• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.121-127
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• 2010

This paper relates with the improved CMA blind adaptive equalization algorithm which uses the constellation matching method that improve the inverse modelling efficiency of a communication channel compared to the present CMA blind adaptive equalizer. The amplitude distortion can be compensated in the present CMA blind adaptive equalizer which is used for the reduction of intersymbol interference by distortion that generate such as a band limited wireless mobile channel, but in the improved adaptive alogorithm operates with the minimize the amplitude phase distortion in the output of equalizer by applying the cost function that is composition of additional signal constellation matching error terms. In order to evaluation of the inverse modeling efficiency of improved algorithm, the residual intersymbol interference and recovered signal constellation were compared by computer simulation. As a result of comparion of computer simulation, the improved algorithm has a good stability in the residual intersymbol interference in the steady state, but it has a slow convergence rate in the adaptation state in initial state.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.350-355
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• 2017

UWB (Ultra Wide Band) refers to a system with a bandwidth of over 500 MHz or a bandwidth of 20% of the center frequency. It is robust against channel fading and has a wide signal bandwidth. Using the IR-UWB based ranging system, it is possible to obtain decimeter-level ranging accuracy. Furthermore, IR-UWB system enables acquisition over glass or cement with high resolution. In recent years, IR-UWB-based ranging chipsets have become cheap and popular, and it has become possible to implement positioning systems of several tens of centimeters. The system can be configured as one-way ranging (OWR) positioning system for fast ranging and TWR (two-way ranging) positioning system for cheap and robust ranging. On the other hand, the ranging based positioning system has a limitation on the number of terminals for localization because it takes time to perform a communication procedure to perform ranging. To overcome this problem, code multiplexing and channel multiplexing are performed. However, errors occur in measurement due to interference between channels and code, multipath, and so on. The measurement filtering is used to reduce the measurement error, but more fundamentally, techniques for removing these measurements should be studied. First, the TWR based positioning was analyzed from a stochastic point of view and the effects of outlier measurements were summarized. The positioning algorithm for analytically identifying and removing single outlier is summarized and extended to three dimensions. Through the simulation, we have verified the algorithm to detect and remove single outliers.

• Atmosphere
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• v.26 no.4
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• pp.599-615
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• 2016

This study investigates the accuracy of short-term ocean predictions during the development of ocean stratification for the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 5 (GloSea5) as well as the effect of atmosphere-ocean coupling on the predictions through a series of sensitive numerical experiments. Model performance is evaluated using the marine meteorological buoys at seas around the Korean peninsular (KP), Tropical Atmosphere Ocean project (TAO) buoys over the tropical Pacific ocean, and ARGO floats data over the western North Pacific for boreal winter (February) and spring (May). Sensitive experiments are conducted using an ocean-atmosphere coupled model (i.e., GloSea5) and an uncoupled ocean model (Nucleus for European Modelling of the Ocean, NEMO) and their results are compared. The verification results revealed an overall good performance for the SST predictions over the tropical Pacific ocean and near the Korean marginal seas, in which the Root Mean Square Errors (RMSE) were $0.31{\sim}0.45^{\circ}C$ and $0.74{\sim}1.11^{\circ}C$ respectively, except oceanic front regions with large spatial and temporal SST variations (the maximum error reached up to $3^{\circ}C$). The sensitive numerical experiments showed that GloSea5 outperformed NEMO over the tropical Pacific in terms of bias and RMSE analysis, while NEMO outperformed GloSea5 near the KP regions. These results suggest that the atmosphere-ocean coupling substantially influences the short-term ocean forecast over the tropical Pacific, while other factors such as atmospheric forcing and the accuracy of simulated local current are more important than the coupling effect for the KP regions being far from tropics during the development of ocean stratification.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.468-477
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• 2007

The DTC of voltage source inverter-fed PMSMs is based on hysteresis controllers of torque and flux. It has several advantages, namely, elimination of the mandatory rotor position sensor, less computation time, and rapid torque response. In addition, the stator resistance is the only parameter, which should be known, and no reference frame transformation is required. The DTC theory has achieved great success in the control of induction motors. However, for the control of PMSM drives proposed a few years ago, there are many basic theoretical problems that must be clarified. This paper describes an investigation into the effect of the zero voltage space vectors in the DTC system and points out that if using it rationally, not only can the DTC of the PMSM drive be driven successfully, but torque and flux ripples are reduced and overall performance of the system is improved. The implementation of DTC in PMSM drives is described and the switching tables specific for an interior PMSM are derived. The conventional eight voltage-vector switching table, which is namely used in the DTC of induction motors does not seem to regulate the torque and stator flux in a PMSM well when the motor operates at low speed. Modelling and simulation studies have both revealed that a six voltage-vector switching table is more appropriate for PMSM drives at low speed. In addition, the sources of difficulties, namely, the error in the detection of the initial rotor position, the variation of stator resistance, and the offsets in measurements are analysed and discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.4
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• pp.449-456
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• 2007

Dispersion coefficient preprocessing schemes have been examined to improve plume dispersion model performance in complex coastal areas. The performances of various schemes for constructing the sigma correction order were evaluated through estimations of statistical measures, such as bias, gross error, R, FB, NMSE, within FAC2, MG, VG, IOA, UAPC and MRE. This was undertaken for the results of dispersion modeling, which applied each scheme. Environmental factors such as sampling time, surface roughness, plume rising, plume height and terrain rolling were considered in this study. Gaussian plume dispersion model was used to calculate 1 hr $SO_2$ concentration 4 km downwind from a power plant in Boryeung coastal area. Here, measured data for January to December of 2002 were obtained so that modelling results could be compared. To compare the performances between various schemes, integrated scores of statistical measures were obtained by giving weights for each measure and then summing each score. This was done because each statistical measure has its own function and criteria; as a result, no measure can be taken as a sole index indicative of the performance level for each modeling scheme. The best preprocessing scheme was discerned using the step-wise method. The most significant factor influencing the magnitude of real dispersion coefficients appeared to be sampling time. A second significant factor appeared to be surface roughness, with the rolling terrain being the least significant for elevated sources in a gently rolling terrain. The best sequence of correcting the sigma from P-G scheme was found to be the combination of (1) sampling time, (2) surface roughness, (3) plume rising, (4) plume height, and (5) terrain rolling.

• Advances in environmental research
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• v.6 no.4
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• pp.265-279
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• 2017

The climate change has made adverse effects on land surface temperature for many regions of the world. Several climatic studies focused on different downscaling techniques for climatological parameters of different regions. For statistical downscaling of any hydrological parameters, conventional Neural Network Models were used in common. However, it seems that in any modeling study, uncertainty is a vital aspect when making any predictions about the performance. In this paper, Gamma Test is performed to determine the data length selection for training to minimize the uncertainty in model development. Another measure to improve the data quality and model development are wavelet transforms. Hence, Gamma Test with Wavelet decomposed Feedforward Neural Network (GT-WNN) model is developed and tested for downscaled land surface temperature of Patna Urban, Bihar. The results of GT-WNN model are compared with GT-FFNN and conventional Feedforward Neural Network (FFNN) model. The effectiveness of the developed models is illustrated by Root Mean Square Error and Coefficient of Correlation. Results showed that GT-WNN outperformed the GT-FFNN and conventional FFNN in downscaling the land surface temperature. The land surface temperature is forecasted for a period of 2015-2044 with GT-WNN model for Patna Urban in Bihar. In addition, the significance of the probable changes in the land surface temperature is also found through Mann-Kendall (M-K) Test for Summer, Winter, Monsoon and Post Monsoon seasons. Results showed an increasing surface temperature trend for summer and winter seasons and no significant trend for monsoon and post monsoon season over the study area for the period between 2015 and 2044. Overall, the M-K test analysis for the annual data shows an increasing trend in the land surface temperature of Patna Urban.

• Geomechanics and Engineering
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• v.14 no.5
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• pp.467-477
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• 2018

Estimation of hydraulic parameters is a critical step during design of foundation dewatering works. When many piles are installed in an aquifer, estimation of the hydraulic conductivity should consider the blocking of groundwater seepage by the piles. Based on field observations during a dewatering project in Shanghai, hydraulic conductivities are back-calculated using a numerical model considering the actual position of each pile. However, it is difficult to apply the aforementioned model directly in field due to requirement to input each pile geometry into the model. To develop a simple numerical model and find the optimal hydraulic conductivity, three scenarios are examined, in which the soil mass containing the piles is considered to be a uniform porous media. In these three scenarios, different sub-regions with different hydraulic conductivities, based on either automatic inverted calculation, or on effective medium theory (EMT), are established. The results indicate that the error, in the case which determines the hydraulic conductivity based on EMT, is less than that determined in the automatic inversion case. With the application of EMT, only the hydraulic conductivity of the soil outside the pit should be inverted. The soil inside the pit with its piles is divided into sub-regions with different hydraulic conductivities, and the hydraulic conductivity is calculated according to the volume ratio of the piles. Thus, the use of EMT in numerical modelling makes it easier to consider the effect of piles installed in an aquifer.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.389-395
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• 2006

This paper proposes the controller for biped robot using intelligent control algorithm. In order to simplify the complexity of biped robot control, manipulator of biped robot is divided into four modules. These modules are controlled by intelligent algorithm with Hierarchical Mixture of Experts(HME) using neural network. Also neural network having direct control method learns the inverse dynamics of biped robot. The HME, which is a network of tree structure, reallocates the input domain for the output by learning pattern of input and output. In this paper, as a result of learning HME repeatedly with EM algorithm, the controller for biped robot operating safety walking is designed by modelling dynamics of biped robot and generating virtual error of HME.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.23 no.3
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• pp.183-190
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• 2017

Carton clamp truck is widely perceived as the high-efficient handling equipment of factory premises and warehouse by its capability of palletless handling. Therefore, the significance of a lab-based handling simulation is becoming higher with the growth of clamp truck usage. In this study, preliminary FEA and design of handling test courses for the lab-based simulation of carton clamp truck handling were performed, and the PSD analyses were performed for the modified one for the test course proposed by Park et al. (2017) as well as ASTM D 6055 and ISTA 3B standards. For the vibration in all directions, the vibration energy intensity analyzed by ISTA 3B standard showed higher than that by the other two cases. A FEA was performed for the handling operation of the sudden stop of the clamps after lifting the target HCP (heavyweight refrigerator corrugated package, w=180 kgf) up to the specified height. The slip distance between the clamp arm and the target HCP was 0.85 mm. The simulation result of 0.85 mm was 3.7 times lower than the experimental result (3.2 mm) obtained by Park et al. (2017), and it was estimated that the deviation comes from both the experimental error by weight imbalance of target HCP, and excessive simplification during the FE modelling of target HCP.

• Advances in environmental research
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• v.6 no.2
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• pp.83-94
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• 2017

Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.