current and the modulation frequency, the FWHM and the pulse energy of the gain switched pulses show 33.3-82.8 psec and 0.97-9.69 pI respectively. Also, the spectral bandwidths for CW and gain switched operations are 0.44 nm and 1.50 nm. We believe that these results are quite useful for high bit rate optical transmission applications with PMMA based plastic optical fibers in addition to estimate properties of ultra fast optical components and electro-optic devices. vices.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

• Journal of Radiation Protection and Research
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• v.39 no.3
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• pp.150-158
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• 2014

Radiation-related practitioners and radiation-treated patients at medical institutions are inevitably exposed to radiation for diagnosis and treatment. Although standards for maximum doses are recommended by the International Commission on Radiological Protection (ICPR) and the International Atomic Energy Agency (IAEA), more direct and available measurement and analytical methods are necessary for optimal exposure management for potential exposure subjects such as practitioners and patients. Thus, in this study we developed a system for real-time radiation monitoring at a distance that works with existing portable device. The monitoring system comprises three parts for detection, imaging, and transmission. For miniaturization of the detection part, a scintillation detector was designed based on a silicon photomultiplier (SiPM). The imaging part uses a wireless charge-coupled device (CCD) camera module along with the detection part to transmit a radiation image and measured data through the transmission part using a Bluetooth-enabled portable device. To evaluate the performance of the developed system, diagnostic X-ray generators and sources of $^{137}Cs$, $^{22}Na$, $^{60}Co$, $^{204}Tl$, and $^{90}Sr$ were used. We checked the results for reactivity to gamma, beta, and X-ray radiation and determined that the error range in the response linearity is less than 3% with regard to radiation strength and in the detection accuracy evaluation with regard to measured distance using MCNPX Code. We hope that the results of this study will contribute to cost savings for radiation detection system configuration and to individual exposure management.

• The Journal of Korean Society for Radiation Therapy
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• v.15 no.1
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• pp.11-18
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• 2003

The concrete is usually used to build a radiation therapy facility and the enough concrete thickness for high energy x-ray beam is about 1 meter. But if the space is not enough to build a radiation therapy facility with concrete, the substitute for concrete is needed, and the Ledite can be a good substitute for concrete. In this study, we compared the Ledite with the concrete. The comparing list are the needed shielding thickness, the period of construction and the cost.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.28-34
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• 2012

Various feature extraction algorithms are widely applied to real-time image processing applications for extracting significant features from images. Feature extraction algorithms are mostly combined with image processing algorithms mostly for image tracking and recognition. Feature extraction function is used to supply feature information to the other image processing algorithms and it is mainly implemented in a preprocessing stage. Nowadays, image processing applications are faced with embedded system implementation for a real-time processing. In order to satisfy this requirement, it is necessary to reduce execution time so as to improve the performance. Reducing the time for executing a feature extraction function dose not only extend the execution time for the other image processing algorithms, but it also helps satisfy a real-time requirement. This paper explains FAST (Feature from Accelerated Segment Test algorithm) of E. Rosten and presents FPGA-based embedded hardware accelerator architecture. The proposed acceleration scheme can be implemented by using approximately 2,217 Flip Flops, 5,034 LUTs, 2,833 Slices, and 18 Block RAMs in the Xilinx Vertex IV FPGA. In the Modelsim - based simulation result, the proposed hardware accelerator takes 3.06 ms to extract 954 features from a image with $640{\times}480$ pixels and this result shows the cost effectiveness of the propose scheme.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.881-890
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• 2009

To solve big problem in high energy physics or bioinformatics, it needs a large number of computing resources. But it hard to be provided by one grid environment. While user can submit each job by using it's own user interface in each grid environment, it may need many cost and efforts to manage several hundred jobs conserved in each grid environment separately. In this paper, to solve this problem we develop Ganga's Gridway backend and InterGrid backend. Therefore as we provide the same grid user interface between different grid environments. We developed a Gridway backend module that provide users with access to globus-based grid resources as well. We have also developed an InterGrid backend that allows users to submit jobs that have access to both glite-based resources and globus-based resources. In order to demonstrate the practicality of the new backend plugin modules, we have integrated the AutoDock application used by WISDOM project into Ganga as a new built-in application plugin for Ganga. And we preformed interoperability experiment between PRAGMA grid based on Globus and EGEE grid based on gLite.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.674-686
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• 2011

Choosing a seismic source and geophone type including a coupling method can be the most important factor in shallow seismic surveys. We studied the characteristics of seismic signals by analyzing 6 different seismic data sets that collected from several sources and geophone conditions. Geophones attached to weight plate (1.8 kg) can be easily and economically installed on the paved road where geophones with spikes would cause the coupling problem. In addition, experiments in this study revealed that a small handy hammer can be used as a seismic source by striking the paved road to generate the seismic signals within 200 ms two-way travel time. Attaching weight plates to geophones may change the geophone response curve which generally depends on the geophone mass, but the change seems not to give significant differences in the first arrival of refracted wave and in the pattern of reflection events. Consequently, using weight plates on paved roads can be an efficient and cost-saving method in the near-surface high-resolution seismic surveys.