• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.14-24
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• 2021

This study aims to examine probable human errors when landing an airplane by the use of SHERPA(systematic human error reduction and prediction approach) and propose methods for preventing the predictive human errors. It has been reported that human errors are concerned with a lot of accidents or incidents of an airplane. It is significant to predict presumable human errors, particularly in the operation mode of human-automation interaction, and attempt to reduce the likelihood of predicted human error. By referring to task procedures and interviewing domain experts, we analyzed airplane landing task by using HTA(hierarchical task analysis) method. In total, 6 sub-tasks and 19 operations were identified from the task analysis. SHERPA method was used for predicting probable human error types for each task. As a result, we identified 31 human errors and predicted their occurrence probability and criticality. Based on them, we suggested a set of methods for minimizing the probability of the predicted human errors. From this study, it can be said that SHERPA can be effectively used for predicting probable human error types in the context of human-automation interaction needed for navigating an airplane.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.84-90
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• 2012

Aviation Maintenance Technician(AMT)'s error is not directly link to deficiency which is differ to flight crew's error and it potentially maintains. Due to it usually occur as undesired aircraft state, hazards, like unreported maintenance error or near miss fortunately undetected and are not develop to accident. This could be a crucial influence of an accident occurrence. To remove these hazards, just safety culture should be support that anyone can report about safety problems and person who reported safety problems and hazards like near miss, should not get disadvantages. Also if it is satisfied, they must exempt for punishment and guaranteed for security. Hence, on this study, aviation maintenance site's just culture need to be researched and analysed about improvement for aviation maintenance field's positive just culture.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.281-288
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• 2010

This paper investigates the performance of IEEE 802.11p wireless access in vehicular environments (WAVE) system in small-scale fading models reported by Georgia Institute of Technology (Georgia Tech). We redesign the small-scale fading models to be applied to the computer simulation and develop the IEEE 802.11p WAVE physical layer simulator to provide the bit error rate and packet error rate performances. Moreover, a new channel estimator using decision directed channel estimation and linear minimum mean square error smoothing is proposed in order to improve the performance of the conventional least square channel estimator using two identical long training symbols. The simulation results are satisfactorily coincident with the scenarios of Georgia Tech report, and the proposed channel estimator significantly outperforms the conventional channel estimator.

• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.1044-1053
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• 2003

There are two major differences between the centerless infeed grinding process and the centerless through-feed grinding process. One is an axial movement of workpieces, and the other is that several workpieces are ground simultaneously and continuously by through-feeding. Because of these differences, through-feed ground parts inherently possess not only the roundness error but also the tapering error. The aims of the research reported in this paper are to examine this inherent tapering characteristic and to find the effects of grinding variables (center height angle, regulating wheel tilt angle, and shape of grinding wheel surface). To accomplish the objectives, experiments were carried out using two types of cylindrical workpiece shapes. Also, computer simulations were performed using the 3-D through-feed grinding model.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.559-564
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• 2013

In this paper a new hybrid forecast method composed of wavelet transform and neural network is proposed to forecast the wind speed more accurately. In the field of wind energy research, accurate forecast of wind speed is a challenging task. This will influence the power system scheduling and the dynamic control of wind turbine. The wind data used here is measured at 15 minute time intervals. The performance is evaluated based on the metrics, namely, mean square error, mean absolute error, sum squared error of the proposed model and compared with the back propagation model. Simulation studies are carried out and it is reported that the proposed model outperforms the compared model based on the metrics used and conclusions were drawn appropriately.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.638-643
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• 2009

A computer-generated hologram(CGH) is made for three-dimensional image reconstruction of a virtual object which is a difficult to irradiate the laser light directly. One of the adverse effect factors is quantization of wave front computed by program when a computer-generated hologram is made. Amplitude element is not considered in Kinoform, it needs processing to reduce noise or false image. So several investigation was reported that the improvement of reconstructed image of Kinoform. Means to calculate the most suitable complex amplitude distribution are iterative algorithm, simulated annealing algorithm and genetic Algorithm. Error diffusion method reconstructed to separate the object as for the noise that originated in the quantization error. So it is efficient method to obtain high quality image with not many processing.

• Journal of Ginseng Research
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• v.17 no.1
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• pp.61-68
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• 1993

From the early 1,100 to 1,900, ginseng cultivation seemed to be practiced with management of the diseases which were, in general, referred to a "disaster" at that time. Farmers had individually developed their own methods to manage the disaster with a try and error from generations to generations. It was not determined until 1909, however, that plant pathogens as a new concept was involved in the disaster and thirteen ginseng diseases were reported in Korea by Japanese plant pathologists. The intensive researches have been carried out from 1978 when Korea Ginseng and Tobacco Research Institute was established. Among the ginseng diseases reported in ginseng growing countries, Altemaria Panax, Eotrytis sp., Cylindrocarpon destmctans, Colletotrichum gloeosporioides, Erwinia carotovora subsp. carotovora, Pythium app. Phytophthora cactomm, Sclerotinia sp., Sclerotium rolfsii, and root rot caused by nitylenchus destructor have been observed in Korea and the appropriate control methods for the major diseases were developed. However, the other nine diseases reported by former researchers have not been confirmed for their pathogenicities and/or occurrences on ginseng yetinseng yet.

• Journal of Integrative Natural Science
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• v.6 no.3
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• pp.163-169
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• 2013

The chemokine receptor CCR1 a GPCR super family protein contains seven transmembrane domains. It plays an important role in rheumatoid arthritis, organ transplant rejection, Alzheimer's disease and also causes inflammation. Because of its role in disease processes, antagonism of CCR1 became an attractive therapeutic target. In the current study, we have taken a novel series of recently reported CCR1 antagonist of 1-(4-Phenylpiperazin-1-yl_-2-(1H-Pyrazol-1-yl) ethanone derivatives and performed a HQSAR analysis. The model was developed with Atom (A) and bond (B) parameters and with different set of atom counts to improve the model. The results of HQSAR showed good predictive ability in terms of $r^2$ (0.904) and $q^2$ (0.590) with 0.710 as standard error of prediction and 0.344 as standard error of estimate. The contribution map depicted the atom contribution in inhibitory effect. Compound-14 which was reported to be a highly active compound showed positive atom contribution in three R groups ($R^3$. $R^{5a}$ and $R^{2b}$) in inhibitory effect, which could be the reason why this compound is highly active compound whereas, the lowest active compound-6 showed negative contribution to inhibitory effect.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.301-316
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• 2002

An important goal of computational wind engineering is to impact the design process with simulations of flow around buildings and bridges. One challenging aspect of this goal is to solve the Navier-Stokes (NS) equations accurately. For the unsteady computations, an adaptive finite element technique may reduce the computer time and storage. The preliminary application of a p-version as well as an h-version adaptive technique to computational wind engineering has been reported in previous paper. The details on the implementation of p-adaptive technique will be discussed in this paper. In this technique, two posteriori error estimations, which are based on the velocity and vorticity, are first presented. Then, the polynomial order of the interpolation function is increased continuously element by element until the estimated error is less than the accepted. The second through sixth orders of hierarchical functions are used as the interpolation polynomials. Unequal order interpolations are used for velocity and pressure. Using the flow around a circular cylinder with Reynolds number of 1000 the two error estimators are compared. The result show that the estimated error based on the velocity is lower than that based on the vorticity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.38-47
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• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure. Furthemore, it is recently reported that the Bhattacharyya distance can be used to estimate error of Gaussian ML classifier within 1-2% margin. In this paper, we propose a feature extraction method utilizing the Bhattacharyya distance. In the proposed method, we first predict the classification error with the error estimation equation based on the Bhauacharyya distance. Then we find the feature vector that minimizes the classification error using two search algorithms: sequential search and global search. Experimental reslts show that the proposed method compares favorably with conventional feature extraction methods. In addition, it is possible to determine how man, feature vectors arc needed for achieving the same classification accuracy as in the original space.