• Korean Journal of Food Science and Technology
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• v.49 no.6
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• pp.591-598
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• 2017

This study aimed to evaluate the measurement uncertainty for the quantitative determination of chlorite and chlorate in ready-to-eat fresh-cut vegetables using ion chromatography with a hydroxide-selective column. One gram of the homogenized sample in deionized water was sonicated and centrifuged at 8,500 rpm. The supernatant was purified by passing it through a Sep-Pak tC18 cartridge, followed by chromatographic determination using a Dionex IonPac AS27 column. The linearity of the calibration curves, recovery, repeatability, and reproducibility of the method were satisfactory. The method detection limit was estimated to be approximately 0.5 mg/kg. Each uncertainty component was evaluated separately, and the combined and expanded uncertainty values were calculated at the 95% confidence level. The measured concentrations for 3 mg/kg of chlorite and chlorate standard materials were $3.18{\pm}0.32$ and $3.10{\pm}0.42mg/kg$, respectively. These results confirmed the reliability of the developed method for measuring the two chlorine-based oxyanions in fresh-cut vegetables.

• Analytical Science and Technology
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• v.24 no.1
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• pp.1-9
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• 2011

We described an estimation of measurement uncertainty in quantitative analysis of 11-nor-9-carboxy-${\Delta}^9$-tetrahydrocannabinol (THC-COOH), the metabolite of ${\Delta}^9$-tetrahydrocannabinol, in hair samples by using the bead-assisted liquid-liquid extraction and gas chromatography-tandem mass spectrometric (GC-NCI-MS/MS) detection. Traceability of measurement was established through the use of reference materials, calibrated volumetric tubes, volume measuring devices, and measuring instruments. The analytical results were compared and the different contributions to the uncertainty were evaluated. Inter-day variation was performed by using statistical analysis of several indicative factors. Measurement uncertainty associated with the analyte in real forensic hair samples were estimated using QC data. The major factor of contribution to combined standard uncertainty was inter-day repeatability, while those associated with preparation of analytical standard and also sample of weight were insignificant considering the degree of contribution. Relative uncertainty of relative extended standard uncertainty divided into the measured concentration of the analyte was 17% in a hair sample. The uncertainty of result evaluation will be invaluable to improve quality of the analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1131-1145
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• 2013

Energy detection is a widely used method for spectrum sensing in cognitive radios due to its simplicity and accuracy. However, it is severely affected by the noise uncertainty. To solve this problem, a blind multiband spectrum sensing scheme which is robust to noise uncertainty is proposed in this paper. The proposed scheme performs spectrum sensing over the total frequency channels simultaneously rather than a single channel each time. To improve the detection performance, the proposal jointly utilizes the likelihood function combined with Gerschgorin radii of unitary transformed covariance matrix. Unlike the conventional sensing methods, our scheme does not need any prior knowledge of noise power or PU signals, and thus is suitable for blind spectrum sensing. In addition, no subjective decision threshold setting is required in our scheme, making it robust to noise uncertainty. Finally, numerical results based on the probability of detection and false alarm versus SNR or the number of samples are presented to validate the performance of the proposed scheme.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.520-528
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• 2001

This paper investigates a resonant microaccelerometer that measures acceleration using a built-in micromechanical resonator, whose resonant frequency is changed by the acceleration-induced axial force. A set of design equations for the resonant microaccelerometer has been developed, including analytic formulae for resonant frequency, sensitivity, nonlinearity and maximum stress. On this basis, the sizes of the accelerometer are designed for the sensitivity of 10$^3$Hz/g in the detection range of 5g, while satisfying the conditions for the maximum nonlinearity of 5%, the minimum shock endurance of 100g and the size constraints placed by microfabrication process. A set of the resonant accelerometers has been fabricated by the combined use of bulk-micromachining and surface-micromachining techniques. From a static test of the cantilever beam resonant accelerometer, a frequency shift of 860Hz has been measured for the proof-mass deflection of 4.3${\pm}$0.5$\mu\textrm{m}$; thereby resulting in the detection sensitivity of 1.10${\times}$10$^3$Hz/g. Uncertainty analysis of the resonant frequency output has been performed to identify important issues involved in the design, fabrication and testing of the resonant accelerometer.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.513-521
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• 2017

Robust optimal operation of a microgrid is required since the increase of the penetration level of renewable generators in the microgrid raises uncertainty due to their intermittent power output. In this paper, an application of probabilistic optimization method to economical operation of a microgrid is studied. To simplify the treatment of the uncertainties of renewable generations and load, the new 'band of virtual equivalent load variation' is introduced considering their uncertainties. A simplified robust optimization methodology to generate the scenarios within the band of virtual equivalent load variation and to obtain the optimal solution for the worst scenario is presented based on Monte Carlo method. The microgrid to be studied here is composed of distributed generation system(DGs), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems and wind power systems. The modeling of the objective function for considering interruption cost by the penalty function is presented. Through the case study for a microgrid with uncertainties, the validity of proposed robust optimization methodology is evaluated.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.3
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• pp.1-6
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• 2006

The altitude engine test is a sort of engine performance tests carried out to measure the performance of a engine at the simulated altitude and flight speed environments prior to that at the flight test. During the performance test of a engine, various values such as pressures and temperatures at different positions, air flow rate, fuel flow rate, and the load by thrust are measured. These measured values are used to derive the representative performance values such as the net thrust and the specific fuel consumption through a momentum equation. Hence each of the measured values has certain effects on the total uncertainty of the performance values. In this paper, the combined standard uncertainties of the performance variables at the engine test were estimated by the uncertainty analysis of the measurement values and the repeatability and reproducibility of the altitude test measurement were assessed by the analysis of variation on the repeated test data with different operator groups.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.155-158
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• 2001

The layup optimization by genetic algorithm (GA) for the strength of laminated composites with free-edge is presented. For the calculation of interlaminar stresses of composite laminates with free edges, extended Kantorovich method is applied. In the formulation of GA, repair strategy is adopted for the satisfaction of given constraints. In order to consider the bounded uncertainty of material properties, convex modeling is used. Results of GA optimization with scattered properties are compared with those of optimization with nominal properties. The GA combined with convex modeling can work as a practical tool for light weight design of laminated composite structures since uncertainties are always encountered in composite materials.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.2
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• pp.241-250
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• 2010

A recurrent adaptive model-free intelligent control with a friction estimation law is proposed to enhance the positioning performance of the mover in PMLSM system. For the PMLSM with nonlinear friction and uncertainty, an adaptive recurrent fuzzy neural network(ARFNN) and compensated control law in $H_{\infty}$ performance criterion are designed to mimic a perfect control law and compensate the approximated error between ideal controller and ARFNN. Combined with friction observer to estimate nonlinear friction parameters of the LuGre model, on-line adaptive laws of the controller and observer are derived based on the Lyapunov stability criterion. To analyze the effectiveness our control scheme, some simulations for the PMLSM with nonlinear friction and uncertainty were executed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.129-133
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• 2003

In this paper, we consider the robust guaranteed cost control problem for a class of uncertain neutral systems with given quadratic cost functions. The uncertainty is assumed to be norm-bounded and time-varying. The goal in this study is to design the memoryless state feedback controller such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound lot all admissible uncertainty. Some criteria for the existence of such controllers are derived based on the matrix inequality approach combined with the Lyapunov second method. A parameterized characterization of the robust guaranteed cost controllers is given in terms of the feasible solutions to the certain matrix inequalities. A numerical example is given to illustrate the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.330-336
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• 2005

An intelligent control method is proposed for control of rigid robot manipulators which achieves exponential tracking of repetitive robot trajectory under uncertain operating conditions such as parameter uncertainty and unknown deterministic disturbance. In the learning controller, exponentially stable learning algorithms are combined with stabilizing computed error feedforward and feedback inputs. It is shown that all the error signals in the learning system are bounded and the repetitive robot motion converges to the desired one exponentially fast with guaranteed convergence rate. An engineering workstation based control system is built to verify the effectiveness of the proposed control scheme.