• ETRI Journal
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• v.35 no.1
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• pp.51-57
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• 2013

In this paper, a small internal antenna for a mobile handset is presented using multiband, wideband, and high-isolation multiple-input multiple-output techniques. The proposed antenna consists of three planar inverted-F antennas (PIFAs) that operate in the global system for mobile communication (GSM900), the digital communication system (DCS), the personal communication system (PCS), the universal mobile telecommunication system (UMTS), and wireless local area network (WLAN) bands with a physical size of $40mm{\times}10mm{\times}10mm$. A resonator attached to the folded PIFA creates dual resonances, achieving a wide bandwidth of approximately 460 MHz, covering the DCS, PCS, and UMTS bands; a meander shorting line is used to improve impedance matching. Additionally, a modified neutralization link is embedded between diversity antennas to enhance isolation, which results in a 6-dB improvement in the isolation and less than 0.1 in the envelope correlation coefficient evaluated from the far-field radiation patterns. Simulation and measurements demonstrate very similar results for S-parameters and radiation patterns. Peak gains show 3.73 dBi, 3.77 dBi, 3.28 dBi, 2.15 dBi, and 5.86 dBi, and antenna efficiencies show 56.15%, 72.15%, 68.59%, 52.92%, and 82.93% for GSM900, DCS, PCS, UMTS, and WLAN bands, respectively.

• Spatial Information Research
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• v.18 no.5
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• pp.107-117
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• 2010

Taking the East-Hwasung area as the case, this study first builds gridded population data based on the municipal population survey raw data, and then measures, by way of GIS tools, the major urban spatial variables that are thought to influence the composition of the regional population. For the purpose of comparison, the urban models based on the Genetic Algorithm technique and the regression technique are constructed using the same input variables. The findings indicate that the GA output performed better in differentiating the effective variables among the pilot model variables, and predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression models. The study results indicate that GA technique could be a very useful and supplementary research tool in understanding the urban phenomena.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.84-87
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• 2000

In this paper, a high gain-broad bandwidth MMIC distributed amplifier was designed using cascaded single section distributed amplifier configuration. The PHEMT for this studies was fabricated at our lab The PHEMT has a 0.2 $\mu\textrm{m}$ gate length. a 80 $\mu\textrm{m}$ unit gate width and 4 gate fingers. A designed MMIC amplifier have higher S$\sub$21/ gain than the common distributed amplifier using the same number of active devices. From the simulated result, we obtained that the S$\sub$21/ gain of DC ∼ 20 GHz bandwidth was 15.6 dB and flatness was ${\pm}$0.9 dB, and input and output reflection coefficient were lower than -8 dB. The simulated gain shows an improvement 7.3 dB compared with those of conventional distributed amplifier. And the chip size is 2.0 ${\times}$ 1.2 $\textrm{mm}^2$.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.102-111
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• 1997

In this paper, a patern recognition method of surface mount device(SMD) IC using wavelet transform and neural network is proposed. We chose the feature parameter according to the characteristics of coefficient matrix which is obtained from four level discrete wavelet transform (DWT). These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Experimental results show that when the same form of feature pattern, as is used for learning, is put into neural network and gained 100% rate ofrecognition irrespective of SMD IC kinds, location and variation of illumination. In the case of unused feature pattern for learning, the recognition rate is 85.9% under the similar surroundings, where as an average recognition rate is 96.87% for the case of reregulated value of illumination. Proosed method is relatively simple compared with the traditional space domain method in extracting the feature parameter and is also well suited for recognizing the pattern's class, position and existence. It can also shorten the processing tiem better than method extracting feature parameter with the use of discrete cosine transform(DCT) and adapt the surroundings such as variation of illumination, the arrangement and the translation of SMD IC.

• Membrane and Water Treatment
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• v.9 no.5
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2826-2840
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• 2018

Traditional methods based active contours or region merging are powerless in processing images with blurring border or hair occlusion. In this paper, a structure based convolutional neural networks is proposed to solve segmentation of skin lesion image. The structure mainly consists of two networks which are segmentation net and discrimination net. The segmentation net is designed based U-net that used to generate the mask of lesion, while the discrimination net is designed with only convolutional layers that used to determine whether input image is from ground truth labels or generated images. Images were obtained from "Skin Lesion Analysis Toward Melanoma Detection" challenge which was hosted by ISBI 2016 conference. We achieved segmentation average accuracy of 0.97, dice coefficient of 0.94 and Jaccard index of 0.89 which outperform the other existed state-of-the-art segmentation networks, including winner of ISBI 2016 challenge for skin melanoma segmentation.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.586-591
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• 2008

This paper studied the emotion recognition system combined with robust speech recognition system in order to improve the performance of emotion recognition system. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. Final emotion recognition is processed using the input utterance and its emotional model according to the result of speech recognition. In the experiment, robust speech recognition system is HMM based speaker independent word recognizer using RASTA mel-cepstral coefficient and its derivatives and cepstral mean subtraction(CMS) as a signal bias removal. Experimental results showed that emotion recognizer combined with speech recognition system showed better performance than emotion recognizer alone.

• Journal of Energy Engineering
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• v.18 no.3
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• pp.156-162
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• 2009

Cylinder-pressure based combustion analysis provides a mechanism through which a combustion researcher can understand the combustion process. This paper was to identify the most significant sources of cycle-to-cycle combustion variability in a spark ignition engine at idle. To analyse the cyclic variation in the test engine, the burn parameters are determined on a cycle-to-cycle basis through analysis of the engine pressure data. The burn rate analysis program was used in the analysis of the data. Burn parameters were used to determine the variations in the input parameter-i.e., fuel, air, residual mass, and so on.

• Explosives and Blasting
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• v.21 no.4
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• pp.37-42
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• 2003

The source of rock breakage by explosive blasting is the energy released from an explosive. It is transmitted to the surrounding rock mass causing various types of fracture of rock material. The reaction of explosives and the resulting action on the surrounding rock mass are completed in very short tine, making it almost impossible to observe the processes occurring in the interior of the rock mass. In this study several input parameters are investigated by numerical modelling of blast source and dynamic response of rock mass. It is shown that damping coefficient and rising time are major parameters affecting dynamics response of rock mass.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.20-28
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• 2016

In this study, an efficient method of designing laminate composite radar absorbing structures (RAS) is proposed with consideration given to the structural shape so as to improve aircraft stealth performance. The calculation of the radar cross section (RCS) should be decreased to enhance the efficiency of the stochastic optimization when designing an RAS. In the proposed method, RAS are optimized to match up the input impedance of the minimal RCS, which is obtained by using physical optics and the transmission line theory. Single and double layer dielectric RAS for aircraft wings are employed as numerical examples and designed using the proposed method, RCS minimization and reflection coefficient minimization. The availability of the proposed method is assessed by comparing the similarity of the results and computation time with other design methods. According to the results, the proposed method produces the same results as the stochastic optimization, which adopts the RCS as the objective function, and can improve RAS design efficiency by reducing the number of RCS analyses.