Computer Aided Simulation of a 4BL Engineering Problem Using Matlab

Abstract: The synthesis and analysis of four bar mechanisms is well known classical design problem. However limitations to the classical theory of this problem potentially limit its application to certain real world problems by virtue of the small number of precision points and unspecified order. In this paper we describe an improved computer aided simulator (CAS) for visualizing a four bar link (4BL -simple movable closed chain linkage) mechanism engineering problem using MATLAB software. The aim is to facilitate the analysis, dynamic simulation of the four-bar mechanisms. First, a brief review of some of the current computer-aided learning software for four-bar mechanisms is presented. These software packages provide two-dimensional visualization and computational capabilities necessary to synthesize and analyze four-bar mechanisms. However, to date, no readily available and effective tools exist to aid in the understanding of 4BL mechanisms due to misinterpretation of data. The paper also reviews the kinematics of four-bar mechanisms as they pertain to their geometric modelling followed by the design approach of the graphical MATLAB CAS for four-bar mechanisms. A preliminary validation test using pre and postest questionnaires and focus group discussion with student participation in using the MATLAB CAS tool has facilitated in visualizing the engineering concepts of 4BL mechanism at UNITEN

Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets

The core aim of this study is to determine the most effective outlier detection methodologies for multivariate psychological datasets, particularly those derived from Omani students. Due to their complex nature, such datasets demand robust analytical methods. To this end, we employed three sophisticated algorithms: local outlier factor (LOF), one-class support vector machine (OCSVM), and isolation forest (IF). Our initial findings showed 155 outliers by both LOF and IF and 147 by OCSVM. A deeper analysis revealed that LOF detected 55 unique outliers based on differences in local density, OCSVM isolated 44 unique outliers utilizing its transformed feature space, and IF identified 76 unique outliers leveraging its tree-based mechanics. Despite these varying results, all methods had a consensus for just 44 outliers. Employing ensemble techniques, both averaging and voting methods identified 155 outliers, whereas the weighted method highlighted 151, with a consensus of 150 outliers across the board. In conclusion, while individual algorithms provide distinct perspectives, ensemble techniques enhance the accuracy and consistency of outlier detection. This underscores the necessity of using multiple algorithms with ensemble techniques in analyzing psychological datasets, facilitating a richer comprehension of inherent data structures

A framework for correcting human motion alignment for traditional dance training using augmented reality

This paper presents a framework for motion capture analysis for dance learning technology using Microsoft Kinect V2. The proposed technology utilizes motion detection, emotion analysis, coordination analysis and interactive feedback techniques for a particular dance style selected by the trainee.This motion capture system solves the heterogeneity of the existing dance learning system and hence provides robustness. The analysis of the proposed work is carried out using query techniques and heuristic evaluation. The Microsoft Kinect V2 embedded with Augmented Reality (AR) technology is explored to demonstrate the recognition accuracy of the proposed framework

Learning Analytics and Teaching Analytics: The Similarities and Differences

Analytics in education which constitutes of Learning Analytics and Teaching Analytics arouses great attention among researchers and practitioners in the current climate. The use of analytics in education enables educational data to be collected and analysed to serve the needs of all stakeholders to improve the educational process. The present paper gives an overview of Learning Analytics and Teaching Analytics and explores its similarities and differences, as well as the confusion that has been raised between the two defined terms. Alongside, the analytics selection flowchart presented in this paper provides a breakdown on the analytics research direction for Learning Analytics and Teaching Analytics. A deeper and varied understanding of Learning Analytics and Teaching Analytics is imperative for establishing effective and accurate analytical tools alongside with recommendations for improvement in the future

A review on making things see: Augmented reality for futuristic virtual educator

In the past few years many choreographers have focused upon implementation of computer technology to enhance their artistic skills. Computer vision technology presents new methods for learning, instructing, developing, and assessing physical movements as well as provides scope to expand dance resources and rediscover the learning process. This work reviews the study done over AR based learning technologies for the development of inter personal skills. This paper further elaborates the literature done till date within the scope of AR based training for educational aspects. The review focuses on the techniques categorized according to the type of dance learning method which can further be enhanced and addressed by means of novel AR based technology. The authors aim to provide an overview for learning standards based on AR Kinect sensors. In addition the future work is toward exploring the latest version of Kinect V2 for dance training that could become the next futuristic virtual educator