• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1117-1123
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• 2021

Object recognition is to identify the location and class of a specific object by analyzing the given image when a specific image is input. One of the fields in which object recognition technology is actively applied in recent years is autonomous vehicles, and this paper describes the trend of image-based object recognition artificial intelligence technology in autonomous vehicles. The image-based object detection algorithm has recently been narrowed down to two methods (a single-step detection method and a two-step detection method), and we will analyze and organize them around this. The advantages and disadvantages of the two detection methods are analyzed and presented, and the YOLO/SSD algorithm belonging to the single-step detection method and the R-CNN/Faster R-CNN algorithm belonging to the two-step detection method are analyzed and described. This will allow the algorithms suitable for each object recognition application required for autonomous driving to be selectively selected and R&D.

• Progress in Medical Physics
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• v.27 no.4
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• pp.180-188
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• 2016

Acuros XB advanced dose calculation algorithm (AXB, Varian Medical Systems, Palo Alto, CA) has been released recently and provided the advantages of speed and accuracy for dose calculation. For clinical use, it is important to investigate the dosimetric performance of AXB compared to the calculation algorithm of the previous version, Anisotropic Analytical Algorithm (AAA, Varian Medical Systems, Palo Alto, CA). Ten volumetric modulated arc therapy (VMAT) plans for each of the following cases were included: head and neck (H&N), prostate, spine, and lung. The spine and lung cases were treated with stereotactic body radiation therapy (SBRT) technique. For all cases, the dose distributions were calculated using AAA and two dose reporting modes in AXB (dose-to-water, $AXB_w$, and dose-to-medium, $AXB_m$) with same plan parameters. For dosimetric evaluation, the dose-volumetric parameters were calculated for each planning target volume (PTV) and interested normal organs. The differences between AAA and AXB were statistically calculated with paired t-test. As a general trend, $AXB_w$ and $AXB_m$ showed dose underestimation as compared with AAA, which did not exceed within -3.5% and -4.5%, respectively. The maximum dose of PTV calculated by $AXB_w$ and $AXB_m$ was tended to be overestimated with the relative dose difference ranged from 1.6% to 4.6% for all cases. The absolute mean values of the relative dose differences were $1.1{\pm}1.2%$ and $2.0{\pm}1.2%$ when comparing between AAA and $AXB_w$, and AAA and $AXB_m$, respectively. For almost dose-volumetric parameters of PTV, the relative dose differences are statistically significant while there are no statistical significance for normal tissues. Both $AXB_w$ and $AXB_m$ was tended to underestimate dose for PTV and normal tissues compared to AAA. For analyzing two dose reporting modes in AXB, the dose distribution calculated by $AXB_w$ was similar to those of AAA when comparing the dose distributions between AAA and $AXB_m$.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.159-167
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• 2000

In optimization problems, computationally intensive or expensive simulations hinder the use of standard optimization techniques because the computational expense is too heavy to implement them at each iteration of the optimization algorithm. Therefore, those expensive simulations are often replaced with approximation models which can be evaluated nearly free. However, because of the limited accuracy of the approximation models, it is practically impossible to find an exact optimal point of the original problem. Significant efforts have been made to overcome this problem. The approximation models are sequentially updated during the iterative optimization process such that interesting design points are included. The interesting points have a strong influence on making the approximation model capture an overall trend of the original function or improving the accuracy of the approximation in the vicinity of a minimizer. They are successively determined at each iteration by utilizing the predictive ability of the approximation model. This paper will focuses on those approaches and introduces various approximation methods.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.123-126
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• 2000

In this paper, the portable game machine called W"alking Beat" is designed and implemented not only to propose the new possibilities for the peripheral equipment market of portable acoustic machine but also to overcome the limitation of the acoustic simulation game machine such as the existing Beat Mania. The old game machine can be used only in a particular place, where it is installed. However, in order to get over the constraint on this space problem "Walking Beat Game Machine" is designed to facilitate the portability. In addition, the frequency analysis method using FFT algorithm is employed by regarding the music data for the portable digital acoustic machine as source so that the limitation that the existing game machine depends heavily on the previously registered game contents can be overcome. By making it possible to play games for all the music and putting an emphasis on multimedia trend only to listen to the music, it is speculated that it can contribute to the development of the new culture in the near future.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.411-414
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• 2005

The most recent trend on digital hearing aid is to increase the ratio of signal to noise by directivity or to develop noise reduction algorithm inside DSP IC chip. This paper designed, fabricated and tested a digital hearing aid directivity testing device in which a micro-mouse-like the stepping motor with a speaker rotates around an examinant. Both ears of the examinant were fixed with ITE hearing aids in order to response to receiving sound. The diameter of the directivity testing device was 2 [m] and the micro-mouse was precisely controlled by PICBASIC micro processor.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.624-634
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• 1994

A numerical method which combines equal-order velocity-pressure formulation originated from SIMPLE algorithm and streamline upwinding method has been developed. To verify the proposed numerical method, we considered the lid-driven cavity flow and backward facing step flow. The trend of convergence history is stable up to the error criterion beyond which the maximum value of error is oscillatory due4 to the round-off error. In the present study, all results were obtained with the single precision calculation up to the given error criterion and it was found to be sufficient for our purpose. The present results were then compared with existing experimental results using laser doppler velocimetry and numerical results using finite difference method and mixed interpolation finite element method. It has been shown that the present method gives accurate results with less memories and execution time than the coventional finite element method.

• Electronics and Telecommunications Trends
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• v.33 no.3
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• pp.89-99
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• 2018

Human activity recognition (HAR) is a technology that aims to offer an automatic recognition of what a person is doing with respect to their body motion and gestures. HAR is essential in many applications such as human-computer interaction, health care, rehabilitation engineering, video surveillance, and artificial intelligence. Smartphones are becoming the most popular platform for activity recognition owing to their convenience, portability, and ease of use. The noticeable change in smartphone-based activity recognition is the adoption of a deep learning algorithm leading to successful learning outcomes. In this article, we analyze the technology trend of activity recognition using smartphone sensors, challenging issues for future development, and a strategy change in terms of the generation of a activity recognition dataset.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.870-875
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• 2004

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• Journal of KSNVE
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• v.6 no.3
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• pp.325-332
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• 1996

One of the greatest shortcoming in today's predictive maintenance program is the ability to diagnose the mechanical and electrical problems within the machine when the vibration exceeds preset overall and spectral alarm levels. In this study, auto-diagnosis system is constructed by using A/D converter to convert analog to digital singal. With this device the system analyses input signal to diagonosis machine condition. Many plots, which display machine condition, and input values of every channel are calculated in this system. If the falut is found, the system diagnoses automatically using fuzzy algorithm and trend monitoring. Prediction is also performed by the grey system theory. Operator finds out eh machine operating condition intuitively based on with personal computer CRT in using this system.