Grand Challenges for Data Sensing and Analysis

A diverse group of experts proposed the 9 grand challenges outlined in this booklet. This expert task force was assembled by the ASCE TCCIT Data Sensing and Analysis (DSA) Committee and endorsed by the TRB AFH10(1) Construction IT joint subcommittee at the request of their membership. The task force did not rank the challenges selected, nor did it endorse particular approaches to meeting them. Rather than attempt to include every important goal for data sensing and analysis, the panel chose opportunities that were both achievable and sustainable to help people and the planet thrive. The panel’s conclusions were reviewed by several subject-matter experts. The DSA is offering an opportunity to comment on the challenges by contacting the task force chair via email at becerik@usc.edu.

Mode-localized displacement sensing

We report the construction of a new class of micromachined displacement sensors that employ the phenomenon of vibration-mode localization for monitoring minute inertial displacements. It is demonstrated both theoretically and experimentally that the eigenstate-shifted output signal of such mode-localized displacement sensors may be as high as 1000 times greater than corresponding resonant-frequency variations that serve as the output in the more traditional vibratory resonant micromechanical displacement/motion sensors. The high parametric sensitivities attainable in such mode-localized displacement sensors, together with their inherent advantages of improved environmental robustness and electrical tunability, suggest an alternative approach in achieving improved sensitivity and stability in high-resolution displacement transduction. © 1992-2012 IEEE.

A Novel Passive UHF RFID Real Time Location Sensing System

Ubiquitous in-building Real Time Location Systems (RTLS) today are limited by costly active radio frequency identification (RFID) tags and short range portal readers of low cost passive RFID tags. We, however, present a novel technology locates RFID tags using a new approach based on (a) minimising RFID fading using antenna diversity, frequency dithering, phase dithering and narrow beam-width antennas, (b) measuring a combination of RSSI and phase shift in the coherent received tag backscatter signals and (c) being selective of use of information from the system by, applying weighting techniques to minimise error. These techniques make it possible to locate tags to an accuracy of less than one metre. This breakthrough will enable, for the first time, the low-cost tagging of items and the possibility of locating them at relatively high precision.

SOI sensing technologies for harsh environment

This paper reviews and addresses certain aspects of Silicon-On-Insulator (SOI) technologies for a harsh environment. The paper first describes the need for specialized sensors in applications such as (i) domestic and other small-scale boilers, (ii) CO2 Capture and Sequestration, (iii) oil & gas storage and transportation, and (iv) automotive. We describe in brief the advantages and special features of SOI technology for sensing applications requiring temperatures in excess of the typical bulk silicon junction temperatures of 150oC. Finally we present the concepts, structures and prototypes of simple and smart micro-hotplate and Infra Red (IR) based emitters for NDIR (Non Dispersive IR) gas sensors in harsh environments. © 2012 IEEE.

Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach

Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. © 2012 IEEE.

Nanotubes complexed with DNA and proteins for resistive-pulse sensing

We use a resistive-pulse technique to analyze molecular hybrids of single-wall carbon nanotubes (SWNTs) wrapped in either single-stranded DNA or protein. Electric fields confined in a glass capillary nanopore allow us to probe the physical size and surface properties of molecular hybrids at the single-molecule level. We find that the translocation duration of a macromolecular hybrid is determined by its hydrodynamic size and solution mobility. The event current reveals the effects of ion exclusion by the rod-shaped hybrids and possible effects due to temporary polarization of the SWNT core. Our results pave the way to direct sensing of small DNA or protein molecules in a large unmodified solid-state nanopore by using nanofilaments as carriers. © 2013 American Chemical Society.

High-resolution strain sensing on steel by Silicon-On-Insulator flexural resonators fabricated with chip-level vacuum packaging

This paper reports on the fabrication and characterization of high-resolution strain sensors for steel based on Silicon On Insulator flexural resonators manufactured with chip-level LPCVD vacuum packaging. The sensors present high sensitivity (120 Hz/μ), very high resolution (4 n), low drift, and near-perfect reversibility in bending tests performed in both tensile and compressive strain regimes. © 2013 IEEE.

Direct detection of molecular biorecognition by dipole sensing mechanism.

This work investigates the feasibility of transducing molecular-recognition events into a measurable potentiometric signal. It is shown for the first time that biorecognition of acetylcholine (ACh) can be translated to conformational changes in the enzyme, acetylcholine-esterase (AChE), which in turn induces a measurable change in surface potential. Our results show that a highly sensitive detector for ACh can be obtained by the dilute assembly of AChE on a floating gate derived field effect transistor (FG-FET). A wide concentration range response is observed for ACh (10(-2)-10(-9)M) and for the inhibitor carbamylcholine CCh (10(-6)-10(-11)M). These enhanced sensitivities are modeled theoretically and explained by the combined response of the device to local pH changes and molecular dipole variations due to the enzyme-substrate recognition event.

Frequency locked micro disk resonator for improved sensing resolution and overcoming perturbations in NSOM measurements

We experimentally demonstrate locking of a laser frequency to a resonance line of a micro disk resonator. Achieving 1±0.1 pm shifting detection, the approach can be applied for sensing enhancement and perturbation immune NSOM measurements. © 2012 OSA.

Frequency locked micro disk resonator for improved sensing resolution and overcoming perturbations in NSOM measurements

We experimentally demonstrate locking of a laser frequency to a resonance line of a micro disk resonator. Achieving 1±0.1 pm shifting detection, the approach can be applied for sensing enhancement and perturbation immune NSOM measurements. © OSA 2012.