• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.521-531
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• 2002

Various diagnostic techniques for identifying influential observations are mostly based on the deletion of a single observation. While such techniques can satisfactorily identify influential observations in many cases, they will not always be successful because of some mask effect. It is necessary, therefore, to develop techniques that examine the potentially influential effects of a subset of observations. The partial regression plots can be used to examine an influential observation for a single parameter in multiple linear regression. However, it is often desirable to detect influential observations for a subset of regression parameters when interest centers on a selected subset of independent variables. Thus, we propose a diagnostic measure which deals with detecting influential observations on a subset of regression parameters. In this paper, we propose a measure M, which can be effectively used for the detection of influential observations on a subset of regression parameters in multiple linear regression. An illustrated example is given to show how we can use the new measure M to identify influential observations on a subset of regression parameters.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1512-1517
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• 2003

This paper presents the calibration for the parallel typed tilting table. The calibration system needs only simple sensing device which is a digital indicator to measure the orientation of a table. The calibration algorithm is developed by a measurement operator. It eliminates the concern about the poor parameter observability due to a large number of parameters of parallel-mechanism. This paper uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of a observation matrix. The number of identifiable parameters is examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a Parallel-typed Tilting Table and all the necessary kinematic parameters are identifiable.

• 전기의세계
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• v.22 no.3
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• pp.49-62
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• 1973

An algorithm for the state estimation and identification of multivariable nonlinear systems with noisy nonlinear observation has been investigated on the basis of the multidimensional Hermitian expansion for the a posteriori probability densities of the predicted observation, the predicted state and the observation conditioned by the state. A new approach for construction of this sequential nonlinear estimator, retaining up to the second order term of the observation error, has been developed, along with the approximation of nonlinear system functions, truncating at the second term. The estimation of the unknown parameters has been established by extending the state estimation technique, regarding the parameters as another state variables. The results of investigation indicate the feasibility of the schemes presented in this paper.

• The Journal of Korean Physical Therapy
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• v.34 no.3
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• pp.98-103
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• 2022

Purpose: New therapeutic approaches have emerged to improve gait ability in patients with brain damage, such as action observation learning (AOT), auditory cueing, motor imagery etc. We attempted to investigate the effects of AOT with auditory cueing (AOTAC) on gait function in patients with stroke. Methods: The eighteen stroke patients with a unilateral hemiparesis were randomly divided into three groups; the AOTAC, AOT, and control groups. The AOTAC group (n=8) received training via observing a video that showed normal gait with sound of footsteps as an auditory cue; the AOT group (n=6) receive action observation without auditory stimulation; the control group (n=5) observed the landscape video image. Intervention time of three groups was 30 minutes per day, five times a week, for four weeks. Gait parameters, such as cadence, velocity, stride length, stance phase, and swing phase were collected in all patients before and after each training session. Results: Significant differences were observed among the three groups with respect to the parameters, such as cadence, velocity, stride length, and stance/swing phase. Post-hoc analysis indicated that the AOTAC group had a greater significant change in all of parameters, compared with the AOT and control groups. Conclusion: Our findings suggest that AOTAC may be an effective therapeutic approach to improve gait symmetry and function in patients with stroke. We believe that this effect is attributable to the change of cortical excitability on motor related to cortical areas.

• Structural Engineering and Mechanics
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• v.34 no.6
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• pp.739-753
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• 2010

Pointing to the design requirement of prestressed space grid structure being the target cable force, the pretension scheme decision analysis method is studied when there's great difference between structural actual state and the analytical model. Based on recursive formulation of cable forces, the simulative recursive system for pretension process is established from the systematic viewpoint, including four kinds of parameters, i.e., system initial value (structural initial state), system input value (tensioning control force scheme), system state parameters (influence matrix of cable forces), system output value (pretension accomplishment). The system controllability depends on the system state parameters. Based on cable force observation values, the influence matrix for system state parameters can be calculated, making the system controllable. Next, the pretension scheme decision method based on cable force observation values can be formed on the basis of iterative calculation for recursive system. In this way, the tensioning control force scheme that can meet the design requirement when next cyclic supplemental tension finished is obtained. Engineering example analysis results show that the proposed method in this paper can reduce a lot of cyclic tensioning work and meanwhile the design requirement can be met.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.113-116
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• 2006

In order to fully utilize the inherent precision that GPS observables could offer, accurate estimation of dynamic and measurement parameters is vital. Among these parameters some are indispensable in virtually every form of GPS processing, while some are limitedly relevant to a particular application. In the context of time transfer by GPS, the transmission-related errors such as ionospheric and tropospheric delays, and the integer ambiguity of the carrier phase observables belong to the former, the atomic clock parameters and data batch-related parameters to the latter. Obviously the atomic clock parameters are of prime importance in GPS time transfer. In this study some of important parameters in conducting time transfer experiments by use of GPS were characterized and their effects on time transfer performance were investigated in detail

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.

• Journal of Environmental Science International
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• v.8 no.5
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• pp.633-637
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• 1999

A series of meterological observation using automation weather station(AWS) carried out to investigate characteristics of nocturnal meteorological parameters for 16~17 June 1998 at Buljeongdong mountain slope, Kyungbuk. Dry temperature at valley was lower than mountain because of high lapse rate at valley, so the strong inversion layer occurrenced at mountain slope for nighttime. Contrary of dry temperature, relative humidity of valley was higher than mountain for nighttime. Wind speed at valley from sunset to next day morning was lower than mountain, but that of valley after sunrise was higher than mountain. Wind direction at valley for all observation time were southeasterlies(SE), that of mountain for nighttime were northeasterlies(NE) or northnorthwesterlies(NNW), and that of mountain after sunrise were irregular. Vapor pressure at valley for all observation time was higher mountain, particularly the difference was high for nighttime.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.255-260
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• 1992

It is reported on the methodology of signal detection in noise which is based on a comparison of statistical parameters of observation sample from region of frequency-time noise space where a signal may be present and observation sample from region of this noise space and it is known a priori about the latter that the signal is absent in this region.

• 전기의세계
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• v.22 no.4
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• pp.17-24
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• 1973

In the view point of practical engineering the identification problem may be considered as a problem to determine the optimal model in the sense of minimizing a given criterion function using the input-output records of the plant. In the system identification the statistical approach has been known to be very effective when the topological structure of the system and the statistical characteristics of the observation noises are known a priori. But in the practical situation there are many cases when the inforhation about the observation noises or the system noises are not available a priori. Here, the authors propose a new identification method which can be used effectively even in the cases when the variances of observation noises are unknown a priori. In the method, the identification of unknown parameters of a linear diserete system is achieved by minimizing the improved quadratic criterion function which is composed of the term of square equation errors and the term to eliminate the affection of observation noises. The method also gives the estimate of noise variance. Numerical computations for several examples show that the proposed procedure gives satisfactory results even when the short time observation data are provided.