Mechatronic system usability evaluation

This study aimed to refine and validate a Mechatronic System Usability Evaluation (MSUE) questionnaire. A total of 626 users were selected using random sampling, from the area of West Thessaloniki, Greece. The validity of the questionnaire were tested with the content and construction validity method. The reliability of the MSUE questionnaire instrument were tested using test-retest and internal consistency method. Factor analysis resulted a 25 questions questionnaire divided into five axes of, namely efficiency, effectiveness, Satisfaction, ease of use, and ease of learn. The Cronbach Alpha coefficient for the entire scale was 0.819. The questionnaire was tested and the results was shown a suitable instrument to measure usability on mechatronic systemsPeer Reviewe

Adaptive Regression Methods with Application to Streaming Financial Data

This thesis is concerned with the analysis of adaptive incremental regression algorithms for data streams. The development of these algorithms is motivated by issues pertaining to financial data streams, data which are very noisy, non-stationary and exhibit high degrees of dependence. These incremental regression techniques are subsequently used to develop efficient and adaptive algorithms for portfolio allocation. We develop a number of temporally incremental regression algorithms that have the following attributes; efficiency: the algorithms are iterative, robustness: the algorithms have a built-in safeguard for outliers and/or use regularisation techniques to alleviate for estimation error, and adaptiveness: the algorithms estimation is adaptive to the underlying streaming data. These algorithms make use of known regression techniques: EWRLS (Exponentially Weighted Recursive Least Squares), TSVD (Truncated Singular Value Decomposition) and FLS (Flexible Least Squares). We focus more of our attention on a proposed robust version of EWRLS algorithm, denoted R-EWRLS, and assess its robustness using a purpose built simulation engine. This simulation engine is able to generate correlated data streams whose drift and correlation change over time and can be subjected to randomly generated outliers whose magnitudes and directions vary. The R-EWRLS algorithm is developed further to allow for a self-tuned forgetting factor in the formulation. The forgetting factor is an important tool to account for non-stationarity in the data through an exponential decay profile which assigns more weight to the more recent data. The new algorithm is assessed against the R-EWRLS algorithm using various performance measures. A number of applications with real data from equities and foreign exchange are used. Various measures are computed to compare our algorithms to established portfolio allocation techniques. The results are promising and in many cases outperform benchmark allocation techniques

Train the robotic trainers methodology

This work reflects the importance of a methodology for robotic train the trainer’s education program, through the aspects of teaching pedagogy, technology and the basic principles of robotics. To achieve this, a methodology is included that contains a sequence of educational processes and applications focused on modern training techniques. Learners are invited to attend a theoretical background of the program for two days (first weekend) with traditional training methods, and then for four weeks using e-learning techniques they study the material, interact with the teacher and submit their work for evaluation. Afterwards in the second weekend, the training is completed and the trainees are closing the program with a micro teaching example. Upon completion of the program, each trainee completes a short questionnaire from which his / her motivation to participate and his / her satisfaction from his / her participation arise. In the course of the survey, 85 trainees participated, and from the questionnaire\u27s work, the overwhelming majority is very satisfied, which highlights this methodology and determines it to be fully operational, reliable and efficient. (DIPF/Orig.

Educational robotics. The pleasure of participation

The paper attempts to identify the pleasure and satisfaction of participating in educational robotic through an educational robotic program that takes place for children ages 9 to 15. The aim is also to identify, with the use of statistical comparisons, any signs of the relationship between pleasure and satisfaction with participation with characteristics such as the gender of learners, the age of learners and the level of parenting. The survey showed that the participants were satisfied with their participation in the program and did not feel tired or bored. Also from the research is obvious that through educational robotics children can learn to cooperate more effectively with each other, and the teaching of basic principles of computer science, mathematics, geometry, physics, engineering, and in general mechatronics can be more effective when it does not have the conventional form of education but it has the form of play. (DIPF/Orig.

Paired associative stimulation as a tool to assess plasticity enhancers in chronic stroke

Background and Purpose: The potential for adaptive plasticity in the post-stroke brain is difficult to estimate, as is the demonstration of central nervous system (CNS) target engagement of drugs that show promise in facilitating stroke recovery. We set out to determine if paired associative stimulation (PAS) can be used (a) as an assay of CNS plasticity in patients with chronic stroke, and (b) to demonstrate CNS engagement by memantine, a drug which has potential plasticity-modulating effects for use in motor recovery following stroke. Methods: We examined the effect of PAS in fourteen participants with chronic hemiparetic stroke at five time-points in a within-subjects repeated measures design study: baseline off-drug, and following a week of orally administered memantine at doses of 5, 10, 15, and 20 mg, comprising a total of seventy sessions. Each week, MEP amplitude pre and post-PAS was assessed in the contralesional hemisphere as a marker of enhanced or diminished plasticity. Strength and dexterity were recorded each week to monitor motor-specific clinical status across the study period. Results: We found that MEP amplitude was significantly larger after PAS in baseline sessions off-drug, and responsiveness to PAS in these sessions was associated with increased clinical severity. There was no observed increase in MEP amplitude after PAS with memantine at any dose. Motor threshold (MT), strength, and dexterity remained unchanged during the study. Conclusion: Paired associative stimulation successfully induced corticospinal excitability enhancement in chronic stroke subjects at the group level. However, this response did not occur in all participants, and was associated with increased clinical severity. This could be an important way to stratify patients for future PAS-drug studies. PAS was suppressed by memantine at all doses, regardless of responsiveness to PAS off-drug, indicating CNS engagement

NeuroMeasure: A Software Package for Quantification of Cortical Motor Maps Using Frameless Stereotaxic Transcranial Magnetic Stimulation

The recent enhanced sophistication of non-invasive mapping of the human motor cortex using MRI-guided Transcranial Magnetic Stimulation (TMS) techniques, has not been matched by refinement of methods for generating maps from motor evoked potential (MEP) data, or in quantifying map features. This is despite continued interest in understanding cortical reorganization for natural adaptive processes such as skill learning, or in the case of motor recovery, such as after lesion affecting the corticospinal system. With the observation that TMS-MEP map calculation and quantification methods vary, and that no readily available commercial or free software exists, we sought to establish and make freely available a comprehensive software package that advances existing methods, and could be helpful to scientists and clinician-researchers. Therefore, we developed NeuroMeasure, an open source interactive software application for the analysis of TMS motor cortex mapping data collected from Nexstim® and BrainSight®, two commonly used neuronavigation platforms. NeuroMeasure features four key innovations designed to improvemotor mapping analysis: de-dimensionalization of the mapping data, fitting a predictive model, reporting measurements to characterize the motor map, and comparing those measurements between datasets. This software provides a powerful and easy to use workflow for characterizing and comparing motor maps generated with neuronavigated TMS. The software can be downloaded on our github page: https://github.com/EdwardsLabNeuroSci/NeuroMeasure. AIM This paper aims to describe a software platform for quantifying and comparing maps of the human primarymotor cortex, using neuronavigated transcranialmagnetic stimulation, for the purpose of studying brain plasticity in health and diseas

The association of thinking styles with research agendas among academics in the social sciences

Research agendas are understudied, despite being key to academic knowledge creation. The literature suggests that the ways that academics determine their research agendas are conditioned by individual, organisational and environmental characteristics. This study explores the cognitive aspects of academics' research agendas in the social sciences by using a theory on thinking styles as an analytical framework. The results suggest that the research agendas of academics in the social sciences are significantly associated with their thinking styles. These findings aid understanding of how academics set their research agendas. This study also represents an important landmark in research on thinking styles, focusing on academic research work as a potential venue for further studies. The findings are relevant for policymakers, research funding agencies, university administrators and academics because they have implications for academic research development processes, outcomes, and for research and academic identity socialisation during doctoral studies.info:eu-repo/semantics/acceptedVersio