A robust method for VR-based hand gesture recognition using density-based CNN

Many VR-based medical purposes applications have been developed to help patients with mobility decrease caused by accidents, diseases, or other injuries to do physical treatment efficiently. VR-based applications were considered more effective helper for individual physical treatment because of their low-cost equipment and flexibility in time and space, less assistance of a physical therapist. A challenge in developing a VR-based physical treatment was understanding the body part movement accurately and quickly. We proposed a robust pipeline to understanding hand motion accurately. We retrieved our data from movement sensors such as HTC vive and leap motion. Given a sequence position of palm, we represent our data as binary 2D images of gesture shape. Our dataset consisted of 14 kinds of hand gestures recommended by a physiotherapist. Given 33 3D points that were mapped into binary images as input, we trained our proposed density-based CNN. Our CNN model concerned with our input characteristics, having many 'blank block pixels', 'single-pixel thickness' shape and generated as a binary image. Pyramid kernel size applied on the feature extraction part and classification layer using softmax as loss function, have given 97.7% accuracy

Towards multisensory storytelling with taste and flavor

Film makers, producers, and theaters have continuously looked at ways to embody and/or integrate multiple sensory cues in the experiences they deliver. Here, we present a reflection on past attempts, lessons learnt, and future directions for the community around multisensory TV, film, and multimedia as a historical, though renewed, space of content creation. In particular, we present an overview of what we call "tasty film", that is, film involving taste, flavor, and more broadly food and drink inputs, to influence the audience experience. We suggest that such elements should be considered beyond "add-ons" in film experiences. We advocate for experimentation with new kinds of storytelling taking inspiration from multisensory design research and work on sensory substitution. We position this article as a starting point for anyone interested in multisensory film involving taste, flavor, and foods

Augmented Reality as a New and Innovative Learning Platform for the Medical Area

This research paper shows an Augmented Reality (AR) project applied to medicine. The project is crystallized through a system, based on this new technology that serves as an innovative and innovative learning platform, which, in turn, helps in both teaching and learning abstract concepts in medicine, which requires of visual and manipulable objects difficult to obtain, due to the large space they occupy in magnetic media or because of how difficult it is to get their models in physical form. The proposed system strengthens the anatomical identification process in the area of medicine, specifically in the physiological activity of the human heart. In addition, this system allows interaction with the students, through which certain body parts of the human heart are identified, and, consequently, facilitates their learning with an iterative operation. Finally, the system is focused, so that the student uses his/her sense of sight, hearing, and kinesthetic, which, together, will allow a better assimilation of knowledge

The Use of Binaural Based Spatial Audio in the Reduction of Auditory Hypersensitivity in Autistic Young People

Individuals diagnosed with autism spectrum disorder (ASD) are characterised as experiencing impairments in social-emotional interaction and communication, alongside frequently displaying repetitive behaviours and interests. Further to this, they are often described as experiencing difficulties in processing sensory information, with particular prevalence within the auditory modality. Provoked by common environmental sounds, auditory hypersensitivity can result in self-regulatory fear responses. Rather than a physiological pain reaction, literature suggests that these hypersensitivities are resulting through irrational fear of the sounds. This investigation evaluates the use of binaural based spatial audio as a rendering technique for delivering realistic simulations of averse stimuli within a virtual reality (VR) exposure based computer game intervention for auditory hypersensitivity in autism. Over multiple experimental sessions, 20 autistic participants experiencing auditory hypersensitivity were exposed to either spatial audio or stereo renders of target stimuli during the intervention. Measurements of self-reported emotions displayed significant reductions in associated negative emotional reactions to target stimuli for all participants. However, significant improvements were experienced by those listening to spatial audio simulations. Moreover, tracked voluntary interactions with exposure based game-mechanics increased as the study progressed. Providing further evidence of increased tolerance towards averse auditory stimuli

Automatic Collection Selection using Machine Learning

Most recent programming languages include a collection framework as part of their standard library (or runtime). Examples are Java, C#, Python and Ruby. The Java Collection Framework provides a number of collection classes, some of which implement the same abstract data type, which makes them interchangeable. Developers can therefore choose between several functionally equivalent options. Since collections have different performance characteristics, and may be allocated in thousands of programs locations, the choice of collection has an important impact on performance. Unfortunately, programmers often make sub-optimal choices when picking their collections.In this licentiate thesis, we consider the problem of building automated tooling, which would help the developer choose among several collection implementations. We consider an existing tool called Brainy, which targets C++, and adapt it to the Java context. In doing so, we investigate how to synthesize benchmarks and analyze their behavior to create training data for automated classification. We propose one new generative model for collection benchmarks and present the challenges that porting JBrainy to Java entails. Finally, we compare JBrainy's suggestions versus greedy search, on five well known benchmarks. Our investigations show that JBrainy's suggestions were almost as effective than those of greedy search in minimizing the running time of programs. However, we also find that Brainy's benchmark synthesis methods do not apply well to the Java context, since they introduce some significant biases

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

Maintenance contributes to gaining high business performance, guarantees system availability and reliability as well as safe and sustainable operations. Maintenance activity effectiveness depends on competences and the skills of operators whose performance strongly affects maintenance and production operations. The research field of human issues in industrial maintenance was deeply addressed in the literature; however, the current industrial paradigm, which focusses on the integration of new technologies in conventional manufacturing operations to support human performance, sheds light on new challenges for enterprises and opportunities for research in this field. While some literature reviews in the field of human errors and human factors are available, no study investigated the main topics, research trends and challenges related to the role of maintenance operators in manufacturing systems. This paper addresses the current state-of-the-art role of maintenance operators in manufacturing systems, providing an overview of the main studies. A systematic literature review was carried out to identify significant papers. Then, a topic modelling algorithm was used to detect the main topics of the selected papers to provide the research trends of the subject. The identified topics provided interesting research insights on the human role in industrial maintenance. Research trends and further research opportunities were defined

Tomographic reconstruction of circularly polarized high-harmonic fields: 3D attosecond metrology

Bright, circularly polarized, extreme ultraviolet (EUV) and soft x-ray high-harmonic beams can now be produced using counter-rotating circularly polarized driving laser fields. Although the resulting circularly polarized harmonics consist of relatively simple pairs of peaks in the spectral domain, in the time domain, the field is predicted to emerge as a complex series of rotating linearly polarized bursts, varying rapidly in amplitude, frequency, and polarization. We extend attosecond metrology techniques to circularly polarized light by simultaneously irradiating a copper surface with circularly polarized high-harmonic and linearly polarized infrared laser fields. The resulting temporal modulation of the photoelectron spectra carries essential phase information about the EUV field. Utilizing the polarization selectivity of the solid surface and by rotating the circularly polarized EUV field in space, we fully retrieve the amplitude and phase of the circularly polarized harmonics, allowing us to reconstruct one of the most complex coherent light fields produced to date.This work was done at JILA. We gratefully acknowledge support from the NSF through the Physics Frontiers Centers Program with grant no. PHY1125844 and the Gordon and Betty Moore Foundation EPiQS (Emergent Phenomena in Quantum Systems) Initiative through Grant GBMF4538 to M.M. C.H.-G. acknowledges support from the Marie Curie International Outgoing Fellowship within the European Union Seventh Framework Programme for Research and Technological Development (2007–2013), under Research Executive Agency grant agreement no. 328334. R.K. acknowledges the Swedish Research Council (VR) for financial support. A.J.-B. was supported by grants from the U.S. NSF (grant nos. PHY-1125844 and PHY-1068706). C.H.-G. and L.P. acknowledge support from Junta de Castilla y León (project SA116U13) and MINECO (Ministerio de Econom a y Competitividad) (FIS2013-44174-P and FIS2015-71933-REDT). This work used the Janus supercomputer, which is supported by the U.S. NSF (grant no. CNS-0821794) and the University of Colorado, Boulder. P.G. acknowledges support from the Deutsche Forschungsgemeinschaft (no. GR 4234/1-1)

Lawrence, Fall 2019

https://lux.lawrence.edu/alumni_magazines/1114/thumbnail.jp

1973 Bluestone

The Bluestone is the yearbook of Madison College.https://commons.lib.jmu.edu/allyearbooks/1066/thumbnail.jp