Using Pinch Gloves(TM) for both Natural and Abstract Interaction Techniques in Virtual Environments

Usable three-dimensional (3D) interaction techniques are difficult to design, implement, and evaluate. One reason for this is a poor understanding of the advantages and disadvantages of the wide range of 3D input devices, and of the mapping between input devices and interaction techniques. We present an analysis of Pinch Gloves™ and their use as input devices for virtual environments (VEs). We have developed a number of novel and usable interaction techniques for VEs using the gloves, including a menu system, a technique for text input, and a two-handed navigation technique. User studies have indicated the usability and utility of these techniques

Interaction techniques for older adults using touchscreen devices : a literature review

International audienceSeveral studies investigated different interaction techniques and input devices for older adults using touchscreen. This literature review analyses the population involved, the kind of tasks that were executed, the apparatus, the input techniques, the provided feedback, the collected data and author's findings and their recommendations. As conclusion, this review shows that age-related changes, previous experience with technologies, characteristics of handheld devices and use situations need to be studied

Time and space integrating acousto-optic folded spectrum processing for SETI

Time and space integrating folded spectrum techniques utilizing acousto-optic devices (AOD) as 1-D input transducers are investigated for a potential application as wideband, high resolution, large processing gain spectrum analyzers in the search for extra-terrestrial intelligence (SETI) program. The space integrating Fourier transform performed by a lens channels the coarse spectral components diffracted from an AOD onto an array of time integrating narrowband fine resolution spectrum analyzers. The pulsing action of a laser diode samples the interferometrically detected output, aliasing the fine resolution components to baseband, as required for the subsequent charge coupled devices (CCD) processing. The raster scan mechanism incorporated into the readout of the CCD detector array is used to unfold the 2-D transform, reproducing the desired high resolution Fourier transform of the input signal

DL-Droid: Deep learning based android malware detection using real devices

open access articleThe Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection avoidance methods have significantly improved, making many traditional malware detection methods obsolete. In this paper, we propose DL-Droid, a deep learning system to detect malicious Android applications through dynamic analysis using stateful input generation. Experiments performed with over 30,000 applications (benign and malware) on real devices are presented. Furthermore, experiments were also conducted to compare the detection performance and code coverage of the stateful input generation method with the commonly used stateless approach using the deep learning system. Our study reveals that DL-Droid can achieve up to 97.8% detection rate (with dynamic features only) and 99.6% detection rate (with dynamic + static features) respectively which outperforms traditional machine learning techniques. Furthermore, the results highlight the significance of enhanced input generation for dynamic analysis as DL-Droid with the state-based input generation is shown to outperform the existing state-of-the-art approaches