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This paper presents an all-dielectric, cascaded, multilayered, thin-film filter, allowing near-infrared filtration for spectral imaging applications. The proposed design is comprised of only eight layers of amorphous silicon (A-Si) and silicon nitride (Si3N4), successively deposited on a glass substrate. The finite difference time domain (FDTD) simulation results demonstrate a distinct peak in the near-infrared (NIR) region with transmission efficiency up to 70% and a full-width-at-half-maximum (FWHM) of 77 nm. The theoretical results are angle-insensitive up to 60° and show polarization insensitivity in the transverse magnetic (TM) and transverse electric (TE) modes. The theoretical response, obtained with the help of spectroscopic ellipsometry (SE), is in good agreement with the experimental result. Likewise, the experimental results for polarization insensitivity and angle invariance of the thin films are in unison with the theoretical results, having an angle invariance up to 50°.

Device-free localization (DFL) systems that rely on the wireless received signal strength indicator (RSSI) metric have been reported in literature for almost a decade. Histogram distance-based DFL (HD-DFL) techniques that operate by constructing RSSI histograms are highly effective as they can localize stationary and moving people in both outdoor and complex indoor environments. A key step in the histogram approaches is the estimation of the difference between the “long-term” and “short-term” histograms. The existing HD-DFL methods use either Kullback–Leibler or the subsequent improvement, kernel distance, to measure this difference. This paper is the first known work to compare an extensive range of histogram distance metrics within a DFL context and demonstrate how a judicious selection of a distance metric can significantly increase the performance of an HD-DFL system. The results from practical implementation in two different environments show that some distance metrics perform considerably better than the kernel distance when used for existing DFL techniques, such as radio tomographic imaging (RTI) and SpringLoc, with the overall median tracking error reducing by up to 25%.

Device-free localization (DFL) systems that rely on the wireless received signal strength indicator (RSSI) metric to localize targets with no device attached to them have been reported in the literature for almost a decade. Approaches using RSSI can be split into three main categories. Link-based approaches utilize weighted summation or probabilistic methods to infer location. Location-based approaches create a fingerprint map of an area. Radio Tomographic Imaging treat DFL as an imaging problem solved with a linear inverse. In this paper, we implement and investigate the performance of all three major RSSI approaches in two test environments. We demonstrate how different environments and walking trajectories can have significant effects on the localization accuracy. The experimental results lead us to the conclusion that without implementing and testing within the same environment for the same target trajectories, the performance of various classes of DFL systems cannot be reliably evaluated. Relying on the stated accuracy from the literature for comparison is a flawed premise.

Device-free localization (DFL) algorithms using the received signal strength indicator (RSSI) metrics have become a popular research focus in recent years as they allow for location-based service using commercial-off-the-shelf (COTS) wireless equipment. However, most existing DFL approaches have limited applicability in realistic smart home environments as they typically require extensive offline calibration, large node densities, or use technology that is not readily available in commercial smart homes. In this paper, we introduce SpringLoc and a DFL algorithm that relies on simple parameter tuning and does not require offline measurements. It localizes and tracks an entity using an adaptive spring relaxation approach. The anchor points of the artificial springs are placed in regions containing the links that are affected by the entity. The affected links are determined by comparing the kernel-based histogram distance of successive RSSI values. SpringLoc is benchmarked against existing algorithms in two diverse and realistic environments, showing significant improvement over the state-of-the-art, especially in situations with low-node deployment density.

This paper presents an autonomous method of collecting data for Visible Light Positioning (VLP) and a comprehensive investigation of VLP using a large set of experimental data. Received Signal Strength (RSS) data are efficiently collected using a novel method that utilizes consumer grade Virtual Reality (VR) tracking for accurate ground truth recording. An investigation into the accuracy of the ground truth system showed median and 90th percentile errors of 4.24 and 7.35 mm, respectively. Co-locating a VR tracker with a photodiode-equipped VLP receiver on a mobile robotic platform allows fingerprinting on a scale and accuracy that has not been possible with traditional manual collection methods. RSS data at 7344 locations within a 6.3 × 6.9 m test space fitted with 11 VLP luminaires is collected and has been made available for researchers. The quality and the volume of the data allow for a robust study of Machine Learning (ML)- and channel model-based positioning utilizing visible light. Among the ML-based techniques, ridge regression is found to be the most accurate, outperforming Weighted k Nearest Neighbor, Multilayer Perceptron, and random forest, among others. Model-based positioning is more accurate than ML techniques when a small data set is available for calibration and training. However, if a large data set is available for training, ML-based positioning outperforms its model-based counterparts in terms of localization accuracy.

Objective Small angle X-ray scattering (SAXS) analysis is a sensitive way of determining the ultrastructure of collagen in tissues. Little is known about how parameters measured by SAXS are affected by preservatives commonly used to prevent autolysis. We determined the effects of formalin, glutaraldehyde, Triton X and saline on measurements of fibril diameter, fibril diameter distribution, and D-spacing of corneal collagen using SAXS analysis. Results Compared to sections of sheep and cats’ corneas stored frozen as controls, those preserved in 5% glutaraldehyde and 10% formalin had significantly larger mean collagen fibril diameters, increased fibril diameter distribution and decreased D-spacing. Sections of corneas preserved in Triton X had significantly increased collagen fibril diameters and decreased fibril diameter distribution. Those preserved in 0.9% saline had significantly increased mean collagen fibril diameters and decreased diameter distributions. Subjectively, the corneas preserved in 5% glutaraldehyde and 10% formalin maintained their transparency but those in Triton X and 0.9% saline became opaque. Subjective morphological assessment of transmission electron microscope images of corneas supported the SAXS data. Workers using SAXS analysis to characterize collagen should be alerted to changes that can be introduced by common preservatives in which their samples may have been stored.

Background: Collagen is a prominent structural protein in biological tissue, and little is known about the effect of preservatives, commonly used to preserve and study tissue, on collagen structures. Method: The study determined the effects of commonly used tissue preservatives on measurements of fibril diameter, fibril diameter distribution, and D-spacing of corneal collagen made using small angle X-ray scattering (SAXS) analysis. Results: Compared to control sheep and cats’ corneas that were preserved frozen at -80 °C, those preserved in 5% glutaraldehyde and 10% formalin had significantly larger mean collagen fibril diameters, increased fibril diameter distribution and decreased D-spacing. Corneas preserved in Triton X had significantly increased mean collagen fibril diameters and orientation indexes with decreased fibril diameter distribution. Corneas preserved in 0.9% saline had significantly increased mean collagen fibril diameters and decreased diameter distributions. Subjectively, the corneas preserved in 5% glutaraldehyde and 10% formalin maintained their transparency but those in Triton X and 0.9% saline became opaque. Subjective morphological assessment of transmission electron microscope images of corneas supported the SAXS data. Conclusions: Workers using SAXS analysis to characterize collagen should be alerted to changes that can be introduced by common preservatives in which their samples may have been stored.

Color plays an important role in human life: without it life would be dull and monochromatic. Printing color with distinct characteristics, like hue, brightness and saturation, and high resolution, are the main characteristic of image sensing devices. A flexible design of color filter is also desired for angle insensitivity and independence of direction of polarization of incident light. Furthermore, it is important that the designed filter be compatible with the image sensing devices in terms of technology and size. Therefore, color filter requires special care in its design, operation and integration. In this paper, we present a comprehensive review of nanostructured color filter designs described to date and evaluate them in terms of their performance.

NIH Public Access Policy requires that published journal articles resulting from NIH-funded research be made available to the public no later than 12 months after the date of publication. The public access mandate has been extended to NSF-funded research as well, and the government is moving toward making it a requirement for ALL federal funding. Non-compliance with this policy affects researchers because federal funding could be withheld. This presentation will introduce best practices for achieving compliance, and provide access to helpful resources, like the NIH Public Access Compliance video produced by UCI’s Office of Research.

Indoor positioning systems (IPS) have gained a lot of traction within the research community in recent years. Received Signal Strength Indicator (RSSI) of wireless networks are the most commonly used metric for indoor localization. The objective of this paper is to see how Wi-Fi interferers of different data rates affect the packet RSSI values of TX-RX links in a ZigBee based indoor localization system. The factors we examine also include the rate of corrupted packets and the overall packet loss. We also explore whether a Microwave Oven, a common source of interference for the ISM Band in a dwelling, perturb RSSI values in a localization system.

Consumer-grade RGB-D cameras capture RGB images along with per-pixel depth information, and because of their limited cost and ability to measure distances at a high frame rate, have been used in robotics and computer vision application. However, drawbacks include the repeatability and accuracy of RGB-D cameras for object detection and localization. This paper investigates and compares RGB-D cameras' performance in terms of depth image quality, depth clouds distribution, etc. performance and configuration methods of frequently used cameras, e.g. PrimeSense, Kinect V1 and Kinect V2, in order to provide useful advice when choosing a camera for robotic applications. Experimental and Point Cloud Library (PCL)-based methods are introduced for point-to-plane distance detection. Based on the obtained results, a relationship between measurements and ground truth is built.

Medical exoskeletons are robotic devices that provide paraplegics with the ability to ambulate again. There are four current market leaders in the industry: REX, by Rex Bionics; ReWalk, by Argo Medical Technologies Ltd; Ekso GT, by Ekso Bionics; and Indego, by Parker Hannifin. A weighted table-based method was used to evaluate the capability of these four devices, which was then compared to their maximum speed. The Ekso GT and the ReWalk devices achieved high speeds but had low capability scores due to their instability and minimal safety features. The REX and Indego devices achieved the highest capability scores but for contrasting reasons; the REX devices are inherently stable but have a slow, static gait, while the Indego device relies on walking aids for stability and achieves a faster speed. Both devices scored high in the safety criteria. It was derived from the results that there is an indirectly proportional relationship between speed and stability, and none of the exoskeletons achieve a balance between the two. This study found that there is an opportunity to enhance the speed, mobility, stability, and cost of medical exoskeletons, which is presented below.

In recent years, research into localization systems has become more popular as the proliferation of Wireless Sensor Networks (WSNs) grows. Wireless Localization can refer to either an “Active” system which tracks a mobile transceiver, or “Passive” localization which tracks a transceiver free entity by measuring the changes it makes to the surrounding wireless environment. Recent work has seen both of these systems implemented with Received Signal Strength Indication (RSSI) values from transceivers. Many algorithms and channel models have been presented to increase the accuracy of a Received Signal Strength (RSS) based system. In this paper we experimentally check whether RSSI values map to the expected RSS values within an IEEE 802.15.4 network. Indoor experiments are repeated within an ideal outdoor environment, with multiple device platforms, to eliminate indoor multipath propagation as the cause for inconsistent behavior of RSSI. We identify 3 key issues with raw RSSI values and present either a possible solution or a mitigation strategy to reduce their effect. We conclude that using raw RSSI values is flawed, as the premise that they uniquely map to the distance between transceivers is incorrect. However they may be calibrated to increase their accuracy, and therefore viability.

In typical chemistry experiments, there are many manual processes; chemistry automation is the process of automating these. In this paper, we describe work done to develop end-effectors that extend current capabilities of chemistry automation plants. The hierarchy established, the design process employed, and four end-effectors: the “Claw”, “Balloon”, “Cross”, and “Band” are presented, described, and discussed. The Claw, Balloon, and Band end-effectors were able to successfully pick-and-place bottles with diameters between 10 and 30 mm. Evaluating the designs, the Band end-effector was chosen as the working solution for use in future work.

There exists a range of feature detecting and feature matching algorithms; many of which have been included in the Open Computer Vision (OpenCV) library. However, given these different tools, which one should be used? This paper discusses the implementation and comparison of a range of the library's feature detectors and feature matchers. It shows that the Speeded-Up Robust Features (SURF) detector found the greatest number of features in an image, and that the Brute Force (BF) matcher matched the greatest number of detected features in an image pair. Given a benchmark image set, OpenCV's SURF detector found, on average, 1907.20 features in 1538.61 ms, and OpenCV's BF matcher, on average, matched features in 160.24 ms. The combination of the Binary Robust Invariant Scalable Key-points (BRISK) detector and BF matcher was found to be the highest ranked combination of OpenCV's feature detectors and feature matchers; on average, detecting and matching 1132.00 and 80.20 features, respectively, in 265.67 ms. It was concluded that if the number of features detected is important, the SURF detector should be used; else, if the number of features matched is important, the BF matcher should be used; otherwise, the combination of the OpenCV's BRISK feature detector and BF feature matcher should be used.

Modern Smart Home Automation (SMA) systems are predominantly based on wireless communication standards. New home automation setups can often include dozens of devices ranging from thermostats, humidity sensors, light switches, digital locks and cooling systems, all communicating on a common network. In this paper we focus on how SMA systems built on one of the most common standards (Zigbee), could be leveraged to provide a secondary benefit in the form of an Indoor Positioning System (IPS). IPS can be implemented in the form of Device Free Localization (DfL), Active tracking or as a combination of both techniques. A system containing a DfL implementation can detect and track moving entities by monitoring the changes in received signal strength (RSSI) values between nodes within a wireless network. DfL does not require the entity that is being tracked to carry an electronic device and actively contribute to the localization process. In Active tracking, the tracked entity contributes to the tracking process. In this paper both techniques are implemented individually, and a combination of both techniques is explored. Having implemented DfL and Active tracking, we were able to localize a person within a 3m × 3m quadrant with DfL with 80% accuracy. Active tracking resulted in a higher resolution of tracking compared to DfL, being able to localize a person within a 2m × 2m area with 95% accuracy. The accuracy of Active Tracking was then further increased to 98%, by coupling Active Tracking with DfL measurements.

This paper examines additive manufacturing technologies in the context of their potential use in flexible manufacturing systems. It reviews which current technologies are capable of producing full-strength production parts. It also examines which technologies might be applicable to FMS and how they might be implemented as part of a hybrid manufacturing cell.