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Laboratory calibration methods are time-consuming and require accurate devices to find the error coefficients of the low-cost microelectromechanical system (MEMS) accelerometer. Besides, low-cost MEMS sensors highly depend on temperature because of their silicon property and the effect of temperature on error coefficients should also be considered for compensation. This paper aims to present a field calibration method in which the accelerometer is placed in different positions without any accurate equipment in a few minutes and its temperature is changed by a simple device like a hairdryer.

In this paper, a non-linear cost function is defined based on this rule that the magnitude of the acceleration measured by the accelerometer in static mode is equal to the gravity plus error factors. Also, the dependency of error coefficients of the accelerometer is presented as a second-order polynomial in this cost function. By minimizing the cost function, the accelerometer error coefficients include bias, scale factor and non-orthogonality and their temperature dependency are obtained simultaneously.

Simulation results in MATLAB and empirical results of a MPU6050 accelerometer verify the good performance of the proposed calibration method.

Finding a fast and simple field calibration method to calibrate a low-cost MEMS accelerometer and compensate for the temperature dependency without using accurate laboratory equipment can help a wide range of industries that use advanced and expensive sensors or use expensive laboratory equipment to calibrate their sensors, to decrease their costs.

This research aims to look at how students feel about taking online learning (OL) while studying in higher education institutions (HEIs) using an extended technology acceptance model (TAM). The study looked into the factors that influence students' decisions to use OL, which helps meet their individual needs beyond the confines of the traditional classroom.

A study of 284 students from the universities of Gujarat in India was conducted using a self-administered questionnaire. The partial least square-structural equation modelling (PLS-SEM) was used to analyse the study's test results.

The result of the study confirms that perceived enjoyment (PE) has a fully significant relationship with the behavioural intention to use online learning (IOL), whereas self-efficacy (SE) is partially supported and system accessibility (ACC) has an insignificant impact on the IOL.

Though the study focussed on the TAM to analyse the proposed model, future studies should address other constructs like ICT infrastructure, perceived behavioural control, experience, etc.

This research identified the key variables of students' intention to adapt to OL and offered a path to encourage higher education students to use online education as a classroom alternative. Educators in Indian administrative positions can better facilitate OL adoption amongst their student bodies by developing a keener awareness of students' goals and the factors influencing their views on the topic.

Gives a bibliographical review of the finite element meshing and remeshing from the theoretical as well as practical points of view. Topics such as adaptive techniques for meshing and remeshing, parallel processing in the finite element modelling, etc. are also included. The bibliography at the end of this paper contains 1,727 references to papers, conference proceedings and theses/dissertations dealing with presented subjects that were published between 1990 and 2001.