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Little is known about how self-determination and financial attitude are linked to retirees’ financial well-being in Nigerian context. Drawing from the theory of reasoned action, the purpose of this paper is to examine the connection of self-determination, financial attitude and financial well-being. Also, this paper examines the mediating role of financial attitude between self-determination and financial well-being.

A cross-sectional study was used in collecting quantitative data from 399 retirees drawn from North Central Nigeria. Hypotheses are tested through structural equation modelling using the Analysis of Moments of Structures (AMOS) software, version 23.

Results from the research indicate that financial attitude serves as a trajectory through which self-determination leads to financial well-being. Therefore, self-determination and financial attitude significantly contribute to the financial well-being of retirees.

The use of a cross-sectional design may undermine the causal conclusions of the findings. This study adds to existing research on financial well-being by showing that financial attitude is significant in attaining financial well-being and how self-determination variable impact financial well-being.

This study contributes to literature by establishing the mediating role of financial attitude in the relationship between self-determination and financial well-being. Thus, instead of concentrating on only the direct effects of self-determination and financial well-being, the indirect effect of financial attitude is tested.

This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors.

First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm.

The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers.

In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm.

To provide a new method to determine parameters of the attitude determination system facing micro‐core.

Take example for attitude determination systems based on star‐sensor and fiber‐optic gyroscope combination and only based on star‐sensor. The optimum parameters of sensors are obtained by setting up of optimization design model of the attitude determination system adopting genetic algorithm.

Put forward a new concept of micro‐core aiming at a micro satellite. Further aiming at micro‐core, a new method which differs from traditional satellite design methods is adopted in this paper. The method proposed in this paper is instructive to the design of future micro satellites.

The method proposed in this paper only applied to attitude determination system. With the development of this method, it is hoped that the method can apply to other systems of a micro satellite.

The method proposed in this paper is instructive to the engineering design of a micro satellite.

Put forward a new concept of micro‐core, and aiming at its design a new method is proposed to design the attitude determination system by adopting genetic algorithm. The method is different from traditional satellite design methods.

An onboard autonomous technique can significantly reduce the costs of the mission. The purpose of this paper is to deal with the autonomous orbit determination and attitude determination of a satellite based on the sun, the earth and the moon sensors.

The models of the conical earth scanner are presented, and its measurement with information from the sun and the moon sensors is processed to simultaneously acquire the orbit and attitude of the satellite via extended Kalman filter.

The numerical simulation shows that the presented method can obtain the orbit and attitude information precisely; even in the new moon period, it can be used to get the satisfied results.

Autonomous orbit determination and attitude determination based on direction information of celestial objects, such as sun, earth and moon, are put forward. The method improves the survival ability of the satellite and decreases its reliance on the ground stations.

The purpose of this paper is to propose an attitude determination and control scheme for a low‐cost Micro‐satellite with defective inertia. Restricted by the payload design, the z‐axis inertia of this satellite is larger than the x and y axes, which is unstable for natural attitude dynamics.

An original operation mode is designed to avoid z axis from long‐time pointing to the sun during damping, which avoids some unexpected damage. In attitude determination design, EKF and UKF algorithms are compared on estimation accuracy, convergence time and computation complexity in attitude estimation design, which is referred to determine the final estimation scheme. A DSP‐based hardware solution is achieved and a semi‐physical testing and simulation system is built.

Simulation results show the 3‐axis stable mode can be built with the proposed scheme, and the unprotected facet of the satellite can be kept away from long‐time pointing to the sun.

The proposed ADCS scheme can be a reference for the future Micro‐satellite programs which share the similar configuration.

To make the single‐antenna attitude method more useful as a back‐up or fault diagnostic system than was targeted originally.

The enhancement incorporates information from the GPS satellite constellation and aircraft dynamic model. The visibility of GPS satellites affects the accuracy of the aircraft's volocity that is the main source of single‐antenna attitude. In addition, to use the aircraft dynamic model is natural because single‐antenna attitude is for exclusive use of aircraft. These are considered and implemented as a covariance matrix or process model of Kalman filters. The enhanced performances are verified by an aircraft nonlinear simulation.

The proposed method estimates more accurate volocity and unpiased single‐antenna attitude by using satellite constellation information and the aircraft dynamics. Moreover, the implemented system has a structure that combines other navigation sensors easily.

It would be more desirable to perform further researches; sensor integration, stability against wind disturbance, and aircraft model uncertainty, etc.

A useful attitude sensor for a back‐up attitude system at low cost on manned aircraft or a main attitude system on unmanned aircraft that are sensitive to the mass or size of payload.

This paper has been the first to promote the potential of single‐antenna attitude and with only information that can be easily obtained.

This chapter presents selected findings from an exploratory case study, which aimed to identify the information literacy of undergraduate students in the Faculty of Arts, Silpakorn University, Thailand. An embedded case study approach was adopted, data were gathered from academics, students, and librarians and relevant policy and curriculum documents were examined. Four departments were chosen as units of analysis within the case study to represent the different disciplines. These were Departments of Thai, Modern Eastern Languages (MEL), History and Geography. A total of 23 lecturers from these 4 departments were interviewed. A total of 35 students from the same departments and 10 librarians from the Central Library were surveyed using focus groups.

For each department, the data was analysed and triangulated and the information literacy conceptions of academics and students were mapped and compared, together with a picture of the department’s goals and pedagogic approach for information literacy. Finally, findings from all four departments were brought together to provide holistic insight into the information literacy of students in the faculty.

It emerged from the data that both staff and students identified a number of personal attributes that were expected of the information literate student. These were categorised into four groupings: attitude, research skills, generic skills and knowledge. The study revealed some common and distinct characteristics of different disciplines, which reflect the similarities and differences of perceptions of information literacy in this study. The key variations were: the conceptualisation and nature of ‘information’, the degree to which the outside world is of importance and the use of specialised technology.

Information literacy education is perceived as a holistic approach, integrated through courses across the curriculum through formal and informal education. Students are engaged with different aspects of information literacy through different teaching, learning and assessment methods and activities. Independent learning is emphasised as a teaching and learning strategy. Discussion-based and coursework-based instructions are identified as best methods in developing students’ information literacy. The findings also reveal that teaching and learning information literacy is deemed the responsibility of academic lecturers while librarians are not involved in information literacy education.

The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system devices in strap-down inertial navigation attitude solution of micro-quadrotor.

In this study, a three-stage attitude estimation scheme that combines data preprocessing, gyro drifts prediction and enhanced unscented Kalman filtering (UKF) is proposed. By introducing a preprocessing model, the quaternion orientation is calculated as the composition of two algebraic quaternions, and the decoupling feature of the two quaternions makes the roll and pitch components independent of magnetic interference. A novel real-time based on differential value (DV) estimation algorithm is proposed for gyro drift. This novel solution prevents the impact of quartic characteristics and uses the iterative method to meet the requirement of real-time applications. A novel attitude determination algorithm, the pre-process DV-UKF algorithm, is proposed in combination with UKF based on the above solution and its characteristics.

Compared to UKF, both simulation and experimental results demonstrate that the pre-process DV-UKF algorithm has higher reliability in attitude determination. The dynamic errors in the three directions of the attitude are below 2.0°, the static errors are all less than 0.2° and the absolute attitude errors tailored by average are about 47.98% compared to the UKF.

This paper fulfils an identified need to achieve high-precision attitude estimation when using low-cost inertial devices in micro-quadrotor. The accuracy of the pre-process DV-UKF algorithm is superior to other products in the market.

For fixed-wing micro air vehicles, the attitude determination is usually produced by the horizon/Global Navigation Satellite System (GNSS) in which the GNSS provides yaw estimates, while roll and pitch are computed using horizon sensors. However, the attitude determination has been independently obtained from the two sensors, which will result in insufficient usage of data. Also, when implementing attitude determination algorithms on embedded platforms, the computational resources are highly restricted. This paper aims to propose a computationally efficient linear Kalman filter to solve the problem.

The observation model is in the form of a least-square optimization composed by GNSS and horizontal measurements. Analytical quaternion solution along with its covariance is derived to significantly speed up on-chip computation.

The reconstructed attitude from Horizon/GNSS is integrated with quaternion kinematic equation from gyroscopic data that builds up a fast linear Kalman filter. The proposed filter does not involve coupling effects presented in existing works and will be more robust encountering bad GNSS measurements.

Electronic systems are designed on a real-world fixed-wing plane. Experiments are conducted on this platform that show comparisons on the accuracy and computation execution time of the proposed method and existing representatives. The results indicate that the proposed algorithm is accurate and much faster computation speed in studied scenarios.

This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the periodic thermal distortion, has a great impact on spacecraft attitude determination accuracy.

The unfavorable effect of the LFE can be partly eliminated by using the calibration algorithm based on the augmented Kalman filter (AKF). However, the AKF may be worse than the traditional Kalman filter (KF) in the absence of the LFE. To cope with this problem, the MMAE is applied first time for combining the AKF and the KF in the spacecraft attitude determination system, such that satisfactory performance can be achieved in different operating scenarios.

The convergence of the presented MMAE is demonstrated through a formal derivation. A novel method is proposed to tune the MMAE design parameter, such that the convergence rate of the estimator is increased. It is shown via numerical studies that the presented algorithm outperforms the AKF and the KF.

The calibration algorithm is applicable for spacecraft attitude determination.

An effective star sensor LFE calibration algorithm based on the MMAE is developed. In addition, a novel method is proposed to increase convergence rate of the estimator.