About: Science Technology and Engineer is an academic journal. The journal publishes majorly in the area(s): Kalman filter & Fast Kalman filter. Over the lifetime, 150 publications have been published receiving 388 citations.
TL;DR: Because of there are many ambiguous and fuzzy factors during supplier selection, a kind of decision optimum model which bases on fussy consistent matrix, analysis it's principle, step and the scope of application is introduced.
Abstract: Because of there are many ambiguous and fuzzy factors during supplier selection, a kind of decision optimum model which bases on fussy consistent matrix, analysis it's principle, step and the scope of application is introduced. A quantitative analysis method in selection supplier is given, and provided it with an example illustration.
TL;DR: According to practical experience, some useful suggestions are offered actually when selecting the units, establishing the models, the material properties and setting up the parameters while simulating and analysing by ANSYS software to the reinforced concrete structure as mentioned in this paper.
Abstract: According to practical experience, some useful suggestions are offered actually when selecting the units, establishing the models, the material properties and setting up the parameters while simulating and analysing by ANSYS software to the reinforced concrete structure.
TL;DR: In this article, two weighted measurement fusion algorithms for Kalman filtering-based multisensor data fusion have been proposed and compared with the centralized measurement fusion algorithm, they have the global optimality and completely functional equivalence.
Abstract: For Kalman filtering-based multisensor data fusion, there are two weighted measurement fusion algorithms. Using the Kalman method, it is proved that compared with the centralized measurement fusion algorithm, they have the global optimality and completely functional equivalence. Not only they can give the globally optimal Kalman estimators (filter, predictor, and smoother) , white noise estimators, and signal estimators, but also the computational burden can be reduced obviously. They are adapted for real time applications.
TL;DR: The temporal course of the Stroop effect was investigated by event related potential (ERP) technique with. children of sixth grade as discussed by the authors, where subjects were asked to identify the display color of the Chinese characters by pressing the corresponding key as quickly and accurately as possible.
Abstract: The temporal course of the Stroop effect was investigated by event related potential(ERP) technique with . children of sixth grade. Subjects were asked to identify the display color of the Chinese characters by pressing the corresponding key as quickly and accurately as possible. The brain electric singnals were recorded by a 32-channel ERP/ EEG system. Besides the behavioural data, the evidence from the ERP data for the Stroop effects was also observed. It is resulted that the first ERP effect was obtained at about 300 ms post stimulus onset. The P300 amplitude induced by inconsistent condition is larger than that in consistent and neutral conditions, while the P300 latency for incongru-ent trials is the slowest. The second ERP effect generated by colored characters is a slow wave emerging at about 400 ms after the stimulus onset. There were significant trial type differences at posterior sites but not at frontal sites. Further comparisons showed that the mean amplitude for incongruent trials and controls was larger than congruent trials. These findings indicate that Stroop effect in children involves a complex process. The interference effect is the result of assembling the early stimuli evaluation stage and later response selection stage, while the facilitation effect may occur at the later stage for response selection.
TL;DR: Using Lagrange multiplier method and matrix differential operation, three information fusion estimation criterions are presented in the linear minimum variance sense, where the fusion estimators are respectively weighted by matrices, weighted by scalar and weighted by Scalar on components.
Abstract: Using Lagrange multiplier method and matrix differential operation, three information fusion estimation criterions are presented in the linear minimum variance sense, where the fusion estimators are respectively weighted by matrices, weighted by scalar and weighted by scalar on components. The correlation among estimation errors is considered. The results of existing literatures are extended and developed. Their precision and computational burdens are compared. They can be applied into optimal information fusion estimation for the states or signals.