Attitude Sensor Measurement Models

2020 ◽  
pp. 53-65
Author(s):  
Chingiz Hajiyev ◽  
Halil Ersin Soken
Keyword(s):  
Measurement Models ◽  
Sensor Measurement ◽  
Attitude Sensor

NONLINEAR OBSERVER VIA EXTENDED KALMAN FILTER ALGORITHM FOR EULER ANGLES ESTIMATION WITHOUT ATTITUDE SENSOR MEASUREMENTS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Nor Hazadura Hamzah ◽  
Sazali Yaacob ◽  
Hariharan Muthusamy ◽  
Norhizam Hamzah ◽  
Teoh Vil Cherd ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Moment Equation ◽  
Nonlinear Observer ◽  
Euler Angles ◽  
Satellite Attitude ◽  
Observer Model ◽  
Kalman Filter Algorithm ◽  
Sensor Measurement ◽  
Attitude Sensor

This paper designs and investigates an observer system via Extended Kalman Filter algorithm to estimate the satellite’s Euler angles attitude during the absence of the attitude sensor measurement. This work contributes as a backup or an alternative system during unavailable attitude sensor measurement due to malfunction sensor or for cost reduction by reducing the number of sensors. In this work, the observer model for satellite attitude is presented in their non-simplified nonlinear form by combining the Euler’s Moment Equation and kinematics Euler angles parameter. The performance of the designed observer via Extended Kalman Filter algorithm is analyzed and verified using real flight data of Malaysian satellite.

FACT-2 – The Frankfurt Adaptive Concentration Test

2009 ◽  
Vol 25 (2) ◽  
pp. 73-82 ◽  
Author(s):  
Frank Goldhammer ◽  
Helfried Moosbrugger ◽  
Sabine A. Krawietz
Keyword(s):  
Convergent Validity ◽  
Four Dimensions ◽  
Measurement Models ◽  
Cognitive Failures ◽  
Concentration Test ◽  
Cognitive Failures Questionnaire

The Frankfurt Adaptive Concentration Test (FACT-2) requires discrimination between geometric target and nontarget items as quickly and accurately as possible. Three forms of the FACT-2 were constructed, namely FACT-I, FACT-S, and FACT-SR. The aim of the present study was to investigate the convergent validity of the FACT-SR with self-reported cognitive failures. The FACT-SR and the Cognitive Failures Questionnaire (CFQ) were completed by 191 participants. The measurement models confirmed the concentration performance, concentration accuracy, and concentration homogeneity dimensions of FACT-SR. The four dimensions of the CFQ (i.e., memory, distractibility, blunders, and names) were not confirmed. The results showed moderate convergent validity of concentration performance, concentration accuracy, and concentration homogeneity with two CFQ dimensions, namely memory and distractibility/blunders.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

Statistical Inference for Measurement Models

1970 ◽  
Vol 15 (6) ◽  
pp. 402, 404-405
Author(s):  
ROBERT E. DEAR
Keyword(s):  
Statistical Inference ◽  
Measurement Models

Structural Model of Service Quality Factors Affecting Loyalty Sustainability

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Eman Al-erqi ◽  
◽  
Mohd Lizam Mohd Diah ◽  
Najmaddin Abo Mosali ◽  
◽  
...  
Keyword(s):  
International Students ◽  
Service Quality ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Quality Factors ◽  
Factors Affecting ◽  
Measurement Models ◽  
Confirmatory Factor ◽  
The University ◽  
The Impact

This study seeks to address the impact of service quality affecting international student's satisfaction towards loyalty tothe Universiti Tun Hussein Onn Malaysia(UTHM). The aim of thestudy is to develop relationship between service quality factor and loyalty to the university from the international students’ perspectives. The study adopted quantitative approach where data was collected through questionnaire survey and analysed statistically. A total of 246 responses were received and found to be valid. The model was developed and analysed using AMOS-SEM software. Confirmatory factor analysis (CFA) function of the software was to assessed the measurement models and found that all the models achieved goodness of fit. Then path analysis function was used to assessed structural model and found that service qualityfactors have a significant effect on the students’ satisfaction and thus affecting the loyaltyto the university. Hopefully the outcome form this study will benefit the university in providing services especially to the international students.

Do Sequential Lineups Impair Discriminability?

2020 ◽  
Author(s):  
Matthew Philip Kaesler ◽  
John C Dunn ◽  
Keith Ransom ◽  
Carolyn Semmler
Keyword(s):  
Human Behavior ◽  
Feature Detection ◽  
Eyewitness Memory ◽  
Simultaneous Presentation ◽  
Diagnostic Feature ◽  
Sequential Presentation ◽  
Sequential Lineups ◽  
Measurement Models ◽  
Sequential Lineup ◽  
Lineup Procedures

The debate regarding the best way to test and measure eyewitness memory has dominated the eyewitness literature for more than thirty years. We argue that to resolve this debate requires the development and application of appropriate measurement models. In this study we develop models of simultaneous and sequential lineup presentations and use these to compare the procedures in terms of discriminability and response bias. We tested a key prediction of the diagnostic feature detection hypothesis that discriminability should be greater for simultaneous than sequential lineups. We fit the models to the corpus of studies originally described by Palmer and Brewer (2012, Law and Human Behavior, 36(3), 247-255) and to data from a new experiment. The results of both investigations showed that discriminability did not differ between the two procedures, while responses were more conservative for sequential presentation compared to simultaneous presentation. We conclude that the two procedures do not differ in the efficiency with which they allow eyewitness memory to be expressed. We discuss the implications of this for the diagnostic feature detection hypothesis and other sequential lineup procedures used in current jurisdictions.

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