COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks

The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach—The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings—The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.

A New Density-Based Clustering Method Considering Spatial Distribution of Lidar Point Cloud for Object Detection of Autonomous Driving

Lidar is a key sensor of autonomous driving systems, but the spatial distribution of its point cloud is uneven because of its scanning mechanism, which greatly degrades the clustering performance of the traditional density-based spatial clustering of application with noise (DSC). Considering the outline feature of detected objects for intelligent vehicles, a DSC-based adaptive clustering method (DAC) is proposed with the adoption of an elliptic neighborhood, which is designed according to the distribution properties of the point cloud. The parameters of the ellipse are adaptively adjusted with the location of the sample point to deal with the uniformity of points in different ranges. Furthermore, the dependence among different parameters of DAC is analyzed, and the parameters are numerically optimized with the KITTI dataset by considering comprehensive performance. To verify the effectiveness, a comparative experiment was conducted with a vehicle equipped with three IBEO LUX8 lidars on campus, and the results show that compared with DSC using a circular neighborhood, DAC has a better clustering performance and can notably reduce the rate of over-segmentation and under-segmentation.

Compact Slotted Waveguide Antenna Array Using Staircase Model of Tapered Dielectric-Inset Guide for Shipboard Marine Radar

This paper presents a new configuration of a slotted waveguide antenna (SWA) array aimed at the X-band within the desired band of 9.38~9.44 GHz for shipboard marine radars. The SWA array, which typically consists of a slotted waveguide, a polarizing filter, and a metal reflector, is widely employed in marine radar applications. Nonetheless, conventional slot array designs are weighty, mechanically complex, and geometrically large to obtain high performances, such as gain. These features of the conventional SWA are undesirable for the shipboard marine radar, where the antenna rotates at high angular speed for the beam scanning mechanism. The proposed SWA array herein reduces the conventional design’s size by 62% using a tapered dielectric-inset guide structure. It shows high gain performance (up to 30 dB) and obtains improvements in radiation efficiency (up to 80% in the numerical simulations) and weight due to the use of loss and low-density dielectric material.

A web browsing interface for people with severe speech and motor impairment

Purpose The Web has become an indispensable medium used by people across the world for education, information, entertainment, social interaction as well as for various daily activities involving shopping and employment-related tasks. It is therefore becoming increasingly essential that the Web must be accessible to all people to provide equal access and equal opportunity. This is specifically more important for people with various kind of disabilities. Several initiatives such as development of Web accessibility guidelines, tools and technologies have been undertaken to make the Web usable for people with different disabilities. However, only a handful of them are aimed at people with Severe Speech and Motor Impairment (SSMI). This paper aims to present a Web browsing interface for people with severe speech and motor impairment. Design/methodology/approach The browser allows easy dissemination of information through World Wide Web for people with SSMI. The browser is augmented with both automatic as well as manual scanning mechanisms through which a motor disorder person can access the browser graphical user interface (GUI). Further, the browser provides an intelligent content scanning mechanism through which the Web contents can be accessed with less time and cognitive effort. Along with the desktop version, WebSanyog is successfully ported on Android-based tablets to make the system portable. Findings The system has been exhaustively field tested by people with SSMI. The browser has been deployed at the Indian Institute of Cerebral Palsy (IICP), Kolkata. The performance of the browser has been measured in terms of three parameters: The Task execution time (TET); Error rates analysis (ER); and Overall usability score by the subject. The evaluation results suggests that the proposed Web browsing interface is effective in terms of task execution time, cognitive effort and overall user satisfaction. Originality/value The browser GUI is integrated with an automatic scanning mechanism as an alternate way to access and navigate through Web pages, instead of using keyboard and mouse. The browser provides novel content access mechanisms that makes navigating through Web page contents like links, images and embedded videos easier and faster. To facilitate text entry, the browser provides two different options, namely, the predictive virtual scanning keyboard and a novel icon-based query entry scheme that allows generating search queries through the selection of multiple icons.

An ultrahigh-resolution soft x-ray microscope for quantitative analysis of chemically heterogeneous nanomaterials

The analysis of chemical states and morphology in nanomaterials is central to many areas of science. We address this need with an ultrahigh-resolution scanning transmission soft x-ray microscope. Our instrument provides multiple analysis tools in a compact assembly and can achieve few-nanometer spatial resolution and high chemical sensitivity via x-ray ptychography and conventional scanning microscopy. A novel scanning mechanism, coupled to advanced x-ray detectors, a high-brightness x-ray source, and high-performance computing for analysis provide a revolutionary step forward in terms of imaging speed and resolution. We present x-ray microscopy with 8-nm full-period spatial resolution and use this capability in conjunction with operando sample environments and cryogenic imaging, which are now routinely available. Our multimodal approach will find wide use across many fields of science and facilitate correlative analysis of materials with other types of probes.

New Measures of Visual Scanning Efficiency and Cognitive Effort

Visual scanning plays an important role in sampling visual information from the surrounding environments for a lot of everyday sensorimotor tasks, such as walking and car driving. In this paper, we consider the problem of visual scanning mechanism underpinning sensorimotor tasks in 3D dynamic environments. We exploit the use of eye tracking data as a behaviometric, for indicating the visuo-motor behavioral measures in the context of virtual driving. A new metric of visual scanning efficiency (VSE), which is defined as a mathematical divergence between a fixation distribution and a distribution of optical flows induced by fixations, is proposed by making use of a widely-known information theoretic tool, namely the square root of Jensen-Shannon divergence. Based on the proposed efficiency metric, a cognitive effort measure (CEM) is developed by using the concept of quantity of information. Psychophysical eye tracking studies, in virtual reality based driving, are conducted to reveal that the new metric of visual scanning efficiency can be employed very well as a proxy evaluation for driving performance. In addition, the effectiveness of the proposed cognitive effort measure is demonstrated by a strong correlation between this measure and pupil size change. These results suggest that the exploitation of eye tracking data provides an effective behaviometric for sensorimotor activity.

Multi-beam X-ray ptychography for high-throughput coherent diffraction imaging

X-ray ptychography is a rapidly developing coherent diffraction imaging technique that provides nanoscale resolution on extended field-of-view. However, the requirement of coherence and the scanning mechanism limit the throughput of ptychographic imaging. In this paper, we propose X-ray ptychography using multiple illuminations instead of single illumination in conventional ptychography. Multiple locations of the sample are simultaneously imaged by spatially separated X-ray beams, therefore, the obtained field-of-view in one scan can be enlarged by a factor equal to the number of illuminations. We have demonstrated this technique experimentally using two X-ray beams focused by a house-made Fresnel zone plate array. Two areas of the object and corresponding double illuminations were successfully reconstructed from diffraction patterns acquired in one scan, with image quality similar with those obtained by conventional single-beam ptychography in sequence. Multi-beam ptychography approach increases the imaging speed, providing an efficient way for high-resolution imaging of large extended specimens.