An Environmental Monitoring System for Managing Spatiotemporal Sensor Data over Sensor Networks

In a wireless sensor network, sensors collect data about natural phenomena and transmit them to a server in real-time. Many studies have been conducted focusing on the processing of continuous queries in an approximate form. However, this approach is difficult to apply to environmental applications which require the correct data to be stored. In this paper, we propose a weather monitoring system for handling and storing the sensor data stream in real-time in order to support continuous spatial and/or temporal queries. In our system, we exploit two time-based insertion methods to store the sensor data stream and reduce the number of managed tuples, without losing any of the raw data which are useful for queries, by using the sensors' temporal attributes. In addition, we offer a method for reducing the cost of the join operations used in processing spatiotemporal queries by filtering out a list of irrelevant sensors from query range before making a join operation. In the results of the performance evaluation, the number of tuples obtained from the data stream is reduced by about 30% in comparison to a naïve approach, thereby decreasing the query execution time

The STAR MAPS-based PiXeL detector

The PiXeL detector (PXL) for the Heavy Flavor Tracker (HFT) of the STAR experiment at RHIC is the first application of the state-of-the-art thin Monolithic Active Pixel Sensors (MAPS) technology in a collider environment. Custom built pixel sensors, their readout electronics and the detector mechanical structure are described in detail. Selected detector design aspects and production steps are presented. The detector operations during the three years of data taking (2014-2016) and the overall performance exceeding the design specifications are discussed in the conclusive sections of this paper

Accuracy of a CGM Sensor in Pediatric Subjects With Type 1 Diabetes. Comparison of Three Insertion Sites: Arm, Abdomen, and Gluteus

Patients with diabetes, especially pediatric ones, sometimes use continuous glucose monitoring (CGM) sensor in different positions from the approved ones. Here we compare the accuracy of Dexcom\uae G5 CGM sensor in three different sites: abdomen, gluteus (both approved) and arm (off-label)

Investigation of Polymer–Plasticizer Blends as SH-SAW Sensor Coatings for Detection of Benzene in Water with High Sensitivity and Long-Term Stability

We report the first-ever direct detection of benzene in water at concentrations below 100 ppb (parts per billion) using acoustic wave (specifically, shear-horizontal surface acoustic wave, SH-SAW) sensors with plasticized polymer coatings. Two polymers and two plasticizers were studied as materials for sensor coatings. For each polymer–plasticizer combination, the influence of the mixing ratio of the blend on the sensitivity to benzene was measured and compared to commercially available polymers that were used for BTEX (benzene, toluene, ethylbenzene, and xylene) detection in previous work. After optimizing the coating parameters, the highest sensitivity and lowest detection limit for benzene were found for a 1.25 μm thick sensor coating of 17.5%-by-weight diisooctyl azelate-polystyrene on the tested acoustic wave device. The calculated detection limit was 45 ppb, with actual sensor responses to concentrations down to 65 ppb measured directly. Among the sensor coatings that showed good sensitivity to benzene, the best long-term stability was found for a 1.0 μm thick coating of 23% diisononyl cyclohexane-1,2-dicarboxylate-polystyrene, which was studied here because it is known to show no detectable leaching in water. The present work demonstrates that, by varying type of plasticizer, mixing ratio, and coating thickness, the mechanical and chemical properties of the coatings can be conveniently tailored to maximize analyte sorption and partial chemical selectivity for a given class of analytes as well as to minimize acoustic-wave attenuation in contact with an aqueous phase at the operating frequency of the sensor device

Combined surface acoustic wave and surface plasmon resonance measurement of collagen and fibrinogen layers

We use an instrument combining optical (surface plasmon resonance) and acoustic (Love mode acoustic wave device) real-time measurements on a same surface for the identification of water content in collagen and fibrinogen protein layers. After calibration of the surface acoustic wave device sensitivity by copper electrodeposition, the bound mass and its physical properties -- density and optical index -- are extracted from the complementary measurement techniques and lead to thickness and water ratio values compatible with the observed signal shifts. Such results are especially usefully for protein layers with a high water content as shown here for collagen on an hydrophobic surface. We obtain the following results: collagen layers include 70+/-20 % water and are 16+/-3 to 19+/-3 nm thick for bulk concentrations ranging from 30 to 300 ug/ml. Fibrinogen layers include 50+/-10 % water for layer thicknesses in the 6+/-1.5 to 13+/-2 nm range when the bulk concentration is in the 46 to 460 ug/ml range.Comment: 50 pages, 8 figures, 1 tabl

Needle Tip Force Estimation using an OCT Fiber and a Fused convGRU-CNN Architecture

Needle insertion is common during minimally invasive interventions such as biopsy or brachytherapy. During soft tissue needle insertion, forces acting at the needle tip cause tissue deformation and needle deflection. Accurate needle tip force measurement provides information on needle-tissue interaction and helps detecting and compensating potential misplacement. For this purpose we introduce an image-based needle tip force estimation method using an optical fiber imaging the deformation of an epoxy layer below the needle tip over time. For calibration and force estimation, we introduce a novel deep learning-based fused convolutional GRU-CNN model which effectively exploits the spatio-temporal data structure. The needle is easy to manufacture and our model achieves a mean absolute error of 1.76 +- 1.5 mN with a cross-correlation coefficient of 0.9996, clearly outperforming other methods. We test needles with different materials to demonstrate that the approach can be adapted for different sensitivities and force ranges. Furthermore, we validate our approach in an ex-vivo prostate needle insertion scenario.Comment: Accepted for Publication at MICCAI 201

Development of a combined surface plasmon resonance/surface acoustic wave device for the characterization of biomolecules

It is known that acoustic sensor devices, if operated in liquid phase, are sensitive not just to the mass of the analyte but also to various other parameters, such as size, shape, charge and elastic constants of the analyte as well as bound and viscously entrained water. This can be used to extract valuable information about a biomolecule, particularly if the acoustic device is combined with another sensor element which is sensitive to the mass or amount of analyte only. The latter is true in good approximation for various optical sensor techniques. This work reports on the development of a combined surface plasmon resonance/surface acoustic wave sensor system which is designed for the investigation of biomolecules such as proteins or DNA. Results for the deposition of neutravidin and DNA are reported