15 research outputs found
Development of efficient brain computer interface (BCI) system for stroke rehabilitation
No full textCritical Race Theory. Impact on Black Minority Ethnic Students within Higher Education
No full textThis book is an attempt to address the notion of Critical Race Theory (CRT) and the underlying parallels with the experiences of Black Minority Ethnic Students (BMEs) under the guise of Widening Participation policies and practices within the realms of Higher Education Institutions (HEIs). The book attempts to explore and compare the post entry academic and social inclusion concepts for BME non-traditional students. The author carried out an extensive level of investigation through her PhD titled “Critical Race Theory A Phenomenological Approach to Black Minority Ethnic Students within Higher Education Institutions”. Moreover, the author within the PhD work identified the habitus structuring models and the academic and social constraints applied within HEIs. This book attempts to illustrate the impact of CRT upon the recruitment, retention, race and racism, learning and teaching themes which are embedded within HEIs. Themes at macro level, meso and micro levels are investigated
Effects of night shift working on some immunological, prostate specific antigen, cortisol level and malondialdehyde in male nurses at Hawler city
No full textA low cost SSVEP-EEG based human-computer-interaction system for completely locked-in patients
No full textHuman computer interaction (HCI) for completely locked-in patients is a very difficult task. Nowadays, information technology (IT) is becoming an essential part of human life. Patients with completely locked-in state are generally unable to facilitate themselves by these useful technological advancements. Hence, they cannot use modern IT gadgets and applications throughout the lifespan after disability. Advancements in brain computer interface (BCI) enable operating IT devices using brain signals specifically when a person is unable to interact with the devices in conventional manner due to cognitive motor disability. However, existing state-of-the-art application specific BCI devices are comparatively too expensive. This paper presents a research and development work that aims to design and develop a low-cost general purpose HCI system that can be used to operate computers and a general purpose control panel through brain signals. The system is based on steady state visual evoked potentials (SSVEP). In proposed system, these electrical signals are obtained in response of a number of different flickering lights of different frequencies through electroencephalogram (EEG) electrodes and an open source BCI hardware. Successful trails conducted on healthy participants suggest that severely paralyzed subjects can operate a computer or control panel as an alternative to conventional HCI device
Comparative Analysis of Horizontal and Vertical Etched Fiber Bragg Sensor for Refractive Index Sensing
No full textCritical Race Theory: Impact on Black Minority Ethnic Students within Higher Education
No full text“This book arrives at a timely moment. The resurgence of the Black Lives Matter movement in the wake of widespread shock felt across the world over the murder of George Floyd at the hands of the police in the US has triggered a renewed concern with race equality and encouraged organisations, including universities, to reflect on what they are doing to address this issue. While we shall have to wait to see whether fine words are translated into effective actions, there is little doubt that universities are currently more willing to listen to BME voices.”– Professor Andrew Pilkington, University of Northampton, UK.“Historically, CRT follows the notion that there is considerable White bias evident in education and society generally (Bimper, 2017). Studies carried out by Ladson Billings believe that there is clear marginalisation regarding students coming from a BME background and in particular, those students for whom English is not their first language (Carrera, 2019). The author further examined the start of the movement for CRT. CRT began when a small group of activists wanted to understand better race, racism and power (Allen, 2017). The first real CRT movement began by focusing their attention on issues relating to conventional civil rights and ethnic study discourses which existed. They began by really questioning the liberal order addressing equality theory, legal reasoning, rationalism and the fundamental principles of constitutional law in America (Dixon, James, & Frieson, 2018). Regardless of the fact that CRT originated from a movement within Law it did, however, move beyond that discipline. The author further established within her research that educators in the main link themselves to CRT quite holistically (Garcia & Velez, 2018). Educational theorists apply CRT quite loosely to HEIs under the guise of school discipline and hierarchy, tracking, controversies over curriculum and history, IQ and achievement testing. Educational theorists do consider and associate CRT and endeavour to use its core principles to change the social situations present in society today.”ContentsCHAPTER 1 – IntroductionCHAPTER 2 – Critical Race Theory An Educational ConstructCHAPTER 3 – Research MethodologyCHAPTER 4 – Academic AttainmentCHAPTER 5 – Black Minority Ethnic ExperiencesCHAPTER 6 – The Societal CurriculumCHAPTER 7 – Government StrategyCHAPTER 8 – Thematic AnalysisCHAPTER 9 – Discussion and Theorising the FindingsCHAPTER 10 – Conclusions and Recommendation
Predictive Modeling of DWT-decomposed ALS-EMG Features Using Group Method of Data Handling
No full textAdvanced supervised machine learning methods for precise diabetes mellitus prediction using feature selection
No full textBackgroundDiabetes mellitus (DM) is a chronic metabolic disorder that poses a significant global health challenge, affecting millions, many of whom remain undiagnosed in the early stages. If left untreated, diabetes can result in severe complications such as blindness, stroke, cancer, joint pain, and kidney failure. Accurate and early prediction is critical for timely intervention. Recent advancements in machine learning techniques (MLT) have shown promising potential in enhancing disease prediction due to their robust pattern recognition and classification capabilities.Materials and methodsThis study presents a comparative analysis of supervised MLT such as Support Vector Machine (SVM), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF) using the Pima Indian Diabetes dataset (PIDD) from the UCI repository. A 10-fold cross-validation approach was employed to mitigate class imbalance and ensure generalizability. Performance was evaluated using standard classification metrics: accuracy, precision, recall, and F1-score.ResultsAmong the evaluated models, SVM outperformed the others with an accuracy of 91.5%, followed by RF (90%), KNN (89%), and NB (83%). The study highlights the effectiveness of SVM in early diabetes prediction and demonstrates how model performance varies with algorithm selection.ConclusionUnlike many prior studies that focus on a single algorithm or overlook validation robustness, this research offers a comprehensive comparison of popular classifiers and emphasizes the value of cross-validation in medical prediction tasks. The proposed framework advances the field by identifying optimal models for real-world diabetes risk assessment
Longitudinal patterns of behavioral, emotional, and social difficulties and self-concept in adolescents with a history of specific language impairment
No full textPurpose: This study explored the prevalence and stability of behavioral difficulties and self-concepts between 8 and 17 years in a sample of children with a history of specific language impairment (SLI). We investigated whether earlier behavioral, emotional and social difficulties (BESD), self-concepts, language, and literacy abilities predicted behavioral difficulties and self-concepts at 16/17 years.
Method: In this prospective longitudinal study, 65 students were followed up with teacher behavior ratings and individual assessments of language, literacy, and self-concepts at 8, 10, 12, 16, and 17 years.
Results: The students had consistently higher levels of five domains of BESD, which had different trajectories over time, and poorer scholastic competence, whose trajectory also varied over time. Earlier language ability did not predict later behavioral difficulties or self-concepts but the prediction of academic self-concept at 16 by literacy at 10 years approached significance.
Conclusions: We demonstrate the importance of distinguishing domains of behavioral difficulties and self-concept. Language, when measured at 8 or 10 years, was not a predictor of behavior or self-concepts at 16 years, or of self-concepts at 17 years. The study stresses the importance of practitioners addressing academic abilities and different social-behavioral domains in delivering support for adolescents with SLI
