• The proposed SWF tokenization method, dynamically capturing emotional subtleties, noise robustness, and contextual information to robustly preserve speaker identity. • A transformative deep-self-supervised spectrogram transformer back-end, outperforming conventional approaches by effectively addressing their inherent limitations in preserving local features without the need for extensive labeled training data. • Complete elimination of dependency on additional speech enhancement, enabling seamless, efficient, and robust end-to-end learning tailored for real-world deployments. Identifying speakers in noisy and emotional conditions remains a significant challenge due to the distortion of spectral cues. This study proposes the Speech Without Filter (SWF) framework, a novel self-supervised learning paradigm that operates directly on raw spectrograms. Theoretically, this research introduces a progressive tokenization mechanism that acts as a structural inductive bias, mimicking the contracting path of a U-Net to preserve local spectro-temporal continuity. Unlike standard fixed-patch Transformers that often smooth over speaker-specific micro-textures, the SWF architecture integrates denoising and feature extraction into a single stage, challenging the traditional decoupled paradigm of speech enhancement and recognition. Using a sample of 1.58 million pre-training instances, the model was evaluated across English (RAVDESS), Arabic (ESD), and stressful (SUSAS) datasets. Results demonstrate significant improvements, with the SWF model achieving 91.01% accuracy in clean conditions and maintaining 88.5% in high-noise cocktail party environments, outperforming state-of-the-art models like WavLM and HuBERT. These findings suggest that architectural innovation in tokenization is as critical as pre-training scale for robust speech processing.

Cable driven exoskeletons are preferred over link-driven exoskeletons due to numerous advantages such as remote actuation, lightweight, reconfigurability, and many more. PD (proportional derivative) controllers are widely implemented in exoskeletons due to simplicity and faster response. However, in cable driven exoskeleton, the PD controller doesn't directly distribute the cable tension and thus the possibility of tracking error is higher. In this work, we formulated a non-linear model predictive controller (NMPC) for C-LREX that directly allocates cable tension and is further simplified to reduce the time delay. The simulation result indicated that simplified NMPC is faster than NMPC but slower than PD for C-LREX. NMPCs tracked trajectory with the least error, however, allocated higher cable tension. PD should be preferred when speed is prioritized while NMPC should be preferred for performance.

A notable gap exists between the competencies that employers in the UAE want entry-level engineers to exhibit and the knowledge, skills and attitudes these fresh engineering graduates from UAE tertiary institutions are able to successfully demonstrate. Inadequate preparation of engineers in key competencies has been cited as one of the main threats to the sustainable development of the region. Misalignment between education and employers' needs was indicated as one of the main reasons behind the skills gaps. A multi-stage project has been launched to explore this misalignment. This paper focuses on Stage 1 of this multi-stage project: the scoping of the research design methodology for the analysis of job advertisements and an employer questionnaire, as well as the results from a preliminary content analysis of three job advertisements for entry-level engineers in the UAE.

A notable gap exists between the competencies that employers in the UAE want entry-level engineers to exhibit and the knowledge, skills and attitudes these fresh engineering graduates from UAE tertiary institutions are able to successfully demonstrate. Inadequate preparation of engineers in key competencies has been cited as one of the main threats to the sustainable development of the region. Misalignment between education and employers' needs was indicated as one of the main reasons behind the skills gaps. A multi-stage project has been launched to explore this misalignment. This paper focuses on Stage 1 of this multi-stage project: the scoping of the research design methodology for the analysis of job advertisements and an employer questionnaire, as well as the results from a preliminary content analysis of three job advertisements for entry-level engineers in the UAE.

This work presents an innovative interdisciplinary cornerstone engineering design-and-build course infused at the freshman level. The course promotes systematic design thinking and process using an inductive pedagogy, PBL, as the mode of delivery, in conjunction with technological tools such as robotics kits, a rapid prototyping machine, and C++ interface.

While internationally there is an awareness that we need new, innovative approaches to engineering education, it is unclear whether a pioneering pedagogy within one cultural context will readily transfer and find acceptance in a very different cultural context. In this paper, we report on a three-site, collaborative experiment in using problem-driven learning in an introductory engineering class. Our three sites are universities in the United States, Abu Dhabi and China. In each location, first year students in biomedical engineering begin the major by joining a team of students who tackle real-world, open-ended problems. Our paper will report on 1) the development and exchange of problems across the three sites, 2) the different constraints, realizations and outcomes of the problem-driven approach at each of using problem-driven learning as a transnational pedagogy for 21stcentury engineering education.