Characterization of the facial phenotype associated with fetal alcohol syndrome using stereo-photogrammetry and geometric morphometrics

Includes abstract.Includes bibliographical references (leaves 108-118).Fetal Alcohol Syndrome (FAS) is a clinical condition caused by excessive pre-natal alcohol exposure and is regarded as a leading identifiable and preventable cause of mental retardation in the Western world. The highest prevalence of FAS was reported in the wine-growing regions of South Africa but data for the rest of the country is not available. Required, therefore, are large-scale screening and surveillance programmes to be conducted in South Africa in order for the epidemiology of the disease to be understood. Efforts to this end have been stymied by the cost and labour-intensive nature of collecting the facial anthropometric data useful in FAS diagnosis. Stereo-photogrammetry provides a low cost, easy to use and non-invasive alternative to traditional facial anthropometry. The design and implementation of a landmark-based stereo-photogrammetry system to obtain 3D facial information for fetal alcohol syndrome diagnosis (FAS) is described. The system consists of three high resolution digital cameras resting on a purpose-built stand and a control frame which surrounds the subject's head during imaging. Reliability and assessments of accuracy for the stereo-photogrammetric tool are presented using 275 inter-landmark distance comparisons between the system and direct anthropometry using a doll. These showed the system to be highly reliable and precise

QoS Considerations in OBS Switched Backbone Net-Works

Optical Burst Switching (OBS) was proposed as a hybrid switching technology solution to handle the multi-Terabit volumes of traffic anticipated to traverse Future Generation backbone Networks. With OBS, incoming data packets are assembled into super-sized packets called data bursts and then assigned an end to end light path. Key challenging areas with regards to OBS Networks implementation are data bursts assembling and scheduling at the network ingress and core nodes respectively as they are key to minimizing subsequent losses due to contention among themselves in the core nodes. These losses are significant contributories to serious degradation in renderable QoS. The paper overviews existing methods of enhancing it at both burst and transport levels. A distributed resources control architecture is proposed together with a proposed wavelength assignment algorithm

Statistical analysis of facial landmark data for optimisation of Fetal Alcohol Syndrome diagnosis

Includes bibliographical references (leaves 100-104).This project involved the statistical analysis of facial landmark used in Fetal Alcohol Syndrome (FAS) diagnosis. FAS is a clinical condition caused by excessive maternal consumption of alcohol during pregnancy. Diagnosis of FAS depends on evidence of growth retardation, CNS neurodevelopment abnormalities, and a characteristic pattern of facial anomalies, specifically a short palpebral fissure length, smooth philtrum, flat upper lip and flat midface. The unique facial appearance associated with FAS is emphasized in diagnosis that relies, in part, on the comparison of linear measurements of facial features to population norms

Development of an assessment instrument for student engagement in design thinking projects for health innovation

Student engagement is a dynamic and multifaceted concept encompassing physical, emotional, and cognitive components. Various instruments to assess student engagement exist; however, these are not intended to assess how students engage with one another and with community stakeholders in participatory health projects. Although instruments exist to assess participation and power-sharing in participatory health research projects, none of the available tools are suitable for assessing student engagement in such projects. Accordingly, this study set out to develop an assessment instrument for student engagement in design thinking projects for health innovation. An adapted form of the survey development guide for medical education research was applied. The development process included triangulation of data, which included collating student input from an initial literature informed instrument, an analysis of written reflective reports and a focus group discussion with students enrolled in a master’s level course called Health Innovation & Design (HID), and design thinking practitioner validation. A final assessment instrument for student engagement in design thinking projects is presented. Note that our instrument incorporates the design thinking phases according to the Innovation Design Engineering Organization (IDEO) design thinking approach, an educational definition of student engagement, and recommendations by students, course lecturers and facilitators of the HID course. The instrument can assess engagement in academic and non-academic settings when design thinking is applied for health innovation

Negotiating boundaries: Framing and sense-making in a design thinking project with an elderly community

In recent years Design Thinking has established itself as a popular methodology for unlocking the creative potential that drives innovation, and scholars have begun to apply it in the health sector. However, as a conceptual framework, the approach has been criticised for lacking coherence and empirical validation. Although few have explicitly highlighted the central role of frame management in Design Thinking, we propose that much of the innovative potential, as outlined in its founding principles, stems from a concern with mental processes that contextualise new information to give it meaning and significance. Here we sought to address this gap by studying the framing process in two design teams tasked with developing solutions to assist an elderly population with compliance with medication schedules. Findings from a qualitative analysis indicate that although Design Thinking has clear merit as a methodology for helping designers shift beyond their immediate field of expertise, feedback and observations gathered during engagement with stakeholders inevitably appear to make their way through a filtering process where specific interpretations and meanings become censored and constrained by dominant discourses. Especially in the health sector, where information is sensitive, critical attention to the underlying value systems and prevailing discourses that influence designers’ implicit frames of reference is needed if Design Thinking is to gain credibility as a scientifically robust method for innovation. design thinking, framing, health innovation, medication adherenc

The influence of using a scientific calculator in learning fractions : a case study of one school in Gauteng Province

The main purpose of the research was to investigate the influence of scientific calculators on Grade 8 South African learner's understanding of fractions in learning mathematics. Quasi-experimental quantitative research methods were used. A sampling frame was selected using non probability sampling technique. A total of 15 learners in each group were randomly selected for an experimental and control group for the study. Both groups were taught fraction concepts by different teachers for the same duration and at the same time. The experimental group used a calculator as a learning aid while the control group used the traditional paper pencil method. Two tasks (post-test and assignment) were administered to both groups and a questionnaire to the experimental group. The results indicated that the scientific calculator has a positive influence in learner's conceptual understanding of fractions in mathematics as reflected in their performance.Mathematics EducationM. Ed. (Mathematics Education

Machine learning as an enabler of medical technology

Driven by advancements in digital computing, data storage, and the availability of large datasets from digitized healthcare workflows and telemedicine, machine learning is swiftly becoming integral to the most diverse aspects of medical technology. It's not merely about optimizing complex clinical tasks; it's also about fostering innovative applications such as large-scale image screening, data inference, and automatic diagnostics. Indeed, machine learning is a prerequisite for a radically new approach to these tasks, transcending the re-implementation of established technologies. This special issue spotlights papers where machine learning is an essential constituent of medical technology innovation

Measurement of Skin Induration Size Using Smartphone Images and Photogrammetric Reconstruction: Pilot Study

Background: The tuberculin skin test (TST) is the most common method for detecting latent tuberculosis infection (LTBI). The test requires that a patient return to the health facility or be visited by a health care worker 48 to 72 hours after the intradermal placement of tuberculin so that the size of the resulting skin induration, if any, can be measured. Objective: This study aimed to propose and evaluate an image-based method for measuring induration size from images captured using a smartphone camera. Methods: We imaged simulated skin indurations, ranging from 4.0 to 19 mm, in 10 subjects using a handheld smartphone, and performed three-dimensional reconstruction of the induration sites using photogrammetry software. An experienced TST reader measured the size of each induration using the standard clinical method. The experienced reader and an inexperienced observer both measured the size of each induration using the software. The agreement between measurements generated by the standard clinical and image-based methods was assessed using the intraclass correlation coefficient (ICC). Inter- and intraobserver agreement for the image-based method was similarly evaluated. Results: Results showed excellent agreement between the standard and image-based measurements performed by the experienced reader with an ICC value of .965. Inter- and intraobserver agreements were also excellent, indicating that experience in reading TSTs is not required with our proposed method. Conclusions: We conclude that the proposed smartphone image-based method is a potential alternative to standard induration size measurement and would enable remote data collection for LTBI screening