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

• International Journal of Concrete Structures and Materials
• /
• v.1 no.1
• /
• pp.63-73
• /
• 2007

Optimum multi-layered feed-forward neural network (NN) models using a resilient back-propagation algorithm and early stopping technique are built to predict the shear capacity of reinforced concrete deep and slender beams. The input layer neurons represent geometrical and material properties of reinforced concrete beams and the output layer produces the beam shear capacity. Training, validation and testing of the developed neural network have been achieved using 50%, 25%, and 25%, respectively, of a comprehensive database compiled from 631 deep and 549 slender beam specimens. The predictions obtained from the developed neural network models are in much better agreement with test results than those determined from shear provisions of different codes, such as KBCS, ACI 318-05, and EC2. The mean and standard deviation of the ratio between predicted using the neural network models and measured shear capacities are 1.02 and 0.18, respectively, for deep beams, and 1.04 and 0.17, respectively, for slender beams. In addition, the influence of different parameters on the shear capacity of reinforced concrete beams predicted by the developed neural network shows consistent agreement with those experimentally observed.

• Journal of Soil and Groundwater Environment
• /
• v.22 no.4
• /
• pp.49-59
• /
• 2017

This study estimated the nitrogen budget, including gaseous nitrogen oxides ($NO_x$), of South Korea in 2012~2014. The nitrogen budget was classified into three categories: agricultural and livestock, forest, and city. To estimate the nitrogen budget, several input and output parameters were investigated, including deposition, fixation, irrigation, chemical fertilizer use, compost, fuel, denitrification, volatilization, runoff, crop uptake, leaching, and $NO_x$ emissions. The annual nitrogen inputs from 2012 to 2014 were 6,202,828, 6,137,708, and 6,022,379 ton/yr, respectively. The corresponding annual nitrogen outputs were 1,393,763, 1,380,406, and 1,360,819 ton/yr, respectively, signifying a slight decrease from 2012 to 2014. $NO_x$ was the parameter contributing to the nitrogen budget to the greatest extent. The annual ratios of $NO_x$ emissions by vehicles, power plants, and businesses were 0.31, 0.31, and 0.30 in 2012, 2013, and 2014, respectively. A change in government policy that prohibited the disposal of livestock manure and sewage sludge in the ocean from 2012 affected nitrogen budget profile. As a result, the ocean disposal ratio completely diminished, which differs from previous studies.

• Journal of the Mineralogical Society of Korea
• /
• v.11 no.1
• /
• pp.45-67
• /
• 1998

FORTRAN program PHYLS was developed to model the structures of 2:1 1M and 2M1 phyllosilicates on the basis of geometrical analyses. Input to PHYLS requires the chemical composition and d(001) spacing of the mineral. The output from PHYLS consists of the coordinates of the crystallographically independent sites in the unit cell, and such structural parameters as the cell dimensions, interaxial angle, cell volume, interatomic distances, and deformation angles of the polyhedra. PHYLS can generate these structural details according to the user's choice of space group and cation configuration. User can choose one of such space groups as C2/m, C2,and C2/c and such cation configurations as random and ordered tetrachedral/octahedral cation configurations. PHYLS simulated the structures of dioctahedral and trioctahedral phyllosilicates having random tetrahedral cation configuration fairly close to the reported experimentally determined structures. In contrast, the simulated structures for ordered tetrahedral cation configurations showed greater deviation from the experimentally determined structures than those for random configurations. However, if the cations were partially ordered and the sizes of the tetrahedra became similar, the simulated PHYLS may be helpful in various investigations on the relationships between structures and physicochemical properties of the phyllosilicates.

• Advances in Computational Design
• /
• v.2 no.3
• /
• pp.225-240
• /
• 2017

This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days' curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.9
• /
• pp.64-72
• /
• 1998

In this paper, the design of a current integrator for low-voltage, low-power, and high frequency applications using complementary high swing cascode current-mirror is presented. The proposed integrator decreases output current errors due to non-zero input resistance and non-infinite output resistance of the simple current integrator. As a design example, the 3rd order Butterworth lowpass filter is designed by a leapfrog method. Also, we apply the predistortion design method to reduce the magnitude distortion which occurs at a cutoff frequency by the undesirable phase shift of a lossless current integrator. The designed current-mode filter is simulated and examined by SPICE using 0.8$\mu\textrm{m}$ CMOS n-well process parameters. The simulation results show 20MHz cutoff frequency and 615㎼ power dissipation with a 2V power supply. And the cutoff frequency of the filters can be easily changed by the DC bias current.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2371-2388
• /
• 2015

In this paper, we investigate the performance evaluation of three dimensional (3D) multiple-input multiple-output (MIMO) systems with an adjustable base station (BS) antenna tilt angle and zero-forcing (ZF) receivers in Ricean/Lognormal fading channels. In particular, we take the lognormal shadow fading, 3D antenna gain with antenna tilt angle and path-loss into account. First, we derive a closed-form lower bound on the sum rate, then we obtain the optimal BS antenna tilt angle based on the derived lower bound, and finally we present linear approximations for the sum rate in high and low-SNR regimes, respectively. Based on our analytical results, we gain valuable insights into the impact of key system parameters, such as the BS antenna tilt angle, the Ricean K-factor and the radius of cell, on the sum rate performance of 3D MIMO with ZF receivers.

• Journal of Power Electronics
• /
• v.8 no.4
• /
• pp.354-362
• /
• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.18 no.6
• /
• pp.532-537
• /
• 2005

In order to develop a tunable resonator which can be easily operated by DC bias and applied for microwave tunable filters and devices using ferroelectric thin or thick films, the non conductor backed-and conductor backed- coplanar stripline resonators have been designed and analyzed. They have been designed to be operated at 25 GHz which involve coplanar stripline input and output ports. The resonators have been simulated and analyzed using Ansoft HFSS. The research has been focused on the Quality factor of the coplanar stripline resonator. The conductor Q, box Q, and radiation Q of the resonators have been analyzed and calculated according to the substrate thickness & conductor width of the resonators. From these parameters, the loss factors of the coplanar stripline resonator have been investigated. The conducting Q of the coplanar stripline resonator has no relation with the thickness of dielectric substrate and increases as the conductor width increases. The box Q has no much relation with the thickness of substrate and the conductor width, which is above 2000. The radiation loss increases as the thickness of substrate and the conductor width increase. To decrease the radiation loss of the coplanar stripline resonator, a conductor backed coplanar stripline resonator has been proposed which has the unloaded Q of 170.

• Journal of electromagnetic engineering and science
• /
• v.14 no.1
• /
• pp.15-24
• /
• 2014

A compact dual-band three-way metamaterial power divider is proposed that has three in-phase outputs. Fully printed composite rightand left-handed (CRLH) unequal and equal power dividers are first implemented for 900-MHz and 2.4-GHz bands with the power-division ratios of 2:1 and 1:1, respectively. An initial 1:1:1 power divider is then achieved by incorporating the input of the two-way equal block into an output of the unequal block, and trimming the interconnection parameters. The condition of an identical phase at the three outputs of the power divider is then met by devising a hybrid CRLH phase-shift line to compensate for the different phase errors at the two frequencies. This scheme is confirmed by predicting the performance of the power divider with circuit analysis and full-wave simulation and measuring the fabricated prototype. They results show agreement; the in-phase outputs as well as the desirable power-division are accomplished and outdo the conventional techniques.