• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.269-279
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• 2004

The most important factor influencing the robustness of the Internet Is the end-to-end TCP congestion control. However, the congestion control scheme of TCP Reno, the most popular TCP version on the Internet, employs passive congestion indication. It makes worse the network congestion. Recently, Brakmo and Peterson have proposed a new version of TCP, which is named TCP Vegas, with a fundamentally different congestion control scheme from that of the Reno. Many studies indicate that the Vegas is able to achieve better throughput and higher stability than the Reno. But there are two unfairness problems in Vegas. These problems hinder the spread of the Vegas in current Internet. In this paper, in order to solve these unfairness problems, we propose a new congestion control algorithm called TCP PowerVegas. The existing Vegas depends mainly only on the rtt(round trip time), but the proposed PowerVegas use the new congestion control scheme combined the Information on the rtt with the information on the packet loss. Therefore the PowerVegas performs the congestion control more competitively than the Vegas. Thus, the PowerVegas is able to solve effectively these unfairness problems which the Vegas has experienced. To evaluate the proposed approach, we compare the performance among PowerVegas, Reno and Vegas under same network environment. Using simulation, the PowerVegas is able to achieve better throughput and higher stability than the Reno and is shown to achieve much better fairness than the existing Vegas.

• KDI Journal of Economic Policy
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• v.36 no.4
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• pp.135-169
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• 2014

This study empirically analyzes changes in production patterns of farmers by agricultural disaster insurance. The aim of this project is to achieve stability of farm management by paying insurance in case of a natural disaster. However, it causes farmers to change production patterns in the direction of increasing production, and leads the crop price to drop. This can be explained by producers' risk reduction through the disaster insurance. The empirical analysis is based on IV approach with using two stage least squares method. The first stage estimates by difference-in-differences methodology indicate that the production of insurable crops increases more about 80,000ton on average than that of non-insurable crops. In addition, to solve the endogeneity problem caused by general supply and demand model, I use the first stage estimates and find that the price index of the crops drops about 2.3% according to the production increase by 10,000ton. The credibility of these results is also attained by various robustness checks. These findings suggest that it is necessary for government to analyze the whole economy which consists of producer and consumer welfare when it determines the policy. Besides, it implies that it is essential to develop a new market to cope with the unintended effect.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1032-1032
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• 2001

Artificial Neural Network (ANN) calibration techniques have been used commercially for agricultural applications since the mid-nineties. Global models, based on transmission data from 850 to 1050 nm, are used routinely to measure protein and moisture in wheat and barley and also moisture in triticale, rye, and oats. These models are currently used commercially in approx. 15 countries throughout the world. Results concerning earlier European ANN models are being published elsewhere. Some of the findings from that study will be discussed here. ANN models have also been developed for coarsely ground samples of compound feed and feed ingredients, again measured in transmission mode from 850 to 1050 nm. The performance of models for pig- and poultry feed will be discussed briefly. These models were developed from a very large data set (more than 20,000 records), and cover a very broad range of finished products. The prediction curves are linear over the entire range for protein, fat moisture, fibre, and starch (measured only on poultry feed), and accuracy is in line with the performance of smaller models based on Partial Least Squares (PLS). A simple bias adjustment is sufficient for calibration transfer across instruments. Recently, we have investigated the possible use of ANN for a different type of NIR spectrometer, based on reflectance data from 1100 to 2500 nm. In one study, based on data for protein, fat, and moisture measured on unground compound feed samples, dedicated ANN models for specific product classes (cattle feed, pig feed, broiler feed, and layers feed) gave moderately better Standard Errors of Prediction (SEP) compared to modified PLS (MPLS). However, if the four product classes were combined into one general calibration model, the performance of the ANN model deteriorated only slightly compared to the class-specific models, while the SEP values for the MPLS predictions doubled. Brix value in molasses is a measure of sugar content. Even with a huge dataset, PLS models were not sufficiently accurate for commercial use. In contrast an ANN model based on the same data improved the accuracy considerably and straightened out non-linearity in the prediction plot. The work of Mr. David Funk (GIPSA, U. S. Department of Agriculture) who has studied the influence of various types of spectral distortions on ANN- and PLS models, thereby providing comparative information on the robustness of these models towards instrument differences, will be discussed. This study was based on data from different classes of North American wheat measured in transmission from 850 to 1050 nm. The distortions studied included the effect of absorbance offset pathlength variation, presence of stray light bandwidth, and wavelength stretch and offset (either individually or combined). It was shown that a global ANN model was much less sensitive to most perturbations than class-specific GIPSA PLS calibrations. It is concluded that ANN models based on large data sets offer substantial advantages over PLS models with respect to accuracy, range of materials that can be handled by a single calibration, stability, transferability, and sensitivity to perturbations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1423-1433
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• 2018

Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.

• Journal of Pharmaceutical Investigation
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• v.35 no.3
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• pp.137-142
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of glipizide in human serum was validated and applied to the pharmacokinetic study of glipizide. Glipizide and internal standard, tolbutamide, were extracted from human serum by liquid-liquid extraction with benzene and analyzed on a Nova Pak $C_{18}\;60{\AA}$ column with the mobile phase of acetonitrile-potassium dihydrogen phosphate (10 mM, pH 3.5) (4:6, v/v). Detection wavelength of 275 nm and flow rate of 0.7 ml/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^3$ factorial design using a fixed glipizide concentration (500 ng/ ml) with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 10-1000 ng/ml with correlation coefficient greater than 0.999. The lower limit of quantitation using 0.5 ml of serum was 10.0 ng/ml, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 82.6 to 105.0% for glipizide with overall precision (% C.V.) being 1.13-13.20%. The percent recovery for human serum was in the range of 85.2 93.5%. Stability studies showed that glipizide was stable during storage, or during the assay procedure in human serum. The peak area and retention time of glipizide were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of glipizide in human serum samples for the pharmacokinetic studies at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.6
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• pp.437-443
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of a major metabolite of terfenadine, fexofenadine, in human serum was developed, validated, and applied to the pharmacokinetic study of terfenadine. Fexofenadine and internal standard, haloperidol were extracted from human serum by liquid-liquid extraction with acetonitrile and analyzed on a $Symmetry^{TM}$ C8 column with the mobile phase of 1% triethylamine phosphate (pH 3.7)-acetonitrile (67:33, v/v, adjusted to pH 5.6 with triethylamine). Detection wavelength of 230 nm for excitation, 280 nm for emission and flow rate of 1.0 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^{3}$ factorial design using a fixed fexofenadine concentration (50 ng/mL) with respect to its peak area and retention time. In addition, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 10-500 ng/mL with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of serum was 10 ng/mL, which was sensitive enough for the pharmacokinetic studies of terfenadine. The overall accuracy of the quality control samples ranged from 95.70 to 114.58% for fexofenadine with overall precision (% C.V.) being 3.53-14.39%. The relative mean recovery of fexofenadine for human serum was 90.17%. Stability studies (freeze-thaw, short-term, extracted serum sample and stock solution) showed that fexofenadine was stable during storage, or during the assay procedure in human serum. However, the storage at $-70^{\circ}C$ for 4 weeks showed that fexofenadine was not stable. The peak area and retention time of fexofenadine were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of fexofenadine in human serum samples for the pharmacokinetic studies of orally administered Tafedine tablet (60 mg as terfenadine) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.4
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• pp.265-271
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of etodolac in human serum was developed, validated, and applied to the pharmacokinetic study of etodolac. Etodolac and internal standard, ibuprofen were extracted from human serum by liquid-liquid extraction with hexane/isopropanol (95:5, v/v) and analyzed on a Luna C18(2) column with the mobile phase of 1% aqueous acetic acid-acetonitrile (4:6, v/v). Detection wavelength of 227 nm and flow rate of 1.0 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^3$ factorial design using a fixed etodolac concentration $(1\;{\mu}g/mL)$ with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of $0.05-40\;{\mu}g/mL$ with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of serum was 0.05 ${\mu}g/mL$, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 92.00 to 110.00% for etodolac with overall precision (% C.V.) being 1.08-10.11%. The percent recovery for human serum was in the range of 76.73-115.30%. Stability studies showed that etodolac was stable during storage, or during the assay procedure in human serum. The peak area and retention time of etodolac were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of etodolac in human serum samples for the pharmacokinetic studies of orally administered Lodin XL tablet (400 mg as etodolac) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.6
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• pp.423-429
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• 2005

A selective and sensitive reversed-phase HPLC method for the determination of fenoprofen in human serum was developed, validated, and applied to the pharmacokinetic study of fenoprofen calcium. Fenoprofen and internal standard, ketoprofen, were extracted from human serum by liquid-liquid extraction with diethyl ether and analyzed on a Luna C18(2) column with the mobile phase of acetonitrile-3 mM potassium dihydrogen phosphate (32:68, v/v, adjusted to pH 6.6 with phosphoric acid). Detection wavelength of 272 nm and flow rate of 0.25 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^{3}$ factorial design using a fixed fenoprofen concentration $(2\;{\mu}g/mL)$ with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of $0.05-100\;{\mu}g/mL$ with correlation coefficients greater than 0.999. The lower limit of quantification using 1 mL of serum was $0.05\;{\mu}g/mL$, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 92.27 to 109.20% for fenoprofen with overall precision (% C.V.) being 5.51-11.71 %. The relative mean recovery of fenoprofen for human serum was 81.7%. Stability (freeze-thaw, short and long-term) studies showed that fenoprofen was not stable during storage. But, extracted serum sample and stock solution were allowed to stand at ambient temperature for 12 hr prior to injection without affecting the quantification. The peak area and retention time of fenoprofen were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of fenoprofen in human serum samples for the pharmacokinetic studies of orally administered Fenopron tablet (600 mg as fenoprofen) at three different laboratories, demonstrating the suitability of the method.

• Journal of IKEEE
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• v.8 no.1 s.14
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• pp.96-107
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• 2004

In this paper, a new integral variable structure regulation controller(IVSRC) is designed by using a special integral sliding surface and a disturbance observer for the improved regulation control of highly nonlinear robot manipulators with prescribed output performance. The sliding surface having the integral state with a special initial condition is employed in this paper to exactly predetermine the ideal sliding trajectory from a given initial condition to origin without any reaching phase. And a continuous sliding mode input using the disturbance observer is also introduced in oder to effectively follow the predetermined sliding trajectory within the prescribed accuracy without large computation burden. The performance of the prescribed tracking accuracy to the predetermined sliding trajectory is clearly investigated in detail through the two theorems together with the closed loop stability. The design of the proposed IVSRC is separated into the performance design and robustness design in each independent link. The usefulness of the algorithm has been demonstrated through simulation studies on the regulation control of a two link manipulator under parameter uncertainties and payload variations, in view of no reaching phase, no overshoot, predetermined response with prescribed accuracy, easy change of output performance, separation of design phase, and so on.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.35-45
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• 2013

A autonomous vehicle requires improved and robust perception systems than conventional perception systems of intelligent vehicles. In particular, single sensor based perception systems have been widely studied by using cameras and laser radar sensors which are the most representative sensors for perception by providing object information such as distance information and object features. The distance information of the laser radar sensor is used for road environment perception of road structures, vehicles, and pedestrians. The image information of the camera is used for visual recognition such as lanes, crosswalks, and traffic signs. However, single sensor based perception systems suffer from false positives and true negatives which are caused by sensor limitations and road environments. Accordingly, information fusion systems are essentially required to ensure the robustness and stability of perception systems in harsh environments. This paper describes a perception system for autonomous vehicles, which performs information fusion to recognize road environments. Particularly, vision and laser radar sensors are fused together to detect lanes, crosswalks, and obstacles. The proposed perception system was validated on various roads and environmental conditions with an autonomous vehicle.