Consistent left gaze bias in processing different facial cues

While viewing faces, humans often demonstrate a natural gaze bias towards the left visual field, that is, the right side of the viewee’s face is often inspected first and for longer periods. Previous studies have suggested that this gaze asymmetry is part of the gaze pattern associated with face exploration, but its relation with perceptual processing of facial cues is unclear. In this study we recorded participants’ saccadic eye movements while exploring face images under different task instructions (free-viewing, judging familiarity and judging facial expression). We observed a consistent left gaze bias in face viewing irrespective of task demands. The probability of the first fixation and the proportion of overall fixations directed at the left hemiface were indistinguishable across different task instructions or across different facial expressions. It seems that the left gaze bias is an automatic reflection of hemispheric lateralisation in face processing, and is not necessarily correlated with the perceptual processing of a specific type of facial information

Developing a Mobile Application‐Based Particle Image Velocimetry Tool for Enhanced Teaching and Learning in Fluid Mechanics: A Design‐Based Research Approach

A robust and intuitive understanding of fluid mechanics—the applied science of fluid motion—is foundational within many engineering disciplines, including aerospace, chemical, civil, mechanical, naval, and ocean engineering. In‐depth knowledge of fluid mechanics is critical to safe and economical design of engineering applications employed globally everyday, such as automobiles, aircraft, and sea craft, and to meeting global 21st century engineering challenges, such as developing renewable energy sources, providing access to clean water, managing the environmental nitrogen cycle, and improving urban infrastructure. Despite the fundamental nature of fluid mechanics within the broader undergraduate engineering curriculum, students often characterize courses in fluid mechanics as mathematically onerous, conceptually difficult, and aesthetically uninteresting; anecdotally, undergraduates may choose to opt‐out of fluids engineering‐related careers based on their early experiences in fluids courses. Therefore, the continued development of new frameworks for engineering instruction in fluid mechanics is needed. Toward that end, this paper introduces mobile instructional particle image velocimetry (mI‐PIV), a low‐cost, open‐source, mobile application‐based educational tool under development for smartphones and tablets running Android. The mobile application provides learners with both technological capability and guided instruction that enables them to visualize and experiment with authentic flow fields in real time. The mI‐PIV tool is designed to generate interest in and intuition about fluid flow and to improve understanding of mathematical concepts as they relate to fluid mechanics by providing opportunities for fluids‐related active engagement and discovery in both formal and informal learning contexts

Using Computational Methods to Reinvigorate an Undergraduate Physics Curriculum

Austin Peay State University\u27s Department of Physics and Astronomy has reinvigorated its physics program by adding a required computational methods class and small computational components to classes across its curriculum. A front-to-back problem management approach has required a change in the way the department assesses students\u27 performance

3D spatio-temporal analysis for compressive sensing in magnetic resonance imaging of the murine cardiac cycle

This thesis consists of two major contributions, each of which has been prepared in a conference paper. These papers will be submitted for publication in the SPIE 2013 Medical Imaging Conference and the ASEE 2013 Annual Conference. The first paper explores a three-dimensional compressive sensing (CS) technique for reducing measurement time in MR imaging of the murine (mouse) cardiac cycle. By randomly undersampling a single 2D slice of a mouse heart at regular time intervals as it expands and contracts through the stages of a heartbeat, a CS reconstruction algorithm can be made to exploit transform sparsity in time as well as space. For the purposes of measuring the left ventricular volume in the mouse heart, this 3D approach offers significant advantages against classical 2D spatial compressive sensing. The second paper describes the modification and testing of a set of laboratory exercises for developing an undergraduate level understanding of Simulink. An existing partial set of lab exercises for Simulink was obtained and improved considerably in pedagogical utility, and then the completed set of pilot exercises was taught as a part of a communications course at the Missouri University of Science and Technology in order to gauge student responses and learning experiences. In this paper, the content of the laboratory exercises with corresponding educational approaches are discussed, along with student feedback and future improvements. --Abstract, page iv

Paralleizing AwSpPCA for robust facial recognition using CUDA

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.Cataloged from PDF version of thesis report.This paper was conducted to analyze the performance benefits of parallelizing the Adaptive Weighted Sub-patterned Principle Component Analysis (Aw SP PCA) algorithm, given that the algorithm is implemented so as to retain the accuracy from its serialized version. The serialized execution of this algorithm is analyzed first and then compared against its parallel implementation, both compiled and run on the same computer. Throughout this paper, the methodology is to undergo a step by step procedure which can clearly outline and describe the problems faced when trying to parallelize this algorithm. It will also describe where, how and why parallelizing procedures were used. The results of the research have shown that while not all parts of the algorithm can be implemented in parallel in the first place, some of the sections that can be parallelized does not necessarily yield a considerable amount of benefits. Also, it was seen that not all sections scale well with problem size, meaning that some portions of the algorithm can be left in its serialized state without much loss in time. The sections which can be parallelized were discussed in detail. Some changes were also made to certain variables to ensure the best accuracy possible. Finally, through analysis and experimentation, a speedup of 2.76 was achieved, with a recognition accuracy of 92.6%.Syed Amer ZawadAshfaque AliB. Computer Science and Engineerin

Computing and Information Science (CIS)

Cornell University Courses of Study Vol. 97 2005/200

A Web-Shareable Real-World Imaging Problem for Enhancing an Image-Processing Curriculum

A real-world laboratory exercise is presented for image processing and related curricula. The exercise is a traffic-monitoring problem in which a truck must be tracked as it moves across a bridge and its velocity measured. Sequential images are taken from a dedicated Web camera that views the Smart Composite Bridge on the University of Missouri-Rolla campus. The prototype bridge is a field laboratory for several interdisciplinary courses, including a Machine Vision elective. The Machine Vision image-processing elective uses the traffic-monitoring exercise to give students experience with processing complex images, tracking image markers, and applying theoretical orthographic concepts. The laboratory exercise uses an image sequence acquired during the springtime with multiple potential markers available on the truck for assignment flexibility. A wintertime image sequence with snowy conditions is also available for assignment flexibility. This paper discusses the bridge and camera resources, the traffic-monitoring laboratory exercise description, and the Machine Vision course implementation and evaluation. Two versions of the traffic-monitoring exercise, including two image sequences and orthographic MATLAB code, are available on the bridge Website

1st INCF Workshop on Needs for Training in Neuroinformatics

The INCF workshop on Needs for Training in Neuroinformatics was organized by the INCF National Node of the UK. The scope of the workshop was to provide as overview of the current state of neuroinformatics training and recommendations for future provision of training. The report presents a summary of the workshop discussions and recommendations to the INCF

Computing and Information Science

Cornell University Courses of Study Vol. 98 2006/200

Innovative pedagogical practices in the craft of Computing

Computer programming, the art of actually instructing a computer to do what one wants, is fundamentally a practical skill. How does one teach this practical skill in a university setting, to students who may not be initially motivated to acquire it, and who may have a variety of past experience, or none at all? Furthermore, how does one do it in a resource-efficient way to large classes? Students are largely motivated by assessment: what is the best way to assess this skill? How does this skill relate to more abstract concepts like “computational thinking”? In this piece NTFs from very different universities explain their solutions