Sensing of molecules using quantum dynamics

PubMed Central

Migliore, Agostino; Naaman, Ron; Beratan, David N.

2015-01-01

We design sensors where information is transferred between the sensing event and the actuator via quantum relaxation processes, through distances of a few nanometers. We thus explore the possibility of sensing using intrinsically quantum mechanical phenomena that are also at play in photobiology, bioenergetics, and information processing. Specifically, we analyze schemes for sensing based on charge transfer and polarization (electronic relaxation) processes. These devices can have surprising properties. Their sensitivity can increase with increasing separation between the sites of sensing (the receptor) and the actuator (often a solid-state substrate). This counterintuitive response and other quantum features give these devices favorable characteristics, such as enhanced sensitivity and selectivity. Using coherent phenomena at the core of molecular sensing presents technical challenges but also suggests appealing schemes for molecular sensing and information transfer in supramolecular structures. PMID:25911636

Consensus-Based Cooperative Spectrum Sensing with Improved Robustness Against SSDF Attacks

NASA Astrophysics Data System (ADS)

Liu, Quan; Gao, Jun; Guo, Yunwei; Liu, Siyang

2011-05-01

Based on the consensus algorithm, an attack-proof cooperative spectrum sensing (CSS) scheme is presented for decentralized cognitive radio networks (CRNs), where a common fusion center is not available and some malicious users may launch attacks with spectrum sensing data falsification (SSDF). Local energy detection is firstly performed by each secondary user (SU), and then, utilizing the consensus notions, each SU can make its own decision individually only by local information exchange with its neighbors rather than any centralized fusion used in most existing schemes. With the help of some anti-attack tricks, each authentic SU can generally identify and exclude those malicious reports during the interactions within the neighborhood. Compared with the existing solutions, the proposed scheme is proved to have much better robustness against three categories of SSDF attack, without requiring any a priori knowledge of the whole network.

Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.

PubMed

Cowlagi, Raghvendra V; Tsiotras, Panagiotis

2012-10-01

We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.

Upper Kalamazoo watershed land cover inventory. [based on remote sensing

NASA Technical Reports Server (NTRS)

Richason, B., III; Enslin, W.

1973-01-01

Approximately 1000 square miles of the eastern portion of the watershed were inventoried based on remote sensing imagery. The classification scheme, imagery and interpretation procedures, and a cost analysis are discussed. The distributions of land cover within the area are tabulated.

Secure Nearest Neighbor Query on Crowd-Sensing Data

PubMed Central

Cheng, Ke; Wang, Liangmin; Zhong, Hong

2016-01-01

Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU) situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes. PMID:27669253

Secure Nearest Neighbor Query on Crowd-Sensing Data.

PubMed

Cheng, Ke; Wang, Liangmin; Zhong, Hong

2016-09-22

Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU) situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.

Sensing of molecules using quantum dynamics

DOE PAGES

Migliore, Agostino; Naaman, Ron; Beratan, David N.

2015-04-24

In this study, we design sensors where information is transferred between the sensing event and the actuator via quantum relaxation processes, through distances of a few nanometers. We thus explore the possibility of sensing using intrinsically quantum mechanical phenomena that are also at play in photobiology, bioenergetics, and information processing. Specifically, we analyze schemes for sensing based on charge transfer and polarization (electronic relaxation) processes. These devices can have surprising properties. Their sensitivity can increase with increasing separation between the sites of sensing (the receptor) and the actuator (often a solid-state substrate). This counterintuitive response and other quantum features givemore » these devices favorable characteristics, such as enhanced sensitivity and selectivity. Finally, using coherent phenomena at the core of molecular sensing presents technical challenges but also suggests appealing schemes for molecular sensing and information transfer in supramolecular structures.« less

Unobtrusive monitoring of heart rate using a cost-effective speckle-based SI-POF remote sensor

NASA Astrophysics Data System (ADS)

Pinzón, P. J.; Montero, D. S.; Tapetado, A.; Vázquez, C.

2017-03-01

A novel speckle-based sensing technique for cost-effective heart-rate monitoring is demonstrated. This technique detects periodical changes in the spatial distribution of energy on the speckle pattern at the output of a Step-Index Polymer Optical Fiber (SI-POF) lead by using a low-cost webcam. The scheme operates in reflective configuration thus performing a centralized interrogation unit scheme. The prototype has been integrated into a mattress and its functionality has been tested with 5 different patients lying on the mattress in different positions without direct contact with the fiber sensing lead.

Modulation aware cluster size optimisation in wireless sensor networks

NASA Astrophysics Data System (ADS)

Sriram Naik, M.; Kumar, Vinay

2017-07-01

Wireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

Strain sensing technology for high temperature applications

NASA Technical Reports Server (NTRS)

Williams, W. Dan

1993-01-01

This review discusses the status of strain sensing technology for high temperature applications. Technologies covered are those supported by NASA such as required for applications in hypersonic vehicles and engines, advanced subsonic engines, as well as material and structure development. The applications may be at temperatures of 540 C (1000 F) to temperatures in excess of 1400 C (2500 F). The most promising technologies at present are the resistance strain gage and remote sensing schemes. Resistance strain gages discussed include the BCL gage, the LaRC compensated gage, and the PdCr gage. Remote sensing schemes such as laser based speckle strain measurement, phase-shifling interferometry, and x-ray extensometry are discussed. Present status and limitations of these technologies are presented.

A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. A thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temp...

Photonic sensing based on variation of propagation properties of photonic crystal fibres

NASA Astrophysics Data System (ADS)

Rothwell, John H.; Flavin, Dónal A.; MacPherson, William N.; Jones, Julian D.; Knight, Jonathan C.; Russell, Philip St. J.

2006-12-01

We report on a low-coherence interferometric scheme for the measurement of the strain and temperature dependences of group delay and dispersion in short, index-guiding, 'endlessly-single-mode' photonic crystal fibre elements in the 840 nm and 1550 nm regions. Based on the measurements, we propose two schemes for simultaneous strain and temperature measurement using a single unmodified PCF element, without a requirement for any compensating components, and we project the measurement accuracies of these schemes.

A fuzzy structural matching scheme for space robotics vision

NASA Technical Reports Server (NTRS)

Naka, Masao; Yamamoto, Hiromichi; Homma, Khozo; Iwata, Yoshitaka

1994-01-01

In this paper, we propose a new fuzzy structural matching scheme for space stereo vision which is based on the fuzzy properties of regions of images and effectively reduces the computational burden in the following low level matching process. Three dimensional distance images of a space truss structural model are estimated using this scheme from stereo images sensed by Charge Coupled Device (CCD) TV cameras.

Chem/bio sensing with non-classical light and integrated photonics.

PubMed

Haas, J; Schwartz, M; Rengstl, U; Jetter, M; Michler, P; Mizaikoff, B

2018-01-29

Modern quantum technology currently experiences extensive advances in applicability in communications, cryptography, computing, metrology and lithography. Harnessing this technology platform for chem/bio sensing scenarios is an appealing opportunity enabling ultra-sensitive detection schemes. This is further facilliated by the progress in fabrication, miniaturization and integration of visible and infrared quantum photonics. Especially, the combination of efficient single-photon sources together with waveguiding/sensing structures, serving as active optical transducer, as well as advanced detector materials is promising integrated quantum photonic chem/bio sensors. Besides the intrinsic molecular selectivity and non-destructive character of visible and infrared light based sensing schemes, chem/bio sensors taking advantage of non-classical light sources promise sensitivities beyond the standard quantum limit. In the present review, recent achievements towards on-chip chem/bio quantum photonic sensing platforms based on N00N states are discussed along with appropriate recognition chemistries, facilitating the detection of relevant (bio)analytes at ultra-trace concentration levels. After evaluating recent developments in this field, a perspective for a potentially promising sensor testbed is discussed for reaching integrated quantum sensing with two fiber-coupled GaAs chips together with semiconductor quantum dots serving as single-photon sources.

A novel secret sharing with two users based on joint transform correlator and compressive sensing

NASA Astrophysics Data System (ADS)

Zhao, Tieyu; Chi, Yingying

2018-05-01

Recently, joint transform correlator (JTC) has been widely applied to image encryption and authentication. This paper presents a novel secret sharing scheme with two users based on JTC. Two users must be present during the decryption that the system has high security and reliability. In the scheme, two users use their fingerprints to encrypt plaintext, and they can decrypt only if both of them provide the fingerprints which are successfully authenticated. The linear relationship between the plaintext and ciphertext is broken using the compressive sensing, which can resist existing attacks on JTC. The results of the theoretical analysis and numerical simulation confirm the validity of the system.

VLSI Technology for Cognitive Radio

NASA Astrophysics Data System (ADS)

VIJAYALAKSHMI, B.; SIDDAIAH, P.

2017-08-01

One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

Development and application of a new comprehensive image-based classification scheme for coastal and benthic environments along the southeast Florida continental shelf

NASA Astrophysics Data System (ADS)

Makowski, Christopher

The coastal (terrestrial) and benthic environments along the southeast Florida continental shelf show a unique biophysical succession of marine features from a highly urbanized, developed coastal region in the north (i.e. northern Miami-Dade County) to a protective marine sanctuary in the southeast (i.e. Florida Keys National Marine Sanctuary). However, the establishment of a standard bio-geomorphological classification scheme for this area of coastal and benthic environments is lacking. The purpose of this study was to test the hypothesis and answer the research question of whether new parameters of integrating geomorphological components with dominant biological covers could be developed and applied across multiple remote sensing platforms for an innovative way to identify, interpret, and classify diverse coastal and benthic environments along the southeast Florida continental shelf. An ordered manageable hierarchical classification scheme was developed to incorporate the categories of Physiographic Realm, Morphodynamic Zone, Geoform, Landform, Dominant Surface Sediment, and Dominant Biological Cover. Six different remote sensing platforms (i.e. five multi-spectral satellite image sensors and one high-resolution aerial orthoimagery) were acquired, delineated according to the new classification scheme, and compared to determine optimal formats for classifying the study area. Cognitive digital classification at a nominal scale of 1:6000 proved to be more accurate than autoclassification programs and therefore used to differentiate coastal marine environments based on spectral reflectance characteristics, such as color, tone, saturation, pattern, and texture of the seafloor topology. In addition, attribute tables were created in conjugation with interpretations to quantify and compare the spatial relationships between classificatory units. IKONOS-2 satellite imagery was determined to be the optimal platform for applying the hierarchical classification scheme. However, each remote sensing platform had beneficial properties depending on research goals, logistical restrictions, and financial support. This study concluded that a new hierarchical comprehensive classification scheme for identifying coastal marine environments along the southeast Florida continental shelf could be achieved by integrating geomorphological features with biological coverages. This newly developed scheme, which can be applied across multiple remote sensing platforms with GIS software, establishes an innovative classification protocol to be used in future research studies.

Rate and power efficient image compressed sensing and transmission

NASA Astrophysics Data System (ADS)

Olanigan, Saheed; Cao, Lei; Viswanathan, Ramanarayanan

2016-01-01

This paper presents a suboptimal quantization and transmission scheme for multiscale block-based compressed sensing images over wireless channels. The proposed method includes two stages: dealing with quantization distortion and transmission errors. First, given the total transmission bit rate, the optimal number of quantization bits is assigned to the sensed measurements in different wavelet sub-bands so that the total quantization distortion is minimized. Second, given the total transmission power, the energy is allocated to different quantization bit layers based on their different error sensitivities. The method of Lagrange multipliers with Karush-Kuhn-Tucker conditions is used to solve both optimization problems, for which the first problem can be solved with relaxation and the second problem can be solved completely. The effectiveness of the scheme is illustrated through simulation results, which have shown up to 10 dB improvement over the method without the rate and power optimization in medium and low signal-to-noise ratio cases.

Schemes of detecting nuclear spin correlations by dynamical decoupling based quantum sensing

NASA Astrophysics Data System (ADS)

Ma, Wen-Long Ma; Liu, Ren-Bao

Single-molecule sensitivity of nuclear magnetic resonance (NMR) and angstrom resolution of magnetic resonance imaging (MRI) are the highest challenges in magnetic microscopy. Recent development in dynamical decoupling (DD) enhanced diamond quantum sensing has enabled NMR of single nuclear spins and nanoscale NMR. Similar to conventional NMR and MRI, current DD-based quantum sensing utilizes the frequency fingerprints of target nuclear spins. Such schemes, however, cannot resolve different nuclear spins that have the same noise frequency or differentiate different types of correlations in nuclear spin clusters. Here we show that the first limitation can be overcome by using wavefunction fingerprints of target nuclear spins, which is much more sensitive than the ''frequency fingerprints'' to weak hyperfine interaction between the targets and a sensor, while the second one can be overcome by a new design of two-dimensional DD sequences composed of two sets of periodic DD sequences with different periods, which can be independently set to match two different transition frequencies. Our schemes not only offer an approach to breaking the resolution limit set by ''frequency gradients'' in conventional MRI, but also provide a standard approach to correlation spectroscopy for single-molecule NMR.

CMOS image sensor-based implantable glucose sensor using glucose-responsive fluorescent hydrogel.

PubMed

Tokuda, Takashi; Takahashi, Masayuki; Uejima, Kazuhiro; Masuda, Keita; Kawamura, Toshikazu; Ohta, Yasumi; Motoyama, Mayumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Okitsu, Teru; Takeuchi, Shoji; Ohta, Jun

2014-11-01

A CMOS image sensor-based implantable glucose sensor based on an optical-sensing scheme is proposed and experimentally verified. A glucose-responsive fluorescent hydrogel is used as the mediator in the measurement scheme. The wired implantable glucose sensor was realized by integrating a CMOS image sensor, hydrogel, UV light emitting diodes, and an optical filter on a flexible polyimide substrate. Feasibility of the glucose sensor was verified by both in vitro and in vivo experiments.

Interference Information Based Power Control for Cognitive Radio with Multi-Hop Cooperative Sensing

NASA Astrophysics Data System (ADS)

Yu, Youngjin; Murata, Hidekazu; Yamamoto, Koji; Yoshida, Susumu

Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

Quantum-Secret-Sharing Scheme Based on Local Distinguishability of Orthogonal Seven-Qudit Entangled States

NASA Astrophysics Data System (ADS)

Liu, Cheng-Ji; Li, Zhi-Hui; Bai, Chen-Ming; Si, Meng-Meng

2018-02-01

The concept of judgment space was proposed by Wang et al. (Phys. Rev. A 95, 022320, 2017), which was used to study some important properties of quantum entangled states based on local distinguishability. In this study, we construct 15 kinds of seven-qudit quantum entangled states in the sense of permutation, calculate their judgment space and propose a distinguishability rule to make the judgment space more clearly. Based on this rule, we study the local distinguishability of the 15 kinds of seven-qudit quantum entangled states and then propose a ( k, n) threshold quantum secret sharing scheme. Finally, we analyze the security of the scheme.

A Qualitative Organic Analysis that Exploits the Senses of Smell, Touch, and Sound

ERIC Educational Resources Information Center

Bromfield-Lee, Deborah C.; Oliver-Hoyo, Maria T.

2007-01-01

This laboratory experiment utilizes the characteristic aromas of some functional groups to exploit the sense of smell as a discriminating tool in an organic qualitative analysis scheme. Students differentiate a variety of compounds by their aromas and based on their olfactory classification identify an unknown functional group. Students then…

CMOS image sensor-based implantable glucose sensor using glucose-responsive fluorescent hydrogel

PubMed Central

Tokuda, Takashi; Takahashi, Masayuki; Uejima, Kazuhiro; Masuda, Keita; Kawamura, Toshikazu; Ohta, Yasumi; Motoyama, Mayumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Okitsu, Teru; Takeuchi, Shoji; Ohta, Jun

2014-01-01

A CMOS image sensor-based implantable glucose sensor based on an optical-sensing scheme is proposed and experimentally verified. A glucose-responsive fluorescent hydrogel is used as the mediator in the measurement scheme. The wired implantable glucose sensor was realized by integrating a CMOS image sensor, hydrogel, UV light emitting diodes, and an optical filter on a flexible polyimide substrate. Feasibility of the glucose sensor was verified by both in vitro and in vivo experiments. PMID:25426316

Fiber optic extrinsic Fabry-Perot accelerometer using laser emission frequency modulated phase generated carrier demodulation scheme

NASA Astrophysics Data System (ADS)

Wang, Dai-Hua; Jia, Ping-Gang

2013-05-01

The principle of a fiber optic Fabry-Perot (F-P) accelerometer (FOFPA) system using the laser emission frequency modulated phase generated carrier (FMPGC) demodulation scheme is first described and experimentally demonstrated. The F-P cavity, which is constituted by placing the end face of a gradient-index lens in parallel with the reflector on the inertial mass, directly translates the inertial mass's displacement generated by the measured acceleration into phase shifts of the interference output from the F-P cavity. An FMPGC demodulation scheme based on the arctangent (Arctan) algorithm is adapted to demodulate the phase shifts. The sensing model for the FOFPA system using the FMPGC-Arctan demodulation scheme is established and the sensing characteristics are theoretically analyzed. On these bases, the FOFPA is designed and fabricated and a prototyping system is built and tested. The results indicate that: (1) the nonlinearity of the FOFPA system using the FMPGC-Arctan demodulation scheme is less than 0.58%, (2) the resonant frequency, on-axial sensitivity, and resolution are 393 Hz, 13.11 rad/g, and 450 μ, respectively, and (3) the maximum deviation of the phase sensitivity of the FOFPA within the temperature range of 30 to 80°C is 0.49 dB re 1 rad/g.

A flexible, highly sensitive catheter for high resolution manometry based on in-fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Bueley, Christopher; Wild, Peter M.

2013-09-01

This work presents a fibre optic-based flexible catheter for high resolution manometry (HRM), with sensing pods located at a pitch of 10 mm and an overall diameter of 2.8 mm. In-fibre Bragg gratings act as the sensing elements within these sensing pods. Hydrodynamic pressure resolution of 0.2 mmHg is demonstrated in conjunction with insensitivity to occlusion pressure. This result is significant in the context of HRM where independent measurement of hydrodynamic pressure is clinically relevant. The sensing system is compact, robust and flexible. Crosstalk between individual sensors is characterized and a compensation scheme is developed and validated.

Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

NASA Technical Reports Server (NTRS)

Steffen, K.; Schweiger, A.; Maslanik, J.; Key, J.; Weaver, R.; Barry, R.

1990-01-01

The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.

Total Variation Diminishing (TVD) schemes of uniform accuracy

NASA Technical Reports Server (NTRS)

Hartwich, PETER-M.; Hsu, Chung-Hao; Liu, C. H.

1988-01-01

Explicit second-order accurate finite-difference schemes for the approximation of hyperbolic conservation laws are presented. These schemes are nonlinear even for the constant coefficient case. They are based on first-order upwind schemes. Their accuracy is enhanced by locally replacing the first-order one-sided differences with either second-order one-sided differences or central differences or a blend thereof. The appropriate local difference stencils are selected such that they give TVD schemes of uniform second-order accuracy in the scalar, or linear systems, case. Like conventional TVD schemes, the new schemes avoid a Gibbs phenomenon at discontinuities of the solution, but they do not switch back to first-order accuracy, in the sense of truncation error, at extrema of the solution. The performance of the new schemes is demonstrated in several numerical tests.

Active Thermal Extraction and Temperature Sensing of Near-field Thermal Radiation

DOE PAGES

Ding, D.; Kim, T.; Minnich, A. J.

2016-09-06

Recently, we proposed an active thermal extraction (ATX) scheme that enables thermally populated surface phonon polaritons to escape into the far-field. The concept is based on a fluorescence upconversion process that also occurs in laser cooling of solids (LCS). Here, we present a generalized analysis of our scheme using the theoretical framework for LCS. We show that both LCS and ATX can be described with the same mathematical formalism by replacing the electron-phonon coupling parameter in LCS with the electron-photon coupling parameter in ATX. Using this framework, we compare the ideal efficiency and power extracted for the two schemes andmore » examine the parasitic loss mechanisms. As a result, this work advances the application of ATX to manipulate near-field thermal radiation for applications such as temperature sensing and active radiative cooling.« less

Blind compressive sensing dynamic MRI

PubMed Central

Lingala, Sajan Goud; Jacob, Mathews

2013-01-01

We propose a novel blind compressive sensing (BCS) frame work to recover dynamic magnetic resonance images from undersampled measurements. This scheme models the dynamic signal as a sparse linear combination of temporal basis functions, chosen from a large dictionary. In contrast to classical compressed sensing, the BCS scheme simultaneously estimates the dictionary and the sparse coefficients from the undersampled measurements. Apart from the sparsity of the coefficients, the key difference of the BCS scheme with current low rank methods is the non-orthogonal nature of the dictionary basis functions. Since the number of degrees of freedom of the BCS model is smaller than that of the low-rank methods, it provides improved reconstructions at high acceleration rates. We formulate the reconstruction as a constrained optimization problem; the objective function is the linear combination of a data consistency term and sparsity promoting ℓ1 prior of the coefficients. The Frobenius norm dictionary constraint is used to avoid scale ambiguity. We introduce a simple and efficient majorize-minimize algorithm, which decouples the original criterion into three simpler sub problems. An alternating minimization strategy is used, where we cycle through the minimization of three simpler problems. This algorithm is seen to be considerably faster than approaches that alternates between sparse coding and dictionary estimation, as well as the extension of K-SVD dictionary learning scheme. The use of the ℓ1 penalty and Frobenius norm dictionary constraint enables the attenuation of insignificant basis functions compared to the ℓ0 norm and column norm constraint assumed in most dictionary learning algorithms; this is especially important since the number of basis functions that can be reliably estimated is restricted by the available measurements. We also observe that the proposed scheme is more robust to local minima compared to K-SVD method, which relies on greedy sparse coding. Our phase transition experiments demonstrate that the BCS scheme provides much better recovery rates than classical Fourier-based CS schemes, while being only marginally worse than the dictionary aware setting. Since the overhead in additionally estimating the dictionary is low, this method can be very useful in dynamic MRI applications, where the signal is not sparse in known dictionaries. We demonstrate the utility of the BCS scheme in accelerating contrast enhanced dynamic data. We observe superior reconstruction performance with the BCS scheme in comparison to existing low rank and compressed sensing schemes. PMID:23542951

Dynamic magnetic resonance imaging method based on golden-ratio cartesian sampling and compressed sensing.

PubMed

Li, Shuo; Zhu, Yanchun; Xie, Yaoqin; Gao, Song

2018-01-01

Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.

Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forrest, Stephanie; He, Wenbo; Groat, Michael

2013-01-01

Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.

A robust cooperative spectrum sensing scheme based on Dempster-Shafer theory and trustworthiness degree calculation in cognitive radio networks

NASA Astrophysics Data System (ADS)

Wang, Jinlong; Feng, Shuo; Wu, Qihui; Zheng, Xueqiang; Xu, Yuhua; Ding, Guoru

2014-12-01

Cognitive radio (CR) is a promising technology that brings about remarkable improvement in spectrum utilization. To tackle the hidden terminal problem, cooperative spectrum sensing (CSS) which benefits from the spatial diversity has been studied extensively. Since CSS is vulnerable to the attacks initiated by malicious secondary users (SUs), several secure CSS schemes based on Dempster-Shafer theory have been proposed. However, the existing works only utilize the current difference of SUs, such as the difference in SNR or similarity degree, to evaluate the trustworthiness of each SU. As the current difference is only one-sided and sometimes inaccurate, the statistical information contained in each SU's historical behavior should not be overlooked. In this article, we propose a robust CSS scheme based on Dempster-Shafer theory and trustworthiness degree calculation. It is carried out in four successive steps, which are basic probability assignment (BPA), trustworthiness degree calculation, selection and adjustment of BPA, and combination by Dempster-Shafer rule, respectively. Our proposed scheme evaluates the trustworthiness degree of SUs from both current difference aspect and historical behavior aspect and exploits Dempster-Shafer theory's potential to establish a `soft update' approach for the reputation value maintenance. It can not only differentiate malicious SUs from honest ones based on their historical behaviors but also reserve the current difference for each SU to achieve a better real-time performance. Abundant simulation results have validated that the proposed scheme outperforms the existing ones under the impact of different attack patterns and different number of malicious SUs.

A beacon interval shifting scheme for interference mitigation in body area networks.

PubMed

Kim, Seungku; Kim, Seokhwan; Kim, Jin-Woo; Eom, Doo-Seop

2012-01-01

This paper investigates the issue of interference avoidance in body area networks (BANs). IEEE 802.15 Task Group 6 presented several schemes to reduce such interference, but these schemes are still not proper solutions for BANs. We present a novel distributed TDMA-based beacon interval shifting scheme that reduces interference in the BANs. A design goal of the scheme is to avoid the wakeup period of each BAN coinciding with other networks by employing carrier sensing before a beacon transmission. We analyze the beacon interval shifting scheme and investigate the proper back-off length when the channel is busy. We compare the performance of the proposed scheme with the schemes presented in IEEE 802.15 Task Group 6 using an OMNeT++ simulation. The simulation results show that the proposed scheme has a lower packet loss, energy consumption, and delivery-latency than the schemes of IEEE 802.15 Task Group 6.

A Beacon Interval Shifting Scheme for Interference Mitigation in Body Area Networks

PubMed Central

Kim, Seungku; Kim, Seokhwan; Kim, Jin-Woo; Eom, Doo-Seop

2012-01-01

This paper investigates the issue of interference avoidance in body area networks (BANs). IEEE 802.15 Task Group 6 presented several schemes to reduce such interference, but these schemes are still not proper solutions for BANs. We present a novel distributed TDMA-based beacon interval shifting scheme that reduces interference in the BANs. A design goal of the scheme is to avoid the wakeup period of each BAN coinciding with other networks by employing carrier sensing before a beacon transmission. We analyze the beacon interval shifting scheme and investigate the proper back-off length when the channel is busy. We compare the performance of the proposed scheme with the schemes presented in IEEE 802.15 Task Group 6 using an OMNeT++ simulation. The simulation results show that the proposed scheme has a lower packet loss, energy consumption, and delivery-latency than the schemes of IEEE 802.15 Task Group 6. PMID:23112639

FORUM: A Suggestion for an Improved Vegetation Scheme for Local and Global Mapping and Monitoring.

PubMed

ADAMS

1999-01-01

/ Understanding of global ecological problems is at least partly dependent on clear assessments of vegetation change, and such assessment is always dependent on the use of a vegetation classification scheme. Use of satellite remotely sensed data is the only practical means of carrying out any global-scale vegetation mapping exercise, but if the resulting maps are to be useful to most ecologists and conservationists, they must be closely tied to clearly defined features of vegetation on the ground. Furthermore, much of the mapping that does take place involves more local-scale description of field sites; for purposes of cost and practicality, such studies usually do not involve remote sensing using satellites. There is a need for a single scheme that integrates the smallest to the largest scale in a way that is meaningful to most environmental scientists. Existing schemes are unsatisfactory for this task; they are ambiguous, unnecessarily complex, and their categories do not correspond to common-sense definitions. In response to these problems, a simple structural-physiognomically based scheme with 23 fundamental categories is proposed here for mapping and monitoring on any scale, from local to global. The fundamental categories each subdivide into more specific structural categories for more detailed mapping, but all the categories can be used throughout the world and at any scale, allowing intercomparison between regions. The next stage in the process will be to obtain the views of as many people working in as many different fields as possible, to see whether the proposed scheme suits their needs and how it should be modified. With a few modifications, such a scheme could easily be appended to an existing land cover classification scheme, such as the FAO system, greatly increasing the usefulness and accessability of the results of the landcover classification. KEY WORDS: Vegetation scheme; Mapping; Monitoring; Land cover

Capillary waveguide optrodes: an approach to optical sensing in medical diagnostics

NASA Astrophysics Data System (ADS)

Lippitsch, Max E.; Draxler, Sonja; Kieslinger, Dietmar; Lehmann, Hartmut; Weigl, Bernhard H.

1996-07-01

Glass capillaries with a chemically sensitive coating on the inner surface are used as optical sensors for medical diagnostics. A capillary simultaneously serves as a sample compartment, a sensor element, and an inhomogeneous optical waveguide. Various detection schemes based on absorption, fluorescence intensity, or fluorescence lifetime are described. In absorption-based capillary waveguide optrodes the absorption in the sensor layer is analyte dependent; hence light transmission along the inhomogeneous waveguiding structure formed by the capillary wall and the sensing layer is a function of the analyte concentration. Similarly, in fluorescence-based capillary optrodes the fluorescence intensity or the fluorescence lifetime of an indicator dye fixed in the sensing layer is analyte dependent; thus the specific property of fluorescent light excited in the sensing layer and thereafter guided along the inhomogeneous waveguiding structure is a function of the analyte concentration. Both schemes are experimentally demonstrated, one with carbon dioxide as the analyte and the other one with oxygen. The device combines optical sensors with the standard glass capillaries usually applied to gather blood drops from fingertips, to yield a versatile diagnostic instrument, integrating the sample compartment, the optical sensor, and the light-collecting optics into a single piece. This ensures enhanced sensor performance as well as improved handling compared with other sensors. waveguide, blood gases, medical diagnostics.

Image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Pan, Shumin; Cheng, Shan; Zhou, Zhihong

2016-08-01

Most image encryption algorithms based on low-dimensional chaos systems bear security risks and suffer encryption data expansion when adopting nonlinear transformation directly. To overcome these weaknesses and reduce the possible transmission burden, an efficient image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing is proposed. The original image is measured by the measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the cycle shift operation controlled by a hyper-chaotic system. Cycle shift operation can change the values of the pixels efficiently. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys distribution simultaneously as a nonlinear encryption system. Simulation results verify the validity and the reliability of the proposed algorithm with acceptable compression and security performance.

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005

Subranging scheme for SQUID sensors

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor)

2008-01-01

A readout scheme for measuring the output from a SQUID-based sensor-array using an improved subranging architecture that includes multiple resolution channels (such as a coarse resolution channel and a fine resolution channel). The scheme employs a flux sensing circuit with a sensing coil connected in series to multiple input coils, each input coil being coupled to a corresponding SQUID detection circuit having a high-resolution SQUID device with independent linearizing feedback. A two-resolution configuration (course and fine) is illustrated with a primary SQUID detection circuit for generating a fine readout, and a secondary SQUID detection circuit for generating a course readout, both having feedback current coupled to the respective SQUID devices via feedback/modulation coils. The primary and secondary SQUID detection circuits function and derive independent feedback. Thus, the SQUID devices may be monitored independently of each other (and read simultaneously) to dramatically increase slew rates and dynamic range.

A Charge-Based Low-Power High-SNR Capacitive Sensing Interface Circuit

PubMed Central

Peng, Sheng-Yu; Qureshi, Muhammad S.; Hasler, Paul E.; Basu, Arindam; Degertekin, F. L.

2008-01-01

This paper describes a low-power approach to capacitive sensing that achieves a high signal-to-noise ratio. The circuit is composed of a capacitive feedback charge amplifier and a charge adaptation circuit. Without the adaptation circuit, the charge amplifier only consumes 1 μW to achieve the audio band SNR of 69.34dB. An adaptation scheme using Fowler-Nordheim tunneling and channel hot electron injection mechanisms to stabilize the DC output voltage is demonstrated. This scheme provides a very low frequency pole at 0.2Hz. The measured noise spectrums show that this slow-time scale adaptation does not degrade the circuit performance. The DC path can also be provided by a large feedback resistance without causing extra power consumption. A charge amplifier with a MOS-bipolar pseudo-resistor feedback scheme is interfaced with a capacitive micromachined ultrasonic transducer to demonstrate the feasibility of this approach for ultrasound applications. PMID:18787650

Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.

Faster and less phototoxic 3D fluorescence microscopy using a versatile compressed sensing scheme

PubMed Central

Woringer, Maxime; Darzacq, Xavier; Zimmer, Christophe

2017-01-01

Three-dimensional fluorescence microscopy based on Nyquist sampling of focal planes faces harsh trade-offs between acquisition time, light exposure, and signal-to-noise. We propose a 3D compressed sensing approach that uses temporal modulation of the excitation intensity during axial stage sweeping and can be adapted to fluorescence microscopes without hardware modification. We describe implementations on a lattice light sheet microscope and an epifluorescence microscope, and show that images of beads and biological samples can be reconstructed with a 5-10 fold reduction of light exposure and acquisition time. Our scheme opens a new door towards faster and less damaging 3D fluorescence microscopy. PMID:28788909

Fault-tolerant Greenberger-Horne-Zeilinger paradox based on non-Abelian anyons.

PubMed

Deng, Dong-Ling; Wu, Chunfeng; Chen, Jing-Ling; Oh, C H

2010-08-06

We propose a scheme to test the Greenberger-Horne-Zeilinger paradox based on braidings of non-Abelian anyons, which are exotic quasiparticle excitations of topological states of matter. Because topological ordered states are robust against local perturbations, this scheme is in some sense "fault-tolerant" and might close the detection inefficiency loophole problem in previous experimental tests of the Greenberger-Horne-Zeilinger paradox. In turn, the construction of the Greenberger-Horne-Zeilinger paradox reveals the nonlocal property of non-Abelian anyons. Our results indicate that the non-Abelian fractional statistics is a pure quantum effect and cannot be described by local realistic theories. Finally, we present a possible experimental implementation of the scheme based on the anyonic interferometry technologies.

Design of a Single Channel Modulated Wideband Converter for Wideband Spectrum Sensing: Theory, Architecture and Hardware Implementation

PubMed Central

Liu, Weisong; Huang, Zhitao; Wang, Xiang; Sun, Weichao

2017-01-01

In a cognitive radio sensor network (CRSN), wideband spectrum sensing devices which aims to effectively exploit temporarily vacant spectrum intervals as soon as possible are of great importance. However, the challenge of increasingly high signal frequency and wide bandwidth requires an extremely high sampling rate which may exceed today’s best analog-to-digital converters (ADCs) front-end bandwidth. Recently, the newly proposed architecture called modulated wideband converter (MWC), is an attractive analog compressed sensing technique that can highly reduce the sampling rate. However, the MWC has high hardware complexity owing to its parallel channel structure especially when the number of signals increases. In this paper, we propose a single channel modulated wideband converter (SCMWC) scheme for spectrum sensing of band-limited wide-sense stationary (WSS) signals. With one antenna or sensor, this scheme can save not only sampling rate but also hardware complexity. We then present a new, SCMWC based, single node CR prototype System, on which the spectrum sensing algorithm was tested. Experiments on our hardware prototype show that the proposed architecture leads to successful spectrum sensing. And the total sampling rate as well as hardware size is only one channel’s consumption of MWC. PMID:28471410

Inferring Cirrus Size Distributions Through Satellite Remote Sensing and Microphysical Databases

NASA Technical Reports Server (NTRS)

Mitchell, David; D'Entremont, Robert P.; Lawson, R. Paul

2010-01-01

Since cirrus clouds have a substantial influence on the global energy balance that depends on their microphysical properties, climate models should strive to realistically characterize the cirrus ice particle size distribution (PSD), at least in a climatological sense. To date, the airborne in situ measurements of the cirrus PSD have contained large uncertainties due to errors in measuring small ice crystals (D<60 m). This paper presents a method to remotely estimate the concentration of the small ice crystals relative to the larger ones using the 11- and 12- m channels aboard several satellites. By understanding the underlying physics producing the emissivity difference between these channels, this emissivity difference can be used to infer the relative concentration of small ice crystals. This is facilitated by enlisting temperature-dependent characterizations of the PSD (i.e., PSD schemes) based on in situ measurements. An average cirrus emissivity relationship between 12 and 11 m is developed here using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and is used to retrieve the PSD based on six different PSD schemes. The PSDs from the measurement-based PSD schemes are compared with corresponding retrieved PSDs to evaluate differences in small ice crystal concentrations. The retrieved PSDs generally had lower concentrations of small ice particles, with total number concentration independent of temperature. In addition, the temperature dependence of the PSD effective diameter De and fall speed Vf for these retrieved PSD schemes exhibited less variability relative to the unmodified PSD schemes. The reduced variability in the retrieved De and Vf was attributed to the lower concentrations of small ice crystals in the retrieved PSD.

Noninvasive blood pressure measurement scheme based on optical fiber sensor

NASA Astrophysics Data System (ADS)

Liu, Xianxuan; Yuan, Xueguang; Zhang, Yangan

2016-10-01

Optical fiber sensing has many advantages, such as volume small, light quality, low loss, strong in anti-jamming. Since the invention of the optical fiber sensing technology in 1977, optical fiber sensing technology has been applied in the military, national defense, aerospace, industrial, medical and other fields in recent years, and made a great contribution to parameter measurement in the environment under the limited condition .With the rapid development of computer, network system, the intelligent optical fiber sensing technology, the sensor technology, the combination of computer and communication technology , the detection, diagnosis and analysis can be automatically and efficiently completed. In this work, we proposed a noninvasive blood pressure detection and analysis scheme which uses optical fiber sensor. Optical fiber sensing system mainly includes the light source, optical fiber, optical detector, optical modulator, the signal processing module and so on. wavelength optical signals were led into the optical fiber sensor and the signals reflected by the human body surface were detected. By comparing actual testing data with the data got by traditional way to measure the blood pressure we can establish models for predicting the blood pressure and achieve noninvasive blood pressure measurement by using spectrum analysis technology. Blood pressure measurement method based on optical fiber sensing system is faster and more convenient than traditional way, and it can get accurate analysis results in a shorter period of time than before, so it can efficiently reduce the time cost and manpower cost.

Highly sensitive selectively coated photonic crystal fiber-based plasmonic sensor.

PubMed

Rifat, Ahmmed A; Haider, Firoz; Ahmed, Rajib; Mahdiraji, Ghafour Amouzad; Mahamd Adikan, F R; Miroshnichenko, Andrey E

2018-02-15

Highly sensitive and miniaturized sensors are highly desirable for real-time analyte/sample detection. In this Letter, we propose a highly sensitive plasmonic sensing scheme with the miniaturized photonic crystal fiber (PCF) attributes. A large cavity is introduced in the first ring of the PCFs for the efficient field excitation of the surface plasmon polariton mode and proficient infiltration of the sensing elements. Due to the irregular air-hole diameter in the first ring, the cavity exhibits the birefringence behavior which enhances the sensing performance. The novel plasmonic material gold has been used considering the chemical stability in an aqueous environment. The guiding properties and the effects of the sensing performance with different parameters have been investigated by the finite element method, and the proposed PCFs have been fabricated using the stack-and-draw fiber drawing method. The proposed sensor performance was investigated based on the wavelength and amplitude sensing techniques and shows the maximum sensitivities of 11,000 nm/RIU and 1,420  RIU -1 , respectively. It also shows the maximum sensor resolutions of 9.1×10 -6 and 7×10 -6   RIU for the wavelength and amplitude sensing schemes, respectively, and the maximum figure of merits of 407. Furthermore, the proposed sensor is able to detect the analyte refractive indices in the range of 1.33-1.42; as a result, it will find the possible applications in the medical diagnostics, biomolecules, organic chemical, and chemical analyte detection.

Multichannel-Sensing Scheduling and Transmission-Energy Optimizing in Cognitive Radio Networks with Energy Harvesting.

PubMed

Hoan, Tran-Nhut-Khai; Hiep, Vu-Van; Koo, In-Soo

2016-03-31

This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.

Cardiac-induced localized thoracic motion detected by a fiber optic sensing scheme

NASA Astrophysics Data System (ADS)

Allsop, Thomas; Lloyd, Glynn; Bhamber, Ranjeet S.; Hadzievski, Ljupco; Halliday, Michael; Webb, David J.; Bennion, Ian

2014-11-01

The cardiovascular health of the human population is a major concern for medical clinicians, with cardiovascular diseases responsible for 48% of all deaths worldwide, according to the World Health Organization. The development of new diagnostic tools that are practicable and economical to scrutinize the cardiovascular health of humans is a major driver for clinicians. We offer a new technique to obtain seismocardiographic signals up to 54 Hz covering both ballistocardiography (below 20 Hz) and audible heart sounds (20 Hz upward), using a system based on curvature sensors formed from fiber optic long period gratings. This system can visualize the real-time three-dimensional (3-D) mechanical motion of the heart by using the data from the sensing array in conjunction with a bespoke 3-D shape reconstruction algorithm. Visualization is demonstrated by adhering three to four sensors on the outside of the thorax and in close proximity to the apex of the heart; the sensing scheme revealed a complex motion of the heart wall next to the apex region of the heart. The detection scheme is low-cost, portable, easily operated and has the potential for ambulatory applications.

Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems

PubMed Central

Li, Feilong; Li, Zhiqiang; Li, Guangxia; Dong, Feihong; Zhang, Wei

2017-01-01

The usable satellite spectrum is becoming scarce due to static spectrum allocation policies. Cognitive radio approaches have already demonstrated their potential towards spectral efficiency for providing more spectrum access opportunities to secondary user (SU) with sufficient protection to licensed primary user (PU). Hence, recent scientific literature has been focused on the tradeoff between spectrum reuse and PU protection within narrowband spectrum sensing (SS) in terrestrial wireless sensing networks. However, those narrowband SS techniques investigated in the context of terrestrial CR may not be applicable for detecting wideband satellite signals. In this paper, we mainly investigate the problem of joint designing sensing time and hard fusion scheme to maximize SU spectral efficiency in the scenario of low earth orbit (LEO) mobile satellite services based on wideband spectrum sensing. Compressed detection model is established to prove that there indeed exists one optimal sensing time achieving maximal spectral efficiency. Moreover, we propose novel wideband cooperative spectrum sensing (CSS) framework where each SU reporting duration can be utilized for its following SU sensing. The sensing performance benefits from the novel CSS framework because the equivalent sensing time is extended by making full use of reporting slot. Furthermore, in respect of time-varying channel, the spatiotemporal CSS (ST-CSS) is presented to attain space and time diversity gain simultaneously under hard decision fusion rule. Computer simulations show that the optimal sensing settings algorithm of joint optimization of sensing time, hard fusion rule and scheduling strategy achieves significant improvement in spectral efficiency. Additionally, the novel ST-CSS scheme performs much higher spectral efficiency than that of general CSS framework. PMID:28117712

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment

PubMed Central

Wang, Liangmin

2018-01-01

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node’s transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical. PMID:29538314

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment.

PubMed

Sohail, Muhammad; Wang, Liangmin

2018-03-14

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node's transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical.

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

Optimizing the loss of one-dimensional photonic crystal towards high-sensitivity Bloch-surface-wave sensors under intensity interrogation scheme

NASA Astrophysics Data System (ADS)

Kong, Weijing; Wan, Yuhang; Du, Kun; Zhao, Wenhui; Wang, Shuang; Zheng, Zheng

2016-11-01

The reflected intensity change of the Bloch-surface-wave (BSW) resonance influenced by the loss of a truncated onedimensional photonic crystal structure is numerically analyzed and studied in order to enhance the sensitivity of the Bloch-surface-wave-based sensors. The finite truncated one-dimensional photonic crystal structure is designed to be able to excite BSW mode for water (n=1.33) as the external medium and for p-polarized plane wave incident light. The intensity interrogation scheme which can be operated on a typical Kretschmann prism-coupling configuration by measuring the reflected intensity change of the resonance dip is investigated to optimize the sensitivity. A figure of merit (FOM) is introduced to measure the performance of the one-dimensional photonic crystal multilayer structure under the scheme. The detection sensitivities are calculated under different device parameters with a refractive index change corresponding to different solutions of glycerol in de-ionized (DI)-water. The results show that the intensity sensitivity curve varies similarly with the FOM curve and the sensitivity of the Bloch-surface-wave sensor is greatly affected by the device loss, where an optimized loss value can be got. For the low-loss BSW devices, the intensity interrogation sensing sensitivity may drop sharply from the optimal value. On the other hand, the performance of the detection scheme is less affected by the higher device loss. This observation is in accordance with BSW experimental sensing demonstrations as well. The results obtained could be useful for improving the performance of the Bloch-surface-wave sensors for the investigated sensing scheme.

Humanity and Social Responsibility, Solidarity, and Social Rights.

PubMed

Ahola-Launonen, Johanna

2016-04-01

This article discusses the suggestion of having the notion of solidarity as the foundational value for welfare scheme reforms. Solidarity is an emerging concept in bioethical deliberations emphasizing the need for value-oriented discussion in revising healthcare structures, and the notion has been contrasted with liberal justice and rights. I suggest that this contrast is unnecessary, flawed, and potentially counterproductive. As necessary as the sense of solidarity is in a society, it is an insufficient concept to secure the goals related to social responsibility. The discussion on solidarity is also based on a questionable sense of nostalgia. Furthermore, solidarity and liberal justice share essential objectives concerning welfare schemes; therefore, the question arises whether the proper comparison should in the first place be within justice and solidarity.

Channel Estimation and Pilot Design for Massive MIMO Systems with Block-Structured Compressive Sensing

NASA Astrophysics Data System (ADS)

Lv, ZhuoKai; Yang, Tiejun; Zhu, Chunhua

2018-03-01

Through utilizing the technology of compressive sensing (CS), the channel estimation methods can achieve the purpose of reducing pilots and improving spectrum efficiency. The channel estimation and pilot design scheme are explored during the correspondence under the help of block-structured CS in massive MIMO systems. The block coherence property of the aggregate system matrix can be minimized so that the pilot design scheme based on stochastic search is proposed. Moreover, the block sparsity adaptive matching pursuit (BSAMP) algorithm under the common sparsity model is proposed so that the channel estimation can be caught precisely. Simulation results are to be proved the proposed design algorithm with superimposed pilots design and the BSAMP algorithm can provide better channel estimation than existing methods.

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

PubMed

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate statistical modeling techniques, demonstrated advantages for estimating the TP concentration in a large lake and had a strong potential for universal application for the TP concentration estimation in large lake waters worldwide. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Decentralized Adaptive Approach to Fault Tolerant Flight Control

NASA Technical Reports Server (NTRS)

Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor

2000-01-01

This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

A Theoretical Analysis of a New Polarimetric Optical Scheme for Glucose Sensing in the Human Eye

NASA Technical Reports Server (NTRS)

Rovati, Luigi L.; Boeckle, Stefan; Ansari, Rafat R.; Salzman, Jack A. (Technical Monitor)

2002-01-01

The challenging task of in vivo polarimetric glucose sensing is the identification and selection of a scheme to optically access the aqueous humor of the human eye. In this short communication an earlier approach of Cote et al. is theoretically compared with our new optical scheme. Simulations of the new scheme using the eye model of Navarro, suggest that the new optical geometry can overcome the limitations of the previous approach for in vivo measurements of glucose in a human eye.

An Efficient User Authentication and User Anonymity Scheme with Provably Security for IoT-Based Medical Care System.

PubMed

Li, Chun-Ta; Wu, Tsu-Yang; Chen, Chin-Ling; Lee, Cheng-Chi; Chen, Chien-Ming

2017-06-23

In recent years, with the increase in degenerative diseases and the aging population in advanced countries, demands for medical care of older or solitary people have increased continually in hospitals and healthcare institutions. Applying wireless sensor networks for the IoT-based telemedicine system enables doctors, caregivers or families to monitor patients' physiological conditions at anytime and anyplace according to the acquired information. However, transmitting physiological data through the Internet concerns the personal privacy of patients. Therefore, before users can access medical care services in IoT-based medical care system, they must be authenticated. Typically, user authentication and data encryption are most critical for securing network communications over a public channel between two or more participants. In 2016, Liu and Chung proposed a bilinear pairing-based password authentication scheme for wireless healthcare sensor networks. They claimed their authentication scheme cannot only secure sensor data transmission, but also resist various well-known security attacks. In this paper, we demonstrate that Liu-Chung's scheme has some security weaknesses, and we further present an improved secure authentication and data encryption scheme for the IoT-based medical care system, which can provide user anonymity and prevent the security threats of replay and password/sensed data disclosure attacks. Moreover, we modify the authentication process to reduce redundancy in protocol design, and the proposed scheme is more efficient in performance compared with previous related schemes. Finally, the proposed scheme is provably secure in the random oracle model under ECDHP.

Reporter-free potentiometric sensing of boronic acids and their reactions by using quaternary ammonium salt-functionalized polymeric liquid membranes.

PubMed

Wang, Xuewei; Yue, Dengfeng; Lv, Enguang; Wu, Lei; Qin, Wei

2014-02-18

The tremendous applications of boronic acids (BAs) in chemical sensing, medical chemistry, molecular assembly, and organic synthesis lead to an urgent demand for developing effective sensing methods for BAs. This paper reports a facile and sensitive potentiometric sensor scheme for heterogeneous detection of BAs based on their unexpected potential responses on quaternary ammonium salt-doped polymeric liquid membranes. (11)B NMR data reveal that a quaternary ammonium chloride can trigger the hydrolysis of an electrically neutral BA in an aprotic solvent. Using the quaternary ammonium salt as the receptor, the BA molecules can be extracted from the sample solution into the polymeric membrane phase and undergo the concomitant hydrolysis. Such salt-triggered hydrolysis generates H(+) ions, which can be coejected into the aqueous phase with the counterions (e.g., Cl(-)) owing to their high hydrophilicities. The perturbation on the ionic partition at the sample-membrane interface changes the phase boundary potential and thus enables the potentiometric sensing of BAs. In contrast to other transduction methods for BAs, for which labeled or separate reporters are exclusively required, the present heterogeneous sensing scheme allows the direct detection of BAs without using any reporter molecules. This technique shows superior detection limits for BAs (e.g., 1.0 × 10(-6) M for phenylboronic acid) as compared to previously reported methods based on colorimetry, fluorimetry, and mass spectrometry. The proposed sensing strategy has also been successfully applied to potentiometric indication of the BA reactions with hydrogen peroxide and saccharides, which allows indirect and sensitive detection of these important species.

Enhance the Quality of Crowdsensing for Fine-Grained Urban Environment Monitoring via Data Correlation

PubMed Central

Kang, Xu; Liu, Liang; Ma, Huadong

2017-01-01

Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research. Recently, with the popularity of smartphones and vehicles equipped with onboard sensors, a people-centric scheme, namely “crowdsensing”, for city-scale environment monitoring is emerging. This paper proposes a data correlation based crowdsensing approach for fine-grained urban environment monitoring. To demonstrate urban status, we generate sensing images via crowdsensing network, and then enhance the quality of sensing images via data correlation. Specifically, to achieve a higher quality of sensing images, we not only utilize temporal correlation of mobile sensing nodes but also fuse the sensory data with correlated environment data by introducing a collective tensor decomposition approach. Finally, we conduct a series of numerical simulations and a real dataset based case study. The results validate that our approach outperforms the traditional spatial interpolation-based method. PMID:28054968

Adaptive Sampling for Urban Air Quality through Participatory Sensing

PubMed Central

Zeng, Yuanyuan; Xiang, Kai

2017-01-01

Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. PMID:29099766

M-OTDR sensing system based on 3D encoded microstructures

PubMed Central

Sun, Qizhen; Ai, Fan; Liu, Deming; Cheng, Jianwei; Luo, Hongbo; Peng, Kuan; Luo, Yiyang; Yan, Zhijun; Shum, Perry Ping

2017-01-01

In this work, a quasi-distributed sensing scheme named as microstructured OTDR (M-OTDR) by introducing ultra-weak microstructures along the fiber is proposed. Owing to its relative higher reflectivity compared with the backscattered coefficient in fiber and three dimensional (3D) i.e. wavelength/frequency/time encoded property, the M-OTDR system exhibits the superiorities of high signal to noise ratio (SNR), high spatial resolution of millimeter level and high multiplexing capacity up to several ten thousands theoretically. A proof-of-concept system consisting of 64 sensing units is constructed to demonstrate the feasibility and sensing performance. With the help of the demodulation method based on 3D analysis and spectrum reconstruction of the signal light, quasi-distributed temperature sensing with a spatial resolution of 20 cm as well as a measurement resolution of 0.1 °C is realized. PMID:28106132

[Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

PubMed

Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

2006-08-01

In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

Resolution-improved in situ DNA hybridization detection based on microwave photonic interrogation.

PubMed

Cao, Yuan; Guo, Tuan; Wang, Xudong; Sun, Dandan; Ran, Yang; Feng, Xinhuan; Guan, Bai-ou

2015-10-19

In situ bio-sensing system based on microwave photonics filter (MPF) interrogation method with improved resolution is proposed and experimentally demonstrated. A microfiber Bragg grating (mFBG) is used as sensing probe for DNA hybridization detection. Different from the traditional wavelength monitoring technique, we use the frequency interrogation scheme for resolution-improved bio-sensing detection. Experimental results show that the frequency shift of MPF notch presents a linear response to the surrounding refractive index (SRI) change over the range of 1.33 to 1.38, with a SRI resolution up to 2.6 × 10(-5) RIU, which has been increased for almost two orders of magnitude compared with the traditional fundamental mode monitoring technique (~3.6 × 10(-3) RIU). Due to the high Q value (about 27), the whole process of DNA hybridization can be in situ monitored. The proposed MPF-based bio-sensing system provides a new interrogation method over the frequency domain with improved sensing resolution and rapid interrogation rate for biochemical and environmental measurement.

Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System

NASA Technical Reports Server (NTRS)

Penanen, Konstantin; Hahn, Inseob; Ho Eom, Byeong

2009-01-01

A new gradiometer scheme uses middle loops as sensing elements in lowfield superconducting quantum interference device (SQUID) magnetic resonance imaging (MRI). This design of a second order gradiometer increases its sensitivity and makes it more uniform, compared to the conventional side loop sensing scheme with a comparable matching SQUID. The space between the two middle loops becomes the imaging volume with the enclosing cryostat built accordingly.

Meeting stroke survivors' perceived needs: a qualitative study of a community-based exercise and education scheme.

PubMed

Reed, Mary; Harrington, Rachel; Duggan, Aine; Wood, Victorine A

2010-01-01

A qualitative study using a phenomenological approach, to explore stroke survivors' needs and their perceptions of whether a community stroke scheme met these needs. Semi-structured in-depth interviews of 12 stroke survivors, purposively selected from participants attending a new community stroke scheme. Interpretative phenomenological analysis of interviews by two researchers independently. Participants attending the community stroke scheme sought to reconstruct their lives in the aftermath of their stroke. To enable this they needed internal resources of confidence and sense of purpose to 'create their social self', and external resources of 'responsive services' and an 'informal support network', to provide direction and encouragement. Participants felt the community stroke scheme met some of these needs through exercise, goal setting and peer group interaction, which included social support and knowledge acquisition. Stroke survivors need a variety of internal and external resources so that they can rebuild their lives positively post stroke. A stroke-specific community scheme, based on exercise, life-centred goal setting, peer support and knowledge acquisition, is an external resource that can help with meeting some of the stroke survivor's needs.

An Integrated Programmable Wide-range PLL for Switching Synchronization in Isolated DC-DC Converters

NASA Astrophysics Data System (ADS)

Fard, Miad

In this thesis, two Phase-Locked-Loop (PLL) based synchronization schemes are introduced and applied to a bi-directional Dual-Active-Bridge (DAB) dc-dc converter with an input voltage up to 80 V switching in the range of 250 kHz to 1 MHz. The two schemes synchronize gating signals across an isolated boundary without the need for an isolator per transistor. The Power Transformer Sensing (PTS) method utilizes the DAB power transformer to indirectly sense switching on the secondary side of the boundary, while the Digital Isolator Sensing (DIS) method utilizes a miniature transformer for synchronization and communication at up to 100 MHz. The PLL is implemented on-chip, and is used to control an external DAB power-stage. This work will lead to lower cost, high-frequency isolated dc-dc converters needed for a wide variety of emerging low power applications where isolator cost is relatively high and there is a demand for the reduction of parts.

Compressed sensing for ultrasound computed tomography.

PubMed

van Sloun, Ruud; Pandharipande, Ashish; Mischi, Massimo; Demi, Libertario

2015-06-01

Ultrasound computed tomography (UCT) allows the reconstruction of quantitative tissue characteristics, such as speed of sound, mass density, and attenuation. Lowering its acquisition time would be beneficial; however, this is fundamentally limited by the physical time of flight and the number of transmission events. In this letter, we propose a compressed sensing solution for UCT. The adopted measurement scheme is based on compressed acquisitions, with concurrent randomised transmissions in a circular array configuration. Reconstruction of the image is then obtained by combining the born iterative method and total variation minimization, thereby exploiting variation sparsity in the image domain. Evaluation using simulated UCT scattering measurements shows that the proposed transmission scheme performs better than uniform undersampling, and is able to reduce acquisition time by almost one order of magnitude, while maintaining high spatial resolution.

Vernier-like super resolution with guided correlated photon pairs.

PubMed

Nespoli, Matteo; Goan, Hsi-Sheng; Shih, Min-Hsiung

2016-01-11

We describe a dispersion-enabled, ultra-low power realization of super-resolution in an integrated Mach-Zehnder interferometer. Our scheme is based on a Vernier-like effect in the coincident detection of frequency correlated, non-degenerate photon pairs at the sensor output in the presence of group index dispersion. We design and simulate a realistic integrated refractive index sensor in a silicon nitride on silica platform and characterize its performance in the proposed scheme. We present numerical results showing a sensitivity improvement upward of 40 times over a traditional sensing scheme. The device we design is well within the reach of modern semiconductor fabrication technology. We believe this is the first metrology scheme that uses waveguide group index dispersion as a resource to attain super-resolution.

Flexible Ag-C60 nano-biosensors based on surface plasmon coupled emission for clinical and forensic applications.

PubMed

Mulpur, Pradyumna; Yadavilli, Sairam; Mulpur, Praharsha; Kondiparthi, Neeharika; Sengupta, Bishwambhar; Rao, Apparao M; Podila, Ramakrishna; Kamisetti, Venkataramaniah

2015-10-14

The relatively low sensitivity of fluorescence detection schemes, which are mainly limited by the isotropic nature of fluorophore emission, can be overcome by utilizing surface plasmon coupled emission (SPCE). In this study, we demonstrate directional emission from fluorophores on flexible Ag-C60 SPCE sensor platforms for point-of-care sensing, in healthcare and forensic sensing scenarios, with at least 10 times higher sensitivity than traditional fluorescence sensing schemes. Adopting the highly sensitive Ag-C60 SPCE platform based on glass and novel low-cost flexible substrates, we report the unambiguous detection of acid-fast Mycobacterium tuberculosis (Mtb) bacteria at densities as low as 20 Mtb mm(-2); from non-acid-fast bacteria (e.g., E. coli and S. aureus), and the specific on-site detection of acid-fast sperm cells in human semen samples. In combination with the directional emission and high-sensitivity of SPCE platforms, we also demonstrate the utility of smartphones that can replace expensive and cumbersome detectors to enable rapid hand-held detection of analytes in resource-limited settings; a much needed critical advance to biosensors, for developing countries.

UNFOLD-SENSE: a parallel MRI method with self-calibration and artifact suppression.

PubMed

Madore, Bruno

2004-08-01

This work aims at improving the performance of parallel imaging by using it with our "unaliasing by Fourier-encoding the overlaps in the temporal dimension" (UNFOLD) temporal strategy. A self-calibration method called "self, hybrid referencing with UNFOLD and GRAPPA" (SHRUG) is presented. SHRUG combines the UNFOLD-based sensitivity mapping strategy introduced in the TSENSE method by Kellman et al. (5), with the strategy introduced in the GRAPPA method by Griswold et al. (10). SHRUG merges the two approaches to alleviate their respective limitations, and provides fast self-calibration at any given acceleration factor. UNFOLD-SENSE further includes an UNFOLD artifact suppression scheme to significantly suppress artifacts and amplified noise produced by parallel imaging. This suppression scheme, which was published previously (4), is related to another method that was presented independently as part of TSENSE. While the two are equivalent at accelerations < or = 2.0, the present approach is shown here to be significantly superior at accelerations > 2.0, with up to double the artifact suppression at high accelerations. Furthermore, a slight modification of Cartesian SENSE is introduced, which allows departures from purely Cartesian sampling grids. This technique, termed variable-density SENSE (vdSENSE), allows the variable-density data required by SHRUG to be reconstructed with the simplicity and fast processing of Cartesian SENSE. UNFOLD-SENSE is given by the combination of SHRUG for sensitivity mapping, vdSENSE for reconstruction, and UNFOLD for artifact/amplified noise suppression. The method was implemented, with online reconstruction, on both an SSFP and a myocardium-perfusion sequence. The results from six patients scanned with UNFOLD-SENSE are presented.

Long distance, distributed gas sensing based on micro-nano fiber evanescent wave quartz-enhanced photoacoustic spectroscopy

NASA Astrophysics Data System (ADS)

He, Ying; Ma, Yufei; Tong, Yao; Yu, Xin; Peng, Zhenfang; Gao, Jing; Tittel, Frank K.

2017-12-01

A long distance, distributed gas sensing using the micro-nano fiber evanescent wave (FEW) quartz enhanced photoacoustic spectroscopy technique was demonstrated. Such a sensor scheme has the advantages of higher detection sensitivity, distributed gas sensing ability, lower cost, and a simpler fabrication procedure compared to conventional FEW gas sensors using a photonic crystal fiber or a tapered fiber with chemical sputtering. A 3 km single mode fiber with multiple tapers and an erbium doped fiber amplifier with an output optical power of 700 mW were employed to perform long distance, distributed gas measurements.

Numerical study of read scheme in one-selector one-resistor crossbar array

NASA Astrophysics Data System (ADS)

Kim, Sungho; Kim, Hee-Dong; Choi, Sung-Jin

2015-12-01

A comprehensive numerical circuit analysis of read schemes of a one selector-one resistance change memory (1S1R) crossbar array is carried out. Three schemes-the ground, V/2, and V/3 schemes-are compared with each other in terms of sensing margin and power consumption. Without the aid of a complex analytical approach or SPICE-based simulation, a simple numerical iteration method is developed to simulate entire current flows and node voltages within a crossbar array. Understanding such phenomena is essential in successfully evaluating the electrical specifications of selectors for suppressing intrinsic drawbacks of crossbar arrays, such as sneaky current paths and series line resistance problems. This method provides a quantitative tool for the accurate analysis of crossbar arrays and provides guidelines for developing an optimal read scheme, array configuration, and selector device specifications.

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

PubMed

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Simultaneous measurement of magnetic field and temperature based on an etched TCFMI cascaded with an FBG

NASA Astrophysics Data System (ADS)

Yan, Guofeng; Zhang, Liang; He, Sailing

2016-04-01

In this paper, a dual-parameter measurement scheme based on an etched thin core fiber modal interferometer (TCMI) cascaded with a fiber Bragg grating (FBG) is proposed and experimentally demonstrated for simultaneous measurement of magnetic field and temperature. The magnetic field and temperature responses of the packaged TCFMI were first investigated, which showed that the magnetic field sensitivity could be highly enhanced by decreasing of the TCF diameter and the temperature-cross sensitivities were up to 3-7 Oe/°C at 1550 nm. Then, the theoretical analysis and experimental demonstration of the proposed dual-parameter sensing scheme were conducted. Experimental results show that, the reflection of the FBG has a magnetic field intensity and temperature sensitivities of -0.017 dB/Oe and 0.133 dB/°C, respectively, while the Bragg wavelength of the FBG is insensitive to magnetic field and has a temperature sensitivity of 13.23 pm/°C. Thus by using the sensing matrix method, the intensity of the magnetic field and the temperature variance can be measured, which enables magnetic field sensing under strict temperature environments. In the on-off time response test, the fabricated sensor exhibited high repeatability and short response time of ∼19.4 s. Meanwhile the reflective sensing probe type is more compact and practical for applications in hard-to-reach conditions.

Multi-focus image fusion and robust encryption algorithm based on compressive sensing

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Lan; Xiang, Tao; Wang, Yong

2017-06-01

Multi-focus image fusion schemes have been studied in recent years. However, little work has been done in multi-focus image transmission security. This paper proposes a scheme that can reduce data transmission volume and resist various attacks. First, multi-focus image fusion based on wavelet decomposition can generate complete scene images and optimize the perception of the human eye. The fused images are sparsely represented with DCT and sampled with structurally random matrix (SRM), which reduces the data volume and realizes the initial encryption. Then the obtained measurements are further encrypted to resist noise and crop attack through combining permutation and diffusion stages. At the receiver, the cipher images can be jointly decrypted and reconstructed. Simulation results demonstrate the security and robustness of the proposed scheme.

On-chip integrated optofluidic complex refractive index sensing using silicon photonic crystal nanobeam cavities.

PubMed

Zhang, Xingwang; Zhou, Guangya; Shi, Peng; Du, Han; Lin, Tong; Teng, Jinghua; Chau, Fook Siong

2016-03-15

Complex refractive index sensing is proposed and experimentally demonstrated in optofluidic sensors based on silicon photonic crystal nanobeam cavities. The sensitivities are 58 and 139 nm/RIU, respectively, for the real part (n) and the imaginary part (κ) of the complex refractive index, and the corresponding detection limits are 1.8×10(-5) RIU for n and 4.1×10(-6) RIU for κ. Moreover, the capability of the complex refractive index sensing method to detect the concentration composition of the ternary mixture is demonstrated without the surface immobilization of functional groups, which is impossible to realize with the conventional refractive index sensing scheme.

Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?

NASA Astrophysics Data System (ADS)

Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.

2013-09-01

Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.

Counter-Based Broadcast Scheme Considering Reachability, Network Density, and Energy Efficiency for Wireless Sensor Networks.

PubMed

Jung, Ji-Young; Seo, Dong-Yoon; Lee, Jung-Ryun

2018-01-04

A wireless sensor network (WSN) is emerging as an innovative method for gathering information that will significantly improve the reliability and efficiency of infrastructure systems. Broadcast is a common method to disseminate information in WSNs. A variety of counter-based broadcast schemes have been proposed to mitigate the broadcast-storm problems, using the count threshold value and a random access delay. However, because of the limited propagation of the broadcast-message, there exists a trade-off in a sense that redundant retransmissions of the broadcast-message become low and energy efficiency of a node is enhanced, but reachability become low. Therefore, it is necessary to study an efficient counter-based broadcast scheme that can dynamically adjust the random access delay and count threshold value to ensure high reachability, low redundant of broadcast-messages, and low energy consumption of nodes. Thus, in this paper, we first measure the additional coverage provided by a node that receives the same broadcast-message from two neighbor nodes, in order to achieve high reachability with low redundant retransmissions of broadcast-messages. Second, we propose a new counter-based broadcast scheme considering the size of the additional coverage area, distance between the node and the broadcasting node, remaining battery of the node, and variations of the node density. Finally, we evaluate performance of the proposed scheme compared with the existing counter-based broadcast schemes. Simulation results show that the proposed scheme outperforms the existing schemes in terms of saved rebroadcasts, reachability, and total energy consumption.

An Efficient User Authentication and User Anonymity Scheme with Provably Security for IoT-Based Medical Care System

PubMed Central

Wu, Tsu-Yang; Chen, Chin-Ling; Lee, Cheng-Chi; Chen, Chien-Ming

2017-01-01

In recent years, with the increase in degenerative diseases and the aging population in advanced countries, demands for medical care of older or solitary people have increased continually in hospitals and healthcare institutions. Applying wireless sensor networks for the IoT-based telemedicine system enables doctors, caregivers or families to monitor patients’ physiological conditions at anytime and anyplace according to the acquired information. However, transmitting physiological data through the Internet concerns the personal privacy of patients. Therefore, before users can access medical care services in IoT-based medical care system, they must be authenticated. Typically, user authentication and data encryption are most critical for securing network communications over a public channel between two or more participants. In 2016, Liu and Chung proposed a bilinear pairing-based password authentication scheme for wireless healthcare sensor networks. They claimed their authentication scheme cannot only secure sensor data transmission, but also resist various well-known security attacks. In this paper, we demonstrate that Liu–Chung’s scheme has some security weaknesses, and we further present an improved secure authentication and data encryption scheme for the IoT-based medical care system, which can provide user anonymity and prevent the security threats of replay and password/sensed data disclosure attacks. Moreover, we modify the authentication process to reduce redundancy in protocol design, and the proposed scheme is more efficient in performance compared with previous related schemes. Finally, the proposed scheme is provably secure in the random oracle model under ECDHP. PMID:28644381

Proposed Robust Entanglement-Based Magnetic Field Sensor Beyond the Standard Quantum Limit.

PubMed

Tanaka, Tohru; Knott, Paul; Matsuzaki, Yuichiro; Dooley, Shane; Yamaguchi, Hiroshi; Munro, William J; Saito, Shiro

2015-10-23

Recently, there have been significant developments in entanglement-based quantum metrology. However, entanglement is fragile against experimental imperfections, and quantum sensing to beat the standard quantum limit in scaling has not yet been achieved in realistic systems. Here, we show that it is possible to overcome such restrictions so that one can sense a magnetic field with an accuracy beyond the standard quantum limit even under the effect of decoherence, by using a realistic entangled state that can be easily created even with current technology. Our scheme could pave the way for the realizations of practical entanglement-based magnetic field sensors.

Pseudorandom Noise Code-Based Technique for Cloud and Aerosol Discrimination Applications

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Prasad, Narasimha S.; Flood, Michael A.; Harrison, Fenton Wallace

2011-01-01

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a PN code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths. Keywords: ASCENDS, CO2 sensing, O2 sensing, PN codes, CW lidar

Long period gratings in multimode optical fibers: application in chemical sensing

NASA Astrophysics Data System (ADS)

Thomas Lee, S.; Dinesh Kumar, R.; Suresh Kumar, P.; Radhakrishnan, P.; Vallabhan, C. P. G.; Nampoori, V. P. N.

2003-09-01

We propose and demonstrate a new technique for evanescent wave chemical sensing by writing long period gratings in a bare multimode plastic clad silica fiber. The sensing length of the present sensor is only 10 mm, but is as sensitive as a conventional unclad evanescent wave sensor having about 100 mm sensing length. The minimum measurable concentration of the sensor reported here is 10 nmol/l and the operating range is more than 4 orders of magnitude. Moreover, the detection is carried out in two independent detection configurations viz., bright field detection scheme that detects the core-mode power and dark field detection scheme that detects the cladding mode power. The use of such a double detection scheme definitely enhances the reliability and accuracy of the results. Furthermore, the cladding of the present fiber need not be removed as done in conventional evanescent wave fiber sensors.

An Improved Unsupervised Image Segmentation Evaluation Approach Based on - and Over-Segmentation Aware

NASA Astrophysics Data System (ADS)

Su, Tengfei

2018-04-01

In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.

Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals

PubMed Central

Da Poian, Giulia; Brandalise, Denis; Bernardini, Riccardo; Rinaldo, Roberto

2016-01-01

This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%. PMID:28025510

Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme

PubMed Central

Xu, Yang; Luo, Xiong; Wang, Weiping; Zhao, Wenbing

2017-01-01

Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI) as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP) as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN)-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC)-based extreme learning machine (ELM) algorithm (ELM-RCC). Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN) on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE) estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square estimation (LSE) in ELM is replaced by the half-quadratic optimization technique. Simulation results show that our proposed scheme outperforms other traditional localization schemes. PMID:28085084

A Hybrid TDMA/CSMA-Based Wireless Sensor and Data Transmission Network for ORS Intra-Microsatellite Applications

PubMed Central

Wang, Long; Liu, Yong; Yin, Zengshan

2018-01-01

To achieve launch-on-demand for Operationally Responsive Space (ORS) missions, in this article, an intra-satellite wireless network (ISWN) is presented. It provides a wireless and modularized scheme for intra-spacecraft sensing and data buses. By removing the wired data bus, the commercial off-the-shelf (COTS) based wireless modular architecture will reduce both the volume and weight of the satellite platform, thus achieving rapid design and cost savings in development and launching. Based on the on-orbit data demand analysis, a hybrid time division multiple access/carrier sense multiple access (TDMA/CSMA) protocol is proposed. It includes an improved clear channel assessment (CCA) mechanism and a traffic adaptive slot allocation method. To analyze the access process, a Markov model is constructed. Then a detailed calculation is given in which the unsaturated cases are considered. Through simulations, the proposed protocol is proved to commendably satisfy the demands and performs better than existing schemes. It helps to build a full-wireless satellite instead of the current wired ones, and will contribute to provide dynamic space capabilities for ORS missions. PMID:29757243

An ultra-sensitive DeltaR/R measurement system for biochemical sensors using piezoresistive micro-cantilevers.

PubMed

Nag, Sudip; Kale, Nitin S; Rao, V; Sharma, Dinesh K

2009-01-01

Piezoresistive micro-cantilevers are interesting bio-sensing tool whose base resistance value (R) changes by a few parts per million (DeltaR) in deflected conditions. Measuring such a small deviation is always being a challenge due to noise. An advanced and reliable DeltaR/R measurement scheme is presented in this paper which can sense resistance changes down to 6 parts per million. The measurement scheme includes the half-bridge connected micro-cantilevers with mismatch compensation, precision op-amp based filters and amplifiers, and a lock-in amplifier based detector. The input actuating sine wave is applied from a function generator and the output dc voltage is displayed on a digital multimeter. The calibration is performed and instrument sensitivity is calculated. An experimental set-up using a probe station is discussed that demonstrates a combined performance of the measurement system and SU8-polysilicon cantilevers. The deflection sensitivity of such polymeric cantilevers is calculated. The system will be highly useful to detect bio-markers such as myoglobin and troponin that are released in blood during or after heart attacks.

A Hybrid TDMA/CSMA-Based Wireless Sensor and Data Transmission Network for ORS Intra-Microsatellite Applications.

PubMed

Wang, Long; Liu, Yong; Yin, Zengshan

2018-05-12

To achieve launch-on-demand for Operationally Responsive Space (ORS) missions, in this article, an intra-satellite wireless network (ISWN) is presented. It provides a wireless and modularized scheme for intra-spacecraft sensing and data buses. By removing the wired data bus, the commercial off-the-shelf (COTS) based wireless modular architecture will reduce both the volume and weight of the satellite platform, thus achieving rapid design and cost savings in development and launching. Based on the on-orbit data demand analysis, a hybrid time division multiple access/carrier sense multiple access (TDMA/CSMA) protocol is proposed. It includes an improved clear channel assessment (CCA) mechanism and a traffic adaptive slot allocation method. To analyze the access process, a Markov model is constructed. Then a detailed calculation is given in which the unsaturated cases are considered. Through simulations, the proposed protocol is proved to commendably satisfy the demands and performs better than existing schemes. It helps to build a full-wireless satellite instead of the current wired ones, and will contribute to provide dynamic space capabilities for ORS missions.

Development of 100 g Si and 250 g Ge detectors for a dark matter search

NASA Astrophysics Data System (ADS)

Brink, P. L.; Cabrera, B.; Chugg, B.; Clarke, R. M.; Davies, A.; Nam, S. W.; Young, B. A.

1996-05-01

Over the last two years we have proposed and implemented a new phonon sensing scheme for Cryogenic elementary particle detectors based upon Transition Edge Sensors (TES) operated in the (negative) Electrothermal-feedback (ETF) mode, and utilizing large Al collection pads for the initial phonon absorption. We have also implemented an ionization electrode, in addition to the phonon sensors, to allow the simultaneous measurement of ionization and phonon signals in Si and Ge absorbers. Our progress to date include successfully discriminating between electron and nuclear recoils down to a threshold of 4 keV recoil energy for a 4 g Si detector. Our first 100 g Si detectors have been fabricated, and initial work on Ge detectors indicates that our phonon sensing scheme will also work on large mass Ge absorbers.

Graphene-Based Long-Period Fiber Grating Surface Plasmon Resonance Sensor for High-Sensitivity Gas Sensing

PubMed Central

Wei, Wei; Nong, Jinpeng; Zhang, Guiwen; Tang, Linlong; Jiang, Xiao; Chen, Na; Luo, Suqin; Lan, Guilian; Zhu, Yong

2016-01-01

A graphene-based long-period fiber grating (LPFG) surface plasmon resonance (SPR) sensor is proposed. A monolayer of graphene is coated onto the Ag film surface of the LPFG SPR sensor, which increases the intensity of the evanescent field on the surface of the fiber and thereby enhances the interaction between the SPR wave and molecules. Such features significantly improve the sensitivity of the sensor. The experimental results demonstrate that the sensitivity of the graphene-based LPFG SPR sensor can reach 0.344 nm%−1 for methane, which is improved 2.96 and 1.31 times with respect to the traditional LPFG sensor and Ag-coated LPFG SPR sensor, respectively. Meanwhile, the graphene-based LPFG SPR sensor exhibits excellent response characteristics and repeatability. Such a SPR sensing scheme offers a promising platform to achieve high sensitivity for gas-sensing applications. PMID:28025483

Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory

NASA Astrophysics Data System (ADS)

Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo

The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.

High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

NASA Astrophysics Data System (ADS)

Zhao, Shengmei; Wang, Le; Liang, Wenqiang; Cheng, Weiwen; Gong, Longyan

2015-10-01

In this paper, we propose a high performance optical encryption (OE) scheme based on computational ghost imaging (GI) with QR code and compressive sensing (CS) technique, named QR-CGI-OE scheme. N random phase screens, generated by Alice, is a secret key and be shared with its authorized user, Bob. The information is first encoded by Alice with QR code, and the QR-coded image is then encrypted with the aid of computational ghost imaging optical system. Here, measurement results from the GI optical system's bucket detector are the encrypted information and be transmitted to Bob. With the key, Bob decrypts the encrypted information to obtain the QR-coded image with GI and CS techniques, and further recovers the information by QR decoding. The experimental and numerical simulated results show that the authorized users can recover completely the original image, whereas the eavesdroppers can not acquire any information about the image even the eavesdropping ratio (ER) is up to 60% at the given measurement times. For the proposed scheme, the number of bits sent from Alice to Bob are reduced considerably and the robustness is enhanced significantly. Meantime, the measurement times in GI system is reduced and the quality of the reconstructed QR-coded image is improved.

Cluster analysis based on dimensional information with applications to feature selection and classification

NASA Technical Reports Server (NTRS)

Eigen, D. J.; Fromm, F. R.; Northouse, R. A.

1974-01-01

A new clustering algorithm is presented that is based on dimensional information. The algorithm includes an inherent feature selection criterion, which is discussed. Further, a heuristic method for choosing the proper number of intervals for a frequency distribution histogram, a feature necessary for the algorithm, is presented. The algorithm, although usable as a stand-alone clustering technique, is then utilized as a global approximator. Local clustering techniques and configuration of a global-local scheme are discussed, and finally the complete global-local and feature selector configuration is shown in application to a real-time adaptive classification scheme for the analysis of remote sensed multispectral scanner data.

Wavelet-based scalable L-infinity-oriented compression.

PubMed

Alecu, Alin; Munteanu, Adrian; Cornelis, Jan P H; Schelkens, Peter

2006-09-01

Among the different classes of coding techniques proposed in literature, predictive schemes have proven their outstanding performance in near-lossless compression. However, these schemes are incapable of providing embedded L(infinity)-oriented compression, or, at most, provide a very limited number of potential L(infinity) bit-stream truncation points. We propose a new multidimensional wavelet-based L(infinity)-constrained scalable coding framework that generates a fully embedded L(infinity)-oriented bit stream and that retains the coding performance and all the scalability options of state-of-the-art L2-oriented wavelet codecs. Moreover, our codec instantiation of the proposed framework clearly outperforms JPEG2000 in L(infinity) coding sense.

Silicon photonic dual-gas sensor for H2 and CO2 detection.

PubMed

Mi, Guangcan; Horvath, Cameron; Van, Vien

2017-07-10

We report a silicon photonic dual-gas sensor based on a wavelength-multiplexed microring resonator array for simultaneous detection of H 2 and CO 2 gases. The sensor uses Pd as the sensing layer for H 2 gas and a novel functional material based on the Polyhexamethylene Biguanide (PHMB) polymer for CO 2 gas sensing. Gas sensing experiments showed that the PHMB-functionalized microring exhibited high sensitivity to CO 2 gas and excellent selectivity against H 2 . However, the Pd-functionalized microring was found to exhibit sensitivity to both H 2 and CO 2 gases, rendering it ineffective for detecting H 2 in a gas mixture containing CO 2 . We show that the dual-gas sensing scheme can allow for accurate measurement of H 2 concentration in the presence of CO 2 by accounting for the cross-sensitivity of Pd to the latter.

Difference equation state approximations for nonlinear hereditary control problems

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1982-01-01

Discrete approximation schemes for the solution of nonlinear hereditary control problems are constructed. The methods involve approximation by a sequence of optimal control problems in which the original infinite dimensional state equation has been approximated by a finite dimensional discrete difference equation. Convergence of the state approximations is argued using linear semigroup theory and is then used to demonstrate that solutions to the approximating optimal control problems in some sense approximate solutions to the original control problem. Two schemes, one based upon piecewise constant approximation, and the other involving spline functions are discussed. Numerical results are presented, analyzed and used to compare the schemes to other available approximation methods for the solution of hereditary control problems.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO

NASA Astrophysics Data System (ADS)

Gao, Zhen; Dai, Linglong; Wang, Zhaocheng; Chen, Sheng

2015-12-01

This paper proposes a spatially common sparsity based adaptive channel estimation and feedback scheme for frequency division duplex based massive multi-input multi-output (MIMO) systems, which adapts training overhead and pilot design to reliably estimate and feed back the downlink channel state information (CSI) with significantly reduced overhead. Specifically, a non-orthogonal downlink pilot design is first proposed, which is very different from standard orthogonal pilots. By exploiting the spatially common sparsity of massive MIMO channels, a compressive sensing (CS) based adaptive CSI acquisition scheme is proposed, where the consumed time slot overhead only adaptively depends on the sparsity level of the channels. Additionally, a distributed sparsity adaptive matching pursuit algorithm is proposed to jointly estimate the channels of multiple subcarriers. Furthermore, by exploiting the temporal channel correlation, a closed-loop channel tracking scheme is provided, which adaptively designs the non-orthogonal pilot according to the previous channel estimation to achieve an enhanced CSI acquisition. Finally, we generalize the results of the multiple-measurement-vectors case in CS and derive the Cramer-Rao lower bound of the proposed scheme, which enlightens us to design the non-orthogonal pilot signals for the improved performance. Simulation results demonstrate that the proposed scheme outperforms its counterparts, and it is capable of approaching the performance bound.

Modeling and Analysis of Energy Conservation Scheme Based on Duty Cycling in Wireless Ad Hoc Sensor Network

PubMed Central

Chung, Yun Won; Hwang, Ho Young

2010-01-01

In sensor network, energy conservation is one of the most critical issues since sensor nodes should perform a sensing task for a long time (e.g., lasting a few years) but the battery of them cannot be replaced in most practical situations. For this purpose, numerous energy conservation schemes have been proposed and duty cycling scheme is considered the most suitable power conservation technique, where sensor nodes alternate between states having different levels of power consumption. In order to analyze the energy consumption of energy conservation scheme based on duty cycling, it is essential to obtain the probability of each state. In this paper, we analytically derive steady state probability of sensor node states, i.e., sleep, listen, and active states, based on traffic characteristics and timer values, i.e., sleep timer, listen timer, and active timer. The effect of traffic characteristics and timer values on the steady state probability and energy consumption is analyzed in detail. Our work can provide sensor network operators guideline for selecting appropriate timer values for efficient energy conservation. The analytical methodology developed in this paper can be extended to other energy conservation schemes based on duty cycling with different sensor node states, without much difficulty. PMID:22219676

An optical color image watermarking scheme by using compressive sensing with human visual characteristics in gyrator domain

NASA Astrophysics Data System (ADS)

Liansheng, Sui; Bei, Zhou; Zhanmin, Wang; Ailing, Tian

2017-05-01

A novel optical color image watermarking scheme considering human visual characteristics is presented in gyrator transform domain. Initially, an appropriate reference image is constructed of significant blocks chosen from the grayscale host image by evaluating visual characteristics such as visual entropy and edge entropy. Three components of the color watermark image are compressed based on compressive sensing, and the corresponding results are combined to form the grayscale watermark. Then, the frequency coefficients of the watermark image are fused into the frequency data of the gyrator-transformed reference image. The fused result is inversely transformed and partitioned, and eventually the watermarked image is obtained by mapping the resultant blocks into their original positions. The scheme can reconstruct the watermark with high perceptual quality and has the enhanced security due to high sensitivity of the secret keys. Importantly, the scheme can be implemented easily under the framework of double random phase encoding with the 4f optical system. To the best of our knowledge, it is the first report on embedding the color watermark into the grayscale host image which will be out of attacker's expectation. Simulation results are given to verify the feasibility and its superior performance in terms of noise and occlusion robustness.

Enhanced DNA Sensing via Catalytic Aggregation of Gold Nanoparticles

PubMed Central

Huttanus, Herbert M.; Graugnard, Elton; Yurke, Bernard; Knowlton, William B.; Kuang, Wan; Hughes, William L.; Lee, Jeunghoon

2014-01-01

A catalytic colorimetric detection scheme that incorporates a DNA-based hybridization chain reaction into gold nanoparticles was designed and tested. While direct aggregation forms an inter-particle linkage from only ones target DNA strand, the catalytic aggregation forms multiple linkages from a single target DNA strand. Gold nanoparticles were functionalized with thiol-modified DNA strands capable of undergoing hybridization chain reactions. The changes in their absorption spectra were measured at different times and target concentrations and compared against direct aggregation. Catalytic aggregation showed a multifold increase in sensitivity at low target concentrations when compared to direct aggregation. Gel electrophoresis was performed to compare DNA hybridization reactions in catalytic and direct aggregation schemes, and the product formation was confirmed in the catalytic aggregation scheme at low levels of target concentrations. The catalytic aggregation scheme also showed high target specificity. This application of a DNA reaction network to gold nanoparticle-based colorimetric detection enables highly-sensitive, field-deployable, colorimetric readout systems capable of detecting a variety of biomolecules. PMID:23891867

Uniformly high-order accurate non-oscillatory schemes, 1

NASA Technical Reports Server (NTRS)

Harten, A.; Osher, S.

1985-01-01

The construction and the analysis of nonoscillatory shock capturing methods for the approximation of hyperbolic conservation laws was begun. These schemes share many desirable properties with total variation diminishing schemes (TVD), but TVD schemes have at most first order accuracy, in the sense of truncation error, at extreme of the solution. A uniformly second order approximation was constucted, which is nonoscillatory in the sense that the number of extrema of the discrete solution is not increasing in time. This is achieved via a nonoscillatory piecewise linear reconstruction of the solution from its cell averages, time evolution through an approximate solution of the resulting initial value problem, and averaging of this approximate solution over each cell.

Achieve Location Privacy-Preserving Range Query in Vehicular Sensing

PubMed Central

Lu, Rongxing; Ma, Maode; Bao, Haiyong

2017-01-01

Modern vehicles are equipped with a plethora of on-board sensors and large on-board storage, which enables them to gather and store various local-relevant data. However, the wide application of vehicular sensing has its own challenges, among which location-privacy preservation and data query accuracy are two critical problems. In this paper, we propose a novel range query scheme, which helps the data requester to accurately retrieve the sensed data from the distributive on-board storage in vehicular ad hoc networks (VANETs) with location privacy preservation. The proposed scheme exploits structured scalars to denote the locations of data requesters and vehicles, and achieves the privacy-preserving location matching with the homomorphic Paillier cryptosystem technique. Detailed security analysis shows that the proposed range query scheme can successfully preserve the location privacy of the involved data requesters and vehicles, and protect the confidentiality of the sensed data. In addition, performance evaluations are conducted to show the efficiency of the proposed scheme, in terms of computation delay and communication overhead. Specifically, the computation delay and communication overhead are not dependent on the length of the scalar, and they are only proportional to the number of vehicles. PMID:28786943

Achieve Location Privacy-Preserving Range Query in Vehicular Sensing.

PubMed

Kong, Qinglei; Lu, Rongxing; Ma, Maode; Bao, Haiyong

2017-08-08

Modern vehicles are equipped with a plethora of on-board sensors and large on-board storage, which enables them to gather and store various local-relevant data. However, the wide application of vehicular sensing has its own challenges, among which location-privacy preservation and data query accuracy are two critical problems. In this paper, we propose a novel range query scheme, which helps the data requester to accurately retrieve the sensed data from the distributive on-board storage in vehicular ad hoc networks (VANETs) with location privacy preservation. The proposed scheme exploits structured scalars to denote the locations of data requesters and vehicles, and achieves the privacy-preserving location matching with the homomorphic Paillier cryptosystem technique. Detailed security analysis shows that the proposed range query scheme can successfully preserve the location privacy of the involved data requesters and vehicles, and protect the confidentiality of the sensed data. In addition, performance evaluations are conducted to show the efficiency of the proposed scheme, in terms of computation delay and communication overhead. Specifically, the computation delay and communication overhead are not dependent on the length of the scalar, and they are only proportional to the number of vehicles.

Semi-quantum Secure Direct Communication Scheme Based on Bell States

NASA Astrophysics Data System (ADS)

Xie, Chen; Li, Lvzhou; Situ, Haozhen; He, Jianhao

2018-06-01

Recently, the idea of semi-quantumness has been often used in designing quantum cryptographic schemes, which allows some of the participants of a quantum cryptographic scheme to remain classical. One of the reasons why this idea is popular is that it allows a quantum information processing task to be accomplished by using quantum resources as few as possible. In this paper, we extend the idea to quantum secure direct communication(QSDC) by proposing a semi-quantum secure direct communication scheme. In the scheme, the message sender, Alice, encodes each bit into a Bell state |φ+> = 1/{√2}(|00> +|11> ) or |{Ψ }+> = 1/{√ 2}(|01> +|10> ), and the message receiver, Bob, who is classical in the sense that he can either let the qubit he received reflect undisturbed, or measure the qubit in the computational basis |0>, |1> and then resend it in the state he found. Moreover, the security analysis of our scheme is also given.

Symmetric and asymmetric hybrid cryptosystem based on compressive sensing and computer generated holography

NASA Astrophysics Data System (ADS)

Ma, Lihong; Jin, Weimin

2018-01-01

A novel symmetric and asymmetric hybrid optical cryptosystem is proposed based on compressive sensing combined with computer generated holography. In this method there are six encryption keys, among which two decryption phase masks are different from the two random phase masks used in the encryption process. Therefore, the encryption system has the feature of both symmetric and asymmetric cryptography. On the other hand, because computer generated holography can flexibly digitalize the encrypted information and compressive sensing can significantly reduce data volume, what is more, the final encryption image is real function by phase truncation, the method favors the storage and transmission of the encryption data. The experimental results demonstrate that the proposed encryption scheme boosts the security and has high robustness against noise and occlusion attacks.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Functionalization and Characterization of Nanomaterial Gated Field-Effect Transistor-Based Biosensors and the Design of a Multi-Analyte Implantable Biosensing Platform

NASA Astrophysics Data System (ADS)

Croce, Robert A., Jr.

Advances in semiconductor research and complementary-metal-oxide semiconductor fabrication allow for the design and implementation of miniaturized metabolic monitoring systems, as well as advanced biosensor design. The first part of this dissertation will focus on the design and fabrication of nanomaterial (single-walled carbon nanotube and quantum dot) gated field-effect transistors configured as protein sensors. These novel device structures have been functionalized with single-stranded DNA aptamers, and have shown sensor operation towards the protein Thrombin. Such advanced transistor-based sensing schemes present considerable advantages over traditional sensing methodologies in view of its miniaturization, low cost, and facile fabrication, paving the way for the ultimate realization of a multi-analyte lab-on-chip. The second part of this dissertation focuses on the design and fabrication of a needle-implantable glucose sensing platform which is based solely on photovoltaic powering and optical communication. By employing these powering and communication schemes, this design negates the need for bulky on-chip RF-based transmitters and batteries in an effort to attain extreme miniaturization required for needle-implantable/extractable applications. A complete single-sensor system coupled with a miniaturized amperometric glucose sensor has been demonstrated to exhibit reality of this technology. Furthermore, an optical selection scheme of multiple potentiostats for four different analytes (glucose, lactate, O 2 and CO2) as well as the optical transmission of sensor data has been designed for multi-analyte applications. The last part of this dissertation will focus on the development of a computational model for the amperometric glucose sensors employed in the aforementioned implantable platform. This model has been applied to single-layer single-enzyme systems, as well as multi-layer (single enzyme) systems utilizing glucose flux limiting layer-by-layer assembled outer membranes. The concentration of glucose and hydrogen peroxide within the sensor geometry, the transient response and the device response time has been simulated for both systems.

Securing Cooperative Spectrum Sensing Against Collusive SSDF Attack using XOR Distance Analysis in Cognitive Radio Networks

PubMed Central

Feng, Jingyu; Zhang, Man; Xiao, Yun; Yue, Hongzhou

2018-01-01

Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce spectrum resources. However, if CSS assumes that all secondary users (SU) are honest, it may offer opportunities for attackers to conduct a spectrum sensing data falsification (SSDF) attack. To suppress such a threat, recent efforts have been made to develop trust mechanisms. Currently, some attackers can collude with each other to form a collusive clique, and thus not only increase the power of SSDF attack but also avoid the detection of a trust mechanism. Noting the duality of sensing data, we propose a defense scheme called XDA from the perspective of XOR distance analysis to suppress a collusive SSDF attack. In the XDA scheme, the XOR distance calculation in line with the type of “0” and “1” historical sensing data is used to measure the similarity between any two SUs. Noting that collusive SSDF attackers hold high trust value and the minimum XOR distance, the algorithm to detect collusive SSDF attackers is designed. Meanwhile, the XDA scheme can perfect the trust mechanism to correct collusive SSDF attackers’ trust value. Simulation results show that the XDA scheme can enhance the accuracy of trust evaluation, and thus successfully reduce the power of collusive SSDF attack against CSS. PMID:29382061

Experimental and simulated study of a composite structure metamaterial absorber

NASA Astrophysics Data System (ADS)

Li, Shengyong; Ai, Xiaochuan; Wu, Ronghua; Chen, Jiajun

2017-11-01

In this paper, a high performance metamaterial absorber is designed and experimental studied. Measured results indicate that a perfect absorption band and a short-wavelength absorption peak are achieved in the near-infrared spectrum. Current strength distributions reveal that the absorption band is excited by the cavity resonance. And electric field distributions show that the short-wavelength absorption peak is excited by the horizontal coupled of localized surface plasmon (LSP) modes near hole edges. On the one hand, the absorption property of the measured metamaterial absorber can be enhanced through optimizing the structural parameters (a, w, and H). On the other hand, the absorption property is sensitive to the change of refractive index of environmental medias. A sensing scheme is proposed for refractive index detecting based on the figure of merit (FOM) value. Measured results indicate that the proposed sensing scheme can achieve high FOM value with different environmental medias (water, glucose solution).

Autonomous Component Health Management with Failed Component Detection, Identification, and Avoidance

NASA Technical Reports Server (NTRS)

Davis, Robert N.; Polites, Michael E.; Trevino, Luis C.

2004-01-01

This paper details a novel scheme for autonomous component health management (ACHM) with failed actuator detection and failed sensor detection, identification, and avoidance. This new scheme has features that far exceed the performance of systems with triple-redundant sensing and voting, yet requires fewer sensors and could be applied to any system with redundant sensing. Relevant background to the ACHM scheme is provided, and the simulation results for the application of that scheme to a single-axis spacecraft attitude control system with a 3rd order plant and dual-redundant measurement of system states are presented. ACHM fulfills key functions needed by an integrated vehicle health monitoring (IVHM) system. It is: autonomous; adaptive; works in realtime; provides optimal state estimation; identifies failed components; avoids failed components; reconfigures for multiple failures; reconfigures for intermittent failures; works for hard-over, soft, and zero-output failures; and works for both open- and closed-loop systems. The ACHM scheme combines a prefilter that generates preliminary state estimates, detects and identifies failed sensors and actuators, and avoids the use of failed sensors in state estimation with a fixed-gain Kalman filter that generates optimal state estimates and provides model-based state estimates that comprise an integral part of the failure detection logic. The results show that ACHM successfully isolates multiple persistent and intermittent hard-over, soft, and zero-output failures. It is now ready to be tested on a computer model of an actual system.

Energy efficiency in cognitive radio network: Study of cooperative sensing using different channel sensing methods

NASA Astrophysics Data System (ADS)

Cui, Chenxuan

When cognitive radio (CR) operates, it starts by sensing spectrum and looking for idle bandwidth. There are several methods for CR to make a decision on either the channel is occupied or idle, for example, energy detection scheme, cyclostationary detection scheme and matching filtering detection scheme [1]. Among them, the most common method is energy detection scheme because of its algorithm and implementation simplicities [2]. There are two major methods for sensing, the first one is to sense single channel slot with varying bandwidth, whereas the second one is to sense multiple channels and each with same bandwidth. After sensing periods, samples are compared with a preset detection threshold and a decision is made on either the primary user (PU) is transmitting or not. Sometimes the sensing and decision results can be erroneous, for example, false alarm error and misdetection error may occur. In order to better control error probabilities and improve CR network performance (i.e. energy efficiency), we introduce cooperative sensing; in which several CR within a certain range detect and make decisions on channel availability together. The decisions are transmitted to and analyzed by a data fusion center (DFC) to make a final decision on channel availability. After the final decision is been made, DFC sends back the decision to the CRs in order to tell them to stay idle or start to transmit data to secondary receiver (SR) within a preset transmission time. After the transmission, a new cycle starts again with sensing. This thesis report is organized as followed: Chapter II review some of the papers on optimizing CR energy efficiency. In Chapter III, we study how to achieve maximal energy efficiency when CR senses single channel with changing bandwidth and with constrain on misdetection threshold in order to protect PU; furthermore, a case study is given and we calculate the energy efficiency. In Chapter IV, we study how to achieve maximal energy efficiency when CR senses multiple channels and each channel with same bandwidth, also, we preset a misdetection threshold and calculate the energy efficiency. A comparison will be shown between two sensing methods at the end of the chapter. Finally, Chapter V concludes this thesis.

Proximal sensing for soil carbon accounting

NASA Astrophysics Data System (ADS)

England, Jacqueline R.; Viscarra Rossel, Raphael A.

2018-05-01

Maintaining or increasing soil organic carbon (C) is vital for securing food production and for mitigating greenhouse gas (GHG) emissions, climate change, and land degradation. Some land management practices in cropping, grazing, horticultural, and mixed farming systems can be used to increase organic C in soil, but to assess their effectiveness, we need accurate and cost-efficient methods for measuring and monitoring the change. To determine the stock of organic C in soil, one requires measurements of soil organic C concentration, bulk density, and gravel content, but using conventional laboratory-based analytical methods is expensive. Our aim here is to review the current state of proximal sensing for the development of new soil C accounting methods for emissions reporting and in emissions reduction schemes. We evaluated sensing techniques in terms of their rapidity, cost, accuracy, safety, readiness, and their state of development. The most suitable method for measuring soil organic C concentrations appears to be visible-near-infrared (vis-NIR) spectroscopy and, for bulk density, active gamma-ray attenuation. Sensors for measuring gravel have not been developed, but an interim solution with rapid wet sieving and automated measurement appears useful. Field-deployable, multi-sensor systems are needed for cost-efficient soil C accounting. Proximal sensing can be used for soil organic C accounting, but the methods need to be standardized and procedural guidelines need to be developed to ensure proficient measurement and accurate reporting and verification. These are particularly important if the schemes use financial incentives for landholders to adopt management practices to sequester soil organic C. We list and discuss requirements for developing new soil C accounting methods based on proximal sensing, including requirements for recording, verification, and auditing.

Hybrid particle-continuum simulations coupling Brownian dynamics and local dynamic density functional theory.

PubMed

Qi, Shuanhu; Schmid, Friederike

2017-11-08

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense such that particles can switch their level of resolution on the fly. The switching of resolution is controlled by a tuning function which can be chosen at will according to the geometry of the system. As an application, the hybrid scheme is used to study the kinetics of interfacial broadening of a polymer blend, and is validated by comparing the results to the predictions from pure Brownian dynamics and pure local dynamics calculations.

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

2018-04-01

We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

Current use of impact models for agri-environment schemes and potential for improvements of policy design and assessment.

PubMed

Primdahl, Jørgen; Vesterager, Jens Peter; Finn, John A; Vlahos, George; Kristensen, Lone; Vejre, Henrik

2010-06-01

Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES. (c) 2009 Elsevier Ltd. All rights reserved.

Difference equation state approximations for nonlinear hereditary control problems

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1984-01-01

Discrete approximation schemes for the solution of nonlinear hereditary control problems are constructed. The methods involve approximation by a sequence of optimal control problems in which the original infinite dimensional state equation has been approximated by a finite dimensional discrete difference equation. Convergence of the state approximations is argued using linear semigroup theory and is then used to demonstrate that solutions to the approximating optimal control problems in some sense approximate solutions to the original control problem. Two schemes, one based upon piecewise constant approximation, and the other involving spline functions are discussed. Numerical results are presented, analyzed and used to compare the schemes to other available approximation methods for the solution of hereditary control problems. Previously announced in STAR as N83-33589

Inferring electric fields and currents from ground magnetometer data - A test with theoretically derived inputs

NASA Technical Reports Server (NTRS)

Wolf, R. A.; Kamide, Y.

1983-01-01

Advanced techniques considered by Kamide et al. (1981) seem to have the potential for providing observation-based high time resolution pictures of the global ionospheric current and electric field patterns for interesting events. However, a reliance on the proposed magnetogram-inversion schemes for the deduction of global ionospheric current and electric field patterns requires proof that reliable results are obtained. 'Theoretical' tests of the accuracy of the magnetogram inversion schemes have, therefore, been considered. The present investigation is concerned with a test, involving the developed KRM algorithm and the Rice Convection Model (RCM). The test was successful in the sense that there was overall agreement between electric fields and currents calculated by the RCM and KRM schemes.

Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

Distributed strain measurement based on long-gauge FBG and delayed transmission/reflection ratiometric reflectometry for dynamic structural deformation monitoring.

PubMed

Nishiyama, Michiko; Igawa, Hirotaka; Kasai, Tokio; Watanabe, Naoyuki

2015-02-10

In this paper, we propose a delayed transmission/reflection ratiometric reflectometry (DTR(3)) scheme using a long-gauge fiber Bragg grating (FBG), which can be used for dynamic structural deformation monitoring of structures of between a few to tens of meters in length, such as airplane wings and helicopter blades. FBG sensors used for multipoint sensing generally employ wavelength division multiplexing techniques utilizing several Bragg central wavelengths; by contrast, the DTR(3) interrogator uses a continuous pulse array based on a pseudorandom number code and a long-gauge FBG utilizing a single Bragg wavelength and composed of simple hardware devices. The DTR(3) scheme can detect distributed strain at a 50 cm spatial resolution using a long-gauge FBG with a 100 Hz sampling rate. We evaluated the strain sensing characteristics of the long-gauge FBG when attached to a 2.5 m aluminum bar and a 5.5 m helicopter blade model, determining these structure natural frequencies in free vibration tests and their distributed strain characteristics in static tests.

Sensitivity Limits of Rydberg Atom-Based Radio Frequency Electric Field Sensing

NASA Astrophysics Data System (ADS)

Jahangiri, Akbar J.; Kumar, Santosh; Kuebler, Harald; Fan, Haoquan; Shaffer, James P.

2017-04-01

We present progress on Rydberg atom-based RF electric field sensing using Rydberg state electromagnetically induced transparency (EIT) in room temperature atomic vapor cells. In recent experiments on homodyne detection with a Mach-Zehnder interferometer and frequency modulation spectroscopy with active control of residual amplitude modulation we determined that photon shot noise on the probe laser detector limits the sensitivity. Another factor that limits the accuracy is residual Doppler broadening due to the wave-vector mismatch between the coupling and the probe lasers. The sensor as limited by project noise can be orders of magnitude better. A multi-photon scheme is presented that can eliminate the residual Doppler effect by matching the wave-vectors of three lasers and reduce the photon shot noise limit by correctly choosing the Rabi frequencies of the first two steps of the EIT scheme. Using density matrix calculations, we predict that the three-photon approach can improve the detection sensitivity to below 200 nV cm-1 Hz- 1 / 2 and expand the Autler-Townes regime which improves the accuracy. This work is supported by DARPA and the NRO.

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node

PubMed Central

Cai, Zhipeng; Zou, Fumin; Zhang, Xiangyu

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption. PMID:29599945

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node.

PubMed

Luo, Kan; Cai, Zhipeng; Du, Keqin; Zou, Fumin; Zhang, Xiangyu; Li, Jianqing

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes.

PubMed

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme.

All-metal meta-surfaces for narrowband light absorption and high performance sensing

NASA Astrophysics Data System (ADS)

Liu, Zhengqi; Liu, Guiqiang; Fu, Guolan; Liu, Xiaoshan; Huang, Zhenping; Gu, Gang

2016-11-01

We report an experimental scheme for high performance sensing by an all-metal meta-surface (AMMS) platform. A dual-band resonant absorption spectrum with a bandwidth down to a single-digit nanometer level and an absorbance up to 89% is achieved due to the surface lattice resonances supported by the resonators array and their hybridization coupling with the particle plasmon resonances. The sensing application in the analysis of the sodium chloride solution has been demonstrated, where remarkable changes from a spectral ‘dark state’ to ‘bright state’ and vice versa are observed. Sensing performance factors of the figure of merit exceeding 50 and the spectral intensity change related FoM* up to 1075 are simultaneously achieved. The corresponding detection limit is as low as 8.849  ×  10-6 RIU. These features make such an AMMS-based sensor a promising route for efficient bio-chemical sensing, etc.

Remote sensing of plant functional types.

PubMed

Ustin, Susan L; Gamon, John A

2010-06-01

Conceptually, plant functional types represent a classification scheme between species and broad vegetation types. Historically, these were based on physiological, structural and/or phenological properties, whereas recently, they have reflected plant responses to resources or environmental conditions. Often, an underlying assumption, based on an economic analogy, is that the functional role of vegetation can be identified by linked sets of morphological and physiological traits constrained by resources, based on the hypothesis of functional convergence. Using these concepts, ecologists have defined a variety of functional traits that are often context dependent, and the diversity of proposed traits demonstrates the lack of agreement on universal categories. Historically, remotely sensed data have been interpreted in ways that parallel these observations, often focused on the categorization of vegetation into discrete types, often dependent on the sampling scale. At the same time, current thinking in both ecology and remote sensing has moved towards viewing vegetation as a continuum rather than as discrete classes. The capabilities of new remote sensing instruments have led us to propose a new concept of optically distinguishable functional types ('optical types') as a unique way to address the scale dependence of this problem. This would ensure more direct relationships between ecological information and remote sensing observations.

A novel 'Gold on Gold' biosensing scheme for an on-fiber immunoassay

NASA Astrophysics Data System (ADS)

Punjabi, N.; Satija, J.; Mukherji, S.

2015-05-01

In this paper, we propose a novel „gold on gold‟ biosensing scheme for absorbance based fiber-optic biosensor. First, a self-assembled monolayer of gold nanoparticles is formed at the sensing region of the fiber-optic probe by incubating an amino-silanized probe in a colloidal gold solution. Thereafter, the receptor moieties, i.e. Human immunoglobulin G (HIgG) were immobilized by using standard alkanethiol and classic carbodiimide coupling chemistry. Finally, biosensing experiments were performed with different concentrations of gold nanoparticle-tagged analyte, i.e. Goat anti- Human immunoglobulin G (Nanogold-GaHIgG). The sensor response was observed to be more than five-fold compared to the control bioassay, in which the sensor matrix was devoid of gold nanoparticle film. Also, the response was found to be ~10 times higher compared to the FITC-tagged scheme and ~14.5 times better compared to untagged scheme. This novel scheme also demonstrated the potential in improving the limit of detection for the fiber-optic biosensors.

RF Jitter Modulation Alignment Sensing

NASA Astrophysics Data System (ADS)

Ortega, L. F.; Fulda, P.; Diaz-Ortiz, M.; Perez Sanchez, G.; Ciani, G.; Voss, D.; Mueller, G.; Tanner, D. B.

2017-01-01

We will present the numerical and experimental results of a new alignment sensing scheme which can reduce the complexity of alignment sensing systems currently used, while maintaining the same shot noise limited sensitivity. This scheme relies on the ability of electro-optic beam deflectors to create angular modulation sidebands in radio frequency, and needs only a single-element photodiode and IQ demodulation to generate error signals for tilt and translation degrees of freedom in one dimension. It distances itself from current techniques by eliminating the need for beam centering servo systems, quadrant photodetectors and Gouy phase telescopes. RF Jitter alignment sensing can be used to reduce the complexity in the alignment systems of many laser optical experiments, including LIGO and the ALPS experiment.

Second-order accurate nonoscillatory schemes for scalar conservation laws

NASA Technical Reports Server (NTRS)

Huynh, Hung T.

1989-01-01

Explicit finite difference schemes for the computation of weak solutions of nonlinear scalar conservation laws is presented and analyzed. These schemes are uniformly second-order accurate and nonoscillatory in the sense that the number of extrema of the discrete solution is not increasing in time.

BARI+: A Biometric Based Distributed Key Management Approach for Wireless Body Area Networks

PubMed Central

Muhammad, Khaliq-ur-Rahman Raazi Syed; Lee, Heejo; Lee, Sungyoung; Lee, Young-Koo

2010-01-01

Wireless body area networks (WBAN) consist of resource constrained sensing devices just like other wireless sensor networks (WSN). However, they differ from WSN in topology, scale and security requirements. Due to these differences, key management schemes designed for WSN are inefficient and unnecessarily complex when applied to WBAN. Considering the key management issue, WBAN are also different from WPAN because WBAN can use random biometric measurements as keys. We highlight the differences between WSN and WBAN and propose an efficient key management scheme, which makes use of biometrics and is specifically designed for WBAN domain. PMID:22319333

Fiber-optic extrinsic Fabry-Perot interferometer sensors with three-wavelength digital phase demodulation.

PubMed

Schmidt, M; Fürstenau, N

1999-05-01

A three-wavelength-based passive quadrature digital phase-demodulation scheme has been developed for readout of fiber-optic extrinsic Fabry-Perot interferometer vibration, acoustic, and strain sensors. This scheme uses a superluminescent diode light source with interference filters in front of the photodiodes and real-time arctan calculation. Quasi-static strain and dynamic vibration sensing with up to an 80-kHz sampling rate is demonstrated. Periodic nonlinearities owing to dephasing with increasing fringe number are corrected for with a suitable algorithm, resulting in significant improvement of the linearity of the sensor characteristics.

BARI+: a biometric based distributed key management approach for wireless body area networks.

PubMed

Muhammad, Khaliq-ur-Rahman Raazi Syed; Lee, Heejo; Lee, Sungyoung; Lee, Young-Koo

2010-01-01

Wireless body area networks (WBAN) consist of resource constrained sensing devices just like other wireless sensor networks (WSN). However, they differ from WSN in topology, scale and security requirements. Due to these differences, key management schemes designed for WSN are inefficient and unnecessarily complex when applied to WBAN. Considering the key management issue, WBAN are also different from WPAN because WBAN can use random biometric measurements as keys. We highlight the differences between WSN and WBAN and propose an efficient key management scheme, which makes use of biometrics and is specifically designed for WBAN domain.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

PubMed

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-03-20

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

PubMed Central

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-01-01

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods. PMID:28335537

A united event grand canonical Monte Carlo study of partially doped polyaniline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byshkin, M. S., E-mail: mbyshkin@unisa.it, E-mail: gmilano@unisa.it; Correa, A.; Buonocore, F.

2013-12-28

A Grand Canonical Monte Carlo scheme, based on united events combining protonation/deprotonation and insertion/deletion of HCl molecules is proposed for the generation of polyaniline structures at intermediate doping levels between 0% (PANI EB) and 100% (PANI ES). A procedure based on this scheme and subsequent structure relaxations using molecular dynamics is described and validated. Using the proposed scheme and the corresponding procedure, atomistic models of amorphous PANI-HCl structures were generated and studied at different doping levels. Density, structure factors, and solubility parameters were calculated. Their values agree well with available experimental data. The interactions of HCl with PANI have beenmore » studied and distribution of their energies has been analyzed. The procedure has also been extended to the generation of PANI models including adsorbed water and the effect of inclusion of water molecules on PANI properties has also been modeled and discussed. The protocol described here is general and the proposed United Event Grand Canonical Monte Carlo scheme can be easily extended to similar polymeric materials used in gas sensing and to other systems involving adsorption and chemical reactions steps.« less

Mass spectrometry based on a coupled Cooper-pair box and nanomechanical resonator system

NASA Astrophysics Data System (ADS)

Jiang, Cheng; Chen, Bin; Li, Jin-Jin; Zhu, Ka-Di

2011-10-01

Nanomechanical resonators (NRs) with very high frequency have a great potential for mass sensing with unprecedented sensitivity. In this study, we propose a scheme for mass sensing based on the NR capacitively coupled to a Cooper-pair box (CPB) driven by two microwave currents. The accreted mass landing on the resonator can be measured conveniently by tracking the resonance frequency shifts because of mass changes in the signal absorption spectrum. We demonstrate that frequency shifts induced by adsorption of ten 1587 bp DNA molecules can be well resolved in the absorption spectrum. Integration with the CPB enables capacitive readout of the mechanical resonance directly on the chip.

Shape memory alloy wire for self-sensing servo actuation

NASA Astrophysics Data System (ADS)

Josephine Selvarani Ruth, D.; Dhanalakshmi, K.

2017-01-01

This paper reports on the development of a straightforward approach to realise self-sensing shape memory alloy (SMA) wire actuated control. A differential electrical resistance measurement circuit (the sensorless signal conditioning (SSC) circuit) is designed; this sensing signal is directly used as the feedback for control. Antagonistic SMA wire actuators designed for servo actuation is realized in self-sensing actuation (SSA) mode for direct control with the differential electrical resistance feedback. The self-sensing scheme is established on a 1-DOF manipulator with the discrete time sliding mode controls which demonstrates good control performance, whatever be the disturbance and loading conditions. The uniqueness of this work is the design of the generic electronic SSC circuit for SMA actuated system, for measurement and control. With a concern to the implementation of self-sensing technique in SMA, this scheme retains the systematic control architecture by using the sensing signal (self-sensed, electrical resistance corresponding to the system position) for feedback, without requiring any processing as that of the methods adopted and reported previously for SSA techniques of SMA.

Respiratory function monitoring using a real-time three-dimensional fiber-optic shaping sensing scheme based upon fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Allsop, Thomas; Bhamber, Ranjeet; Lloyd, Glynn; Miller, Martin R.; Dixon, Andrew; Webb, David; Ania Castañón, Juan Diego; Bennion, Ian

2012-11-01

An array of in-line curvature sensors on a garment is used to monitor the thoracic and abdominal movements of a human during respiration. The results are used to obtain volumetric changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The array of 40 in-line fiber Bragg gratings is used to produce 20 curvature sensors at different locations, each sensor consisting of two fiber Bragg gratings. The 20 curvature sensors and adjoining fiber are encapsulated into a low-temperature-cured synthetic silicone. The sensors are wavelength interrogated by a commercially available system from Moog Insensys, and the wavelength changes are calibrated to recover curvature. A three-dimensional algorithm is used to generate shape changes during respiration that allow the measurement of absolute volume changes at various sections of the torso. It is shown that the sensing scheme yields a volumetric error of 6%. Comparing the volume data obtained from the spirometer with the volume estimated with the synchronous data from the shape-sensing array yielded a correlation value 0.86 with a Pearson's correlation coefficient p<0.01.

Collaborative damage mapping for emergency response: the role of Cognitive Systems Engineering

NASA Astrophysics Data System (ADS)

Kerle, N.; Hoffman, R. R.

2013-01-01

Remote sensing is increasingly used to assess disaster damage, traditionally by professional image analysts. A recent alternative is crowdsourcing by volunteers experienced in remote sensing, using internet-based mapping portals. We identify a range of problems in current approaches, including how volunteers can best be instructed for the task, ensuring that instructions are accurately understood and translate into valid results, or how the mapping scheme must be adapted for different map user needs. The volunteers, the mapping organizers, and the map users all perform complex cognitive tasks, yet little is known about the actual information needs of the users. We also identify problematic assumptions about the capabilities of the volunteers, principally related to the ability to perform the mapping, and to understand mapping instructions unambiguously. We propose that any robust scheme for collaborative damage mapping must rely on Cognitive Systems Engineering and its principal method, Cognitive Task Analysis (CTA), to understand the information and decision requirements of the map and image users, and how the volunteers can be optimally instructed and their mapping contributions merged into suitable map products. We recommend an iterative approach involving map users, remote sensing specialists, cognitive systems engineers and instructional designers, as well as experimental psychologists.

An Efficient Image Compressor for Charge Coupled Devices Camera

PubMed Central

Li, Jin; Xing, Fei; You, Zheng

2014-01-01

Recently, the discrete wavelet transforms- (DWT-) based compressor, such as JPEG2000 and CCSDS-IDC, is widely seen as the state of the art compression scheme for charge coupled devices (CCD) camera. However, CCD images project on the DWT basis to produce a large number of large amplitude high-frequency coefficients because these images have a large number of complex texture and contour information, which are disadvantage for the later coding. In this paper, we proposed a low-complexity posttransform coupled with compressing sensing (PT-CS) compression approach for remote sensing image. First, the DWT is applied to the remote sensing image. Then, a pair base posttransform is applied to the DWT coefficients. The pair base are DCT base and Hadamard base, which can be used on the high and low bit-rate, respectively. The best posttransform is selected by the l p-norm-based approach. The posttransform is considered as the sparse representation stage of CS. The posttransform coefficients are resampled by sensing measurement matrix. Experimental results on on-board CCD camera images show that the proposed approach significantly outperforms the CCSDS-IDC-based coder, and its performance is comparable to that of the JPEG2000 at low bit rate and it does not have the high excessive implementation complexity of JPEG2000. PMID:25114977

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

Pseudorandom Noise Code-Based Technique for Thin Cloud Discrimination with CO2 and O2 Absorption Measurements

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Prasad, Narasimha S.; Flood, Michael A.

2011-01-01

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a pseudo noise (PN) code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths.

Clowne Science Scheme--A Method Based Course for the Early Years in Secondary Schools

ERIC Educational Resources Information Center

Burden, I. J.; And Others

1975-01-01

Describes a two-year course sequence that is team taught and theme centered. Themes include the earth, the senses, time, and rate of change. The teaching method is the discovery approach and the role of the teacher is outlined. Explains student assessment and outlines problems and observations related to the program. (GS)

A Software Architecture for Adaptive Modular Sensing Systems

PubMed Central

Lyle, Andrew C.; Naish, Michael D.

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration. PMID:22163614

A software architecture for adaptive modular sensing systems.

PubMed

Lyle, Andrew C; Naish, Michael D

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration.

High-Speed Interrogation for Large-Scale Fiber Bragg Grating Sensing

PubMed Central

Hu, Chenyuan; Bai, Wei

2018-01-01

A high-speed interrogation scheme for large-scale fiber Bragg grating (FBG) sensing arrays is presented. This technique employs parallel computing and pipeline control to modulate incident light and demodulate the reflected sensing signal. One Electro-optic modulator (EOM) and one semiconductor optical amplifier (SOA) were used to generate a phase delay to filter reflected spectrum form multiple candidate FBGs with the same optical path difference (OPD). Experimental results showed that the fastest interrogation delay time for the proposed method was only about 27.2 us for a single FBG interrogation, and the system scanning period was only limited by the optical transmission delay in the sensing fiber owing to the multiple simultaneous central wavelength calculations. Furthermore, the proposed FPGA-based technique had a verified FBG wavelength demodulation stability of ±1 pm without average processing. PMID:29495263

High-Speed Interrogation for Large-Scale Fiber Bragg Grating Sensing.

PubMed

Hu, Chenyuan; Bai, Wei

2018-02-24

A high-speed interrogation scheme for large-scale fiber Bragg grating (FBG) sensing arrays is presented. This technique employs parallel computing and pipeline control to modulate incident light and demodulate the reflected sensing signal. One Electro-optic modulator (EOM) and one semiconductor optical amplifier (SOA) were used to generate a phase delay to filter reflected spectrum form multiple candidate FBGs with the same optical path difference (OPD). Experimental results showed that the fastest interrogation delay time for the proposed method was only about 27.2 us for a single FBG interrogation, and the system scanning period was only limited by the optical transmission delay in the sensing fiber owing to the multiple simultaneous central wavelength calculations. Furthermore, the proposed FPGA-based technique had a verified FBG wavelength demodulation stability of ±1 pm without average processing.

Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

PubMed

Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

2016-04-20

Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.

On-chip optical transduction scheme for graphene nano-electro-mechanical systems in silicon-photonic platform.

PubMed

Dash, Aneesh; Selvaraja, S K; Naik, A K

2018-02-15

We present a scheme for on-chip optical transduction of strain and displacement of graphene-based nano-electro-mechanical systems (NEMS). A detailed numerical study on the feasibility of three silicon-photonic integrated circuit configurations is presented: the Mach-Zehnder interferometer (MZI), the micro-ring resonator, and the ring-loaded MZI. An index sensing based technique using an MZI loaded with a ring resonator with a moderate Q-factor of 2400 can yield a sensitivity of 28  fm/Hz and 6.5×10 -6 %/Hz for displacement and strain, respectively. Though any phase-sensitive integrated-photonic device could be used for optical transduction, here we show that optimal sensitivity is achievable by combining resonance with phase sensitivity.

On-chip optical transduction scheme for graphene nano-electro-mechanical systems in silicon-photonic platform

NASA Astrophysics Data System (ADS)

Dash, Aneesh; Selvaraja, S. K.; Naik, A. K.

2018-02-01

We present a scheme for on-chip optical transduction of strain and displacement of Graphene-based Nano-Electro-Mechanical Systems (NEMS). A detailed numerical study on the feasibility of three silicon-photonic integrated circuit configurations is presented: Mach-Zehnder Interferometer(MZI), micro-ring resonator and ring-loaded MZI. An index-sensing based technique using a Mach-Zehnder Interferometer loaded with a ring resonator with a moderate Q-factor of 2400 can yield a sensitivity of 28 fm/sqrt(Hz), and 6.5E-6 %/sqrt(Hz) for displacement and strain respectively. Though any phase sensitive integrated photonic device could be used for optical transduction, here we show that optimal sensitivity is achievable by combining resonance with phase sensitivity.

PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

PubMed

Rizvi, Sanam Shahla; Chung, Tae-Sun

2010-01-01

Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

Portable Nanoparticle-Based Sensors for Food Safety Assessment

PubMed Central

Bülbül, Gonca; Hayat, Akhtar; Andreescu, Silvana

2015-01-01

The use of nanotechnology-derived products in the development of sensors and analytical measurement methodologies has increased significantly over the past decade. Nano-based sensing approaches include the use of nanoparticles (NPs) and nanostructures to enhance sensitivity and selectivity, design new detection schemes, improve sample preparation and increase portability. This review summarizes recent advancements in the design and development of NP-based sensors for assessing food safety. The most common types of NPs used to fabricate sensors for detection of food contaminants are discussed. Selected examples of NP-based detection schemes with colorimetric and electrochemical detection are provided with focus on sensors for the detection of chemical and biological contaminants including pesticides, heavy metals, bacterial pathogens and natural toxins. Current trends in the development of low-cost portable NP-based technology for rapid assessment of food safety as well as challenges for practical implementation and future research directions are discussed. PMID:26690169

COxSwAIN: Compressive Sensing for Advanced Imaging and Navigation

NASA Technical Reports Server (NTRS)

Kurwitz, Richard; Pulley, Marina; LaFerney, Nathan; Munoz, Carlos

2015-01-01

The COxSwAIN project focuses on building an image and video compression scheme that can be implemented in a small or low-power satellite. To do this, we used Compressive Sensing, where the compression is performed by matrix multiplications on the satellite and reconstructed on the ground. Our paper explains our methodology and demonstrates the results of the scheme, being able to achieve high quality image compression that is robust to noise and corruption.

Fibre optic technique for simultaneous measurement of strain and temperature variations in composite materials

NASA Astrophysics Data System (ADS)

Michie, W. C.; Culshaw, Brian; Roberts, Scott S. J.; Davidson, Roger

1991-12-01

A technique based upon the differential sensitivities of dual mode and polarimetric sensing schemes is shown to be capable of resolving simultaneously temperature and strain variations to within 20 micro-epsilon and 1 K over a strain and temperature excursion of 2 micro-epsilon and 45 K. The technique is evaluated experimentally over an 80 cm sensing length of unembedded optical fiber and in an 8 ply unidirectional carbon/epoxide laminate subject to temperature and strain cycling. A comparative analysis of the performance of the embedded and the unembedded fiber sensors is presented.

Parallel phase-shifting self-interference digital holography with faithful reconstruction using compressive sensing

NASA Astrophysics Data System (ADS)

Wan, Yuhong; Man, Tianlong; Wu, Fan; Kim, Myung K.; Wang, Dayong

2016-11-01

We present a new self-interference digital holographic approach that allows single-shot capturing three-dimensional intensity distribution of the spatially incoherent objects. The Fresnel incoherent correlation holographic microscopy is combined with parallel phase-shifting technique to instantaneously obtain spatially multiplexed phase-shifting holograms. The compressive-sensing-based reconstruction algorithm is implemented to reconstruct the original object from the under sampled demultiplexed holograms. The scheme is verified with simulations. The validity of the proposed method is experimentally demonstrated in an indirectly way by simulating the use of specific parallel phase-shifting recording device.

Performance analyses and improvements for the IEEE 802.15.4 CSMA/CA scheme with heterogeneous buffered conditions.

PubMed

Zhu, Jianping; Tao, Zhengsu; Lv, Chunfeng

2012-01-01

Studies of the IEEE 802.15.4 Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) scheme have been received considerable attention recently, with most of these studies focusing on homogeneous or saturated traffic. Two novel transmission schemes-OSTS/BSTS (One Service a Time Scheme/Bulk Service a Time Scheme)-are proposed in this paper to improve the behaviors of time-critical buffered networks with heterogeneous unsaturated traffic. First, we propose a model which contains two modified semi-Markov chains and a macro-Markov chain combined with the theory of M/G/1/K queues to evaluate the characteristics of these two improved CSMA/CA schemes, in which traffic arrivals and accessing packets are bestowed with non-preemptive priority over each other, instead of prioritization. Then, throughput, packet delay and energy consumption of unsaturated, unacknowledged IEEE 802.15.4 beacon-enabled networks are predicted based on the overall point of view which takes the dependent interactions of different types of nodes into account. Moreover, performance comparisons of these two schemes with other non-priority schemes are also proposed. Analysis and simulation results show that delay and fairness of our schemes are superior to those of other schemes, while throughput and energy efficiency are superior to others in more heterogeneous situations. Comprehensive simulations demonstrate that the analysis results of these models match well with the simulation results.

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks.

PubMed

Tang, Chengpei; Shokla, Sanesy Kumcr; Modhawar, George; Wang, Qiang

2016-02-19

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain.

Numerical solution of the unsteady Navier-Stokes equation

NASA Technical Reports Server (NTRS)

Osher, Stanley J.; Engquist, Bjoern

1985-01-01

The construction and the analysis of nonoscillatory shock capturing methods for the approximation of hyperbolic conservation laws are discussed. These schemes share many desirable properties with total variation diminishing schemes, but TVD schemes have at most first-order accuracy, in the sense of truncation error, at extrema of the solution. In this paper a uniformly second-order approximation is constructed, which is nonoscillatory in the sense that the number of extrema of the discrete solution is not increasing in time. This is achieved via a nonoscillatory piecewise linear reconstruction of the solution from its cell averages, time evolution through an approximate solution of the resulting initial value problem, and averaging of this approximate solution over each cell.

Nanofluidic Device with Embedded Nanopore

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2014-03-01

Nanofluidic based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. We also show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore until a certain voltage bias is added.

Blood pulse wave velocity and pressure sensing via fiber based and free space based optical sensors

NASA Astrophysics Data System (ADS)

Sirkis, Talia; Beiderman, Yevgeny; Agdarov, Sergey; Beiderman, Yafim; Zalevsky, Zeev

2017-02-01

Continuous noninvasive measurement of vital bio-signs, such as cardiopulmonary parameters, is an important tool in evaluation of the patient's physiological condition and health monitoring. On the demand of new enabling technologies, some works have been done in continuous monitoring of blood pressure and pulse wave velocity. In this paper, we introduce two techniques for non-contact sensing of vital bio signs. In the first approach the optical sensor is based on single mode in-fibers Mach-Zehnder interferometer (MZI) to detect heartbeat, respiration and pulse wave velocity (PWV). The introduced interferometer is based on a new implanted scheme. It replaces the conventional MZI realized by inserting of discontinuities in the fiber to break the total internal reflection and scatter/collect light. The proposed fiber sensor was successfully incorporated into shirt to produce smart clothing. The measurements obtained from the smart clothing could be obtained in comfortable manner and there is no need to have an initial calibration or a direct contact between the sensor and the skin of the tested individual. In the second concept we show a remote noncontact blood pulse wave velocity and pressure measurement based on tracking the temporal changes of reflected secondary speckle patterns produced in human skin when illuminated by a laser beams. In both concept experimental validation of the proposed schemes is shown and analyzed.

Optimal throughput for cognitive radio with energy harvesting in fading wireless channel.

PubMed

Vu-Van, Hiep; Koo, Insoo

2014-01-01

Energy resource management is a crucial problem of a device with a finite capacity battery. In this paper, cognitive radio is considered to be a device with an energy harvester that can harvest energy from a non-RF energy resource while performing other actions of cognitive radio. Harvested energy will be stored in a finite capacity battery. At the start of the time slot of cognitive radio, the radio needs to determine if it should remain silent or carry out spectrum sensing based on the idle probability of the primary user and the remaining energy in order to maximize the throughput of the cognitive radio system. In addition, optimal sensing energy and adaptive transmission power control are also investigated in this paper to effectively utilize the limited energy of cognitive radio. Finding an optimal approach is formulated as a partially observable Markov decision process. The simulation results show that the proposed optimal decision scheme outperforms the myopic scheme in which current throughput is only considered when making a decision.

Assistive obstacle detection and navigation devices for vision-impaired users.

PubMed

Ong, S K; Zhang, J; Nee, A Y C

2013-09-01

Quality of life for the visually impaired is an urgent worldwide issue that needs to be addressed. Obstacle detection is one of the most important navigation tasks for the visually impaired. In this research, a novel range sensor placement scheme is proposed in this paper for the development of obstacle detection devices. Based on this scheme, two prototypes have been developed targeting at different user groups. This paper discusses the design issues, functional modules and the evaluation tests carried out for both prototypes. Implications for Rehabilitation Visual impairment problem is becoming more severe due to the worldwide ageing population. Individuals with visual impairment require assistance from assistive devices in daily navigation tasks. Traditional assistive devices that assist navigation may have certain drawbacks, such as the limited sensing range of a white cane. Obstacle detection devices applying the range sensor technology can identify road conditions with a higher sensing range to notify the users of potential dangers in advance.

Securing image information using double random phase encoding and parallel compressive sensing with updated sampling processes

NASA Astrophysics Data System (ADS)

Hu, Guiqiang; Xiao, Di; Wang, Yong; Xiang, Tao; Zhou, Qing

2017-11-01

Recently, a new kind of image encryption approach using compressive sensing (CS) and double random phase encoding has received much attention due to the advantages such as compressibility and robustness. However, this approach is found to be vulnerable to chosen plaintext attack (CPA) if the CS measurement matrix is re-used. Therefore, designing an efficient measurement matrix updating mechanism that ensures resistance to CPA is of practical significance. In this paper, we provide a novel solution to update the CS measurement matrix by altering the secret sparse basis with the help of counter mode operation. Particularly, the secret sparse basis is implemented by a reality-preserving fractional cosine transform matrix. Compared with the conventional CS-based cryptosystem that totally generates all the random entries of measurement matrix, our scheme owns efficiency superiority while guaranteeing resistance to CPA. Experimental and analysis results show that the proposed scheme has a good security performance and has robustness against noise and occlusion.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes

PubMed Central

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme. PMID:28072851

Quantum-Enhanced Sensing Based on Time Reversal of Nonlinear Dynamics.

PubMed

Linnemann, D; Strobel, H; Muessel, W; Schulz, J; Lewis-Swan, R J; Kheruntsyan, K V; Oberthaler, M K

2016-07-01

We experimentally demonstrate a nonlinear detection scheme exploiting time-reversal dynamics that disentangles continuous variable entangled states for feasible readout. Spin-exchange dynamics of Bose-Einstein condensates is used as the nonlinear mechanism which not only generates entangled states but can also be time reversed by controlled phase imprinting. For demonstration of a quantum-enhanced measurement we construct an active atom SU(1,1) interferometer, where entangled state preparation and nonlinear readout both consist of parametric amplification. This scheme is capable of exhausting the quantum resource by detecting solely mean atom numbers. Controlled nonlinear transformations widen the spectrum of useful entangled states for applied quantum technologies.

An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT).

PubMed

Li, Ran; Duan, Xiaomeng; Li, Xu; He, Wei; Li, Yanling

2018-04-17

Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

Optical image hiding based on computational ghost imaging

NASA Astrophysics Data System (ADS)

Wang, Le; Zhao, Shengmei; Cheng, Weiwen; Gong, Longyan; Chen, Hanwu

2016-05-01

Imaging hiding schemes play important roles in now big data times. They provide copyright protections of digital images. In the paper, we propose a novel image hiding scheme based on computational ghost imaging to have strong robustness and high security. The watermark is encrypted with the configuration of a computational ghost imaging system, and the random speckle patterns compose a secret key. Least significant bit algorithm is adopted to embed the watermark and both the second-order correlation algorithm and the compressed sensing (CS) algorithm are used to extract the watermark. The experimental and simulation results show that the authorized users can get the watermark with the secret key. The watermark image could not be retrieved when the eavesdropping ratio is less than 45% with the second-order correlation algorithm, whereas it is less than 20% with the TVAL3 CS reconstructed algorithm. In addition, the proposed scheme is robust against the 'salt and pepper' noise and image cropping degradations.

High speed, high performance, portable, dual-channel, optical fiber Bragg grating (FBG) demodulator

NASA Astrophysics Data System (ADS)

Zhang, Hongtao; Wei, Zhanxiong; Fan, Lingling; Wang, Pengfei; Zhao, Xilin; Wang, Zhenhua; Yang, Shangming; Cui, Hong-Liang

2009-10-01

A high speed, high performance, portable, dual-channel, optical Fiber Bragg Grating demodulator based on fiber Fabry- Pérot tunable filter (FFP-FT) is reported in this paper. The high speed demodulation can be achieved to detect the dynamical loads of vehicles with speed of 15 mph. However, the drifts of piezoelectric transducer (PZT) in the cavity of FFP-FT dramatically degrade the stability of system. Two schemes are implemented to improve the stability of system. Firstly, a temperature control system is installed to effectively remove the thermal drifts of PZT. Secondly, a scheme of changing the bias voltage of FFP-FT to restrain non-thermal drifts has been realized at lab and will be further developed to an automatic control system based on microcontroller. Although this demodulator is originally used in Weight-In- Motion (WIM) sensing system, it can be extended into other aspects and the schemes presented in this paper will be useful in many applications.

Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

NASA Astrophysics Data System (ADS)

Benaskeur, Abder R.; Roy, Jean

2001-08-01

Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

Multiple Sensing Application on Wireless Sensor Network Simulation using NS3

NASA Astrophysics Data System (ADS)

Kurniawan, I. F.; Bisma, R.

2018-01-01

Hardware enhancement provides opportunity to install various sensor device on single monitoring node which then enables users to acquire multiple data simultaneously. Constructing multiple sensing application in NS3 is a challenging task since numbers of aspects such as wireless communication, packet transmission pattern, and energy model must be taken into account. Despite of numerous types of monitoring data available, this study only considers two types such as periodic, and event-based data. Periodical data will generate monitoring data follows configured interval, while event-based transmit data when certain determined condition is met. Therefore, this study attempts to cover mentioned aspects in NS3. Several simulations are performed with different number of nodes on arbitrary communication scheme.

Mass sensing based on a circuit cavity electromechanical system

NASA Astrophysics Data System (ADS)

Jiang, Cheng; Chen, Bin; Li, Jin-Jin; Zhu, Ka-Di

2011-10-01

We present a scheme for mass sensing based on a circuit cavity electromechanical system where a free-standing, flexible aluminium membrane is capacitively coupled to a superconducting microwave cavity. Integration with the microwave cavity enables capacitive readout of the mechanical resonance directly on the chip. A microwave pump field and a second probe field are simultaneously applied to the cavity. The accreted mass landing on the membrane can be measured conveniently by tracking the mechanical resonance frequency shifts due to mass changes in the probe transmission spectrum. The mass responsivity for the membrane is 0.72 Hz/ag and we demonstrate that frequency shifts induced by adsorption of one hundred 1587 bp DNA molecules can be well resolved in the probe transmission spectrum.

Bimodal wireless sensing with dual-channel wide bandgap heterostructure varactors

NASA Astrophysics Data System (ADS)

Deen, David A.; Osinsky, Andrei; Miller, Ross

2014-03-01

A capacitive wireless sensing scheme is developed that utilizes an AlN/GaN-based dual-channel varactor. The dual-channel heterostructure affords two capacitance plateaus within the capacitance-voltage (CV) characteristic, owing to the two parallel two-dimensional electron gases (2DEGs) located at respective AlN/GaN interfaces. The capacitance plateaus are leveraged for the definition of two resonant states of the sensor when implemented in an inductively-coupled resonant LRC network for wireless readout. The physics-based CV model is compared with published experimental results, which serve as a basis for the sensor embodiment. The bimodal resonant sensor is befitting for a broad application space ranging from gas, electrostatic, and piezoelectric sensors to biological and chemical detection.

Analysis and experiment on a self-sensing ionic polymer-metal composite actuator

NASA Astrophysics Data System (ADS)

Nam, Doan Ngoc Chi; Ahn, Kyoung Kwan

2014-07-01

An ionic polymer-metal composite (IPMC) actuator is an electro-active polymer (EAP) that bends in response to a small applied electrical field as a result of the mobility of cations in the polymer network. This paper aims to develop a self-sensing actuator for practical use, since current sensing methods generally face limitations due to the compact size and mobility of the IPMC actuator. Firstly, the variation of surface resistance during bending operations is investigated. Then, the behavior of IPMC corresponding to the variation of surface resistance is mathematically analyzed. Based on the analysis results, a simple configuration to realize the self-sensing behavior is introduced. In this technique, the bending curvature of an IPMC can be obtained accurately by employing several feedback voltage signals along with the IPMC length. Finally, experimental evaluations proved the ability of the proposed scheme to estimate the bending behavior of IPMC actuators.

Multi-stage robust scheme for citrus identification from high resolution airborne images

NASA Astrophysics Data System (ADS)

Amorós-López, Julia; Izquierdo Verdiguier, Emma; Gómez-Chova, Luis; Muñoz-Marí, Jordi; Zoilo Rodríguez-Barreiro, Jorge; Camps-Valls, Gustavo; Calpe-Maravilla, Javier

2008-10-01

Identification of land cover types is one of the most critical activities in remote sensing. Nowadays, managing land resources by using remote sensing techniques is becoming a common procedure to speed up the process while reducing costs. However, data analysis procedures should satisfy the accuracy figures demanded by institutions and governments for further administrative actions. This paper presents a methodological scheme to update the citrus Geographical Information Systems (GIS) of the Comunidad Valenciana autonomous region, Spain). The proposed approach introduces a multi-stage automatic scheme to reduce visual photointerpretation and ground validation tasks. First, an object-oriented feature extraction process is carried out for each cadastral parcel from very high spatial resolution (VHR) images (0.5m) acquired in the visible and near infrared. Next, several automatic classifiers (decision trees, multilayer perceptron, and support vector machines) are trained and combined to improve the final accuracy of the results. The proposed strategy fulfills the high accuracy demanded by policy makers by means of combining automatic classification methods with visual photointerpretation available resources. A level of confidence based on the agreement between classifiers allows us an effective management by fixing the quantity of parcels to be reviewed. The proposed methodology can be applied to similar problems and applications.

Performance Analyses and Improvements for the IEEE 802.15.4 CSMA/CA Scheme with Heterogeneous Buffered Conditions

PubMed Central

Zhu, Jianping; Tao, Zhengsu; Lv, Chunfeng

2012-01-01

Studies of the IEEE 802.15.4 Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) scheme have been received considerable attention recently, with most of these studies focusing on homogeneous or saturated traffic. Two novel transmission schemes—OSTS/BSTS (One Service a Time Scheme/Bulk Service a Time Scheme)—are proposed in this paper to improve the behaviors of time-critical buffered networks with heterogeneous unsaturated traffic. First, we propose a model which contains two modified semi-Markov chains and a macro-Markov chain combined with the theory of M/G/1/K queues to evaluate the characteristics of these two improved CSMA/CA schemes, in which traffic arrivals and accessing packets are bestowed with non-preemptive priority over each other, instead of prioritization. Then, throughput, packet delay and energy consumption of unsaturated, unacknowledged IEEE 802.15.4 beacon-enabled networks are predicted based on the overall point of view which takes the dependent interactions of different types of nodes into account. Moreover, performance comparisons of these two schemes with other non-priority schemes are also proposed. Analysis and simulation results show that delay and fairness of our schemes are superior to those of other schemes, while throughput and energy efficiency are superior to others in more heterogeneous situations. Comprehensive simulations demonstrate that the analysis results of these models match well with the simulation results. PMID:22666076

A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-Hoc Networks

PubMed Central

Xu, Yixuan; Chen, Xi; Liu, Anfeng; Hu, Chunhua

2017-01-01

Using mobile vehicles as “data mules” to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the proposed methods instead of their final performance. In this paper, a latency and coverage optimized data collection (LCODC) scheme is proposed to collect data on smart cities through opportunistic routing. Compared with other schemes, the efficiency of data collection is improved since the data flow in LCODC scheme consists of not only vehicle to device transmission (V2D), but also vehicle to vehicle transmission (V2V). Besides, through data mining on patterns hidden in the smart city, waste and redundancy in the utilization of public resources are mitigated, leading to the easy implementation of our scheme. In detail, no extra supporting device is needed in the LCODC scheme to facilitate data transmission. A large-scale and real-world dataset on Beijing is used to evaluate the LCODC scheme. Results indicate that with very limited costs, the LCODC scheme enables the average latency to decrease from several hours to around 12 min with respect to schemes where V2V transmission is disabled while the coverage rate is able to reach over 30%. PMID:28420218

A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks.

PubMed

Xu, Yixuan; Chen, Xi; Liu, Anfeng; Hu, Chunhua

2017-04-18

Using mobile vehicles as "data mules" to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the proposed methods instead of their final performance. In this paper, a latency and coverage optimized data collection (LCODC) scheme is proposed to collect data on smart cities through opportunistic routing. Compared with other schemes, the efficiency of data collection is improved since the data flow in LCODC scheme consists of not only vehicle to device transmission (V2D), but also vehicle to vehicle transmission (V2V). Besides, through data mining on patterns hidden in the smart city, waste and redundancy in the utilization of public resources are mitigated, leading to the easy implementation of our scheme. In detail, no extra supporting device is needed in the LCODC scheme to facilitate data transmission. A large-scale and real-world dataset on Beijing is used to evaluate the LCODC scheme. Results indicate that with very limited costs, the LCODC scheme enables the average latency to decrease from several hours to around 12 min with respect to schemes where V2V transmission is disabled while the coverage rate is able to reach over 30%.

Implementation of a compressive sampling scheme for wireless sensors to achieve energy efficiency in a structural health monitoring system

NASA Astrophysics Data System (ADS)

O'Connor, Sean M.; Lynch, Jerome P.; Gilbert, Anna C.

2013-04-01

Wireless sensors have emerged to offer low-cost sensors with impressive functionality (e.g., data acquisition, computing, and communication) and modular installations. Such advantages enable higher nodal densities than tethered systems resulting in increased spatial resolution of the monitoring system. However, high nodal density comes at a cost as huge amounts of data are generated, weighing heavy on power sources, transmission bandwidth, and data management requirements, often making data compression necessary. The traditional compression paradigm consists of high rate (>Nyquist) uniform sampling and storage of the entire target signal followed by some desired compression scheme prior to transmission. The recently proposed compressed sensing (CS) framework combines the acquisition and compression stage together, thus removing the need for storage and operation of the full target signal prior to transmission. The effectiveness of the CS approach hinges on the presence of a sparse representation of the target signal in a known basis, similarly exploited by several traditional compressive sensing applications today (e.g., imaging, MRI). Field implementations of CS schemes in wireless SHM systems have been challenging due to the lack of commercially available sensing units capable of sampling methods (e.g., random) consistent with the compressed sensing framework, often moving evaluation of CS techniques to simulation and post-processing. The research presented here describes implementation of a CS sampling scheme to the Narada wireless sensing node and the energy efficiencies observed in the deployed sensors. Of interest in this study is the compressibility of acceleration response signals collected from a multi-girder steel-concrete composite bridge. The study shows the benefit of CS in reducing data requirements while ensuring data analysis on compressed data remain accurate.

Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing

NASA Astrophysics Data System (ADS)

Lu, Yichen; Lyu, Hongming; Richardson, Andrew G.; Lucas, Timothy H.; Kuzum, Duygu

2016-09-01

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial.

A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data

NASA Astrophysics Data System (ADS)

Song, Yi; Wang, Jiemin; Yang, Kun; Ma, Mingguo; Li, Xin; Zhang, Zhihui; Wang, Xufeng

2012-07-01

Estimating evapotranspiration (ET) is required for many environmental studies. Remote sensing provides the ability to spatially map latent heat flux. Many studies have developed approaches to derive spatially distributed surface energy fluxes from various satellite sensors with the help of field observations. In this study, remote-sensing-based λE mapping was conducted using a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image. The remotely sensed data and field observations employed in this study were obtained from Watershed Allied Telemetry Experimental Research (WATER). A biophysics-based surface resistance model was revised to account for water stress and temperature constraints. The precision of the results was validated using 'ground truth' data obtained by eddy covariance (EC) system. Scale effects play an important role, especially for parameter optimisation and validation of the latent heat flux (λE). After considering the footprint of EC, the λE derived from the remote sensing data was comparable to the EC measured value during the satellite's passage. The results showed that the revised surface resistance parameterisation scheme was useful for estimating the latent heat flux over cropland in arid regions.

A robust control scheme for flexible arms with friction in the joints

NASA Technical Reports Server (NTRS)

Rattan, Kuldip S.; Feliu, Vicente; Brown, H. Benjamin, Jr.

1988-01-01

A general control scheme to control flexible arms with friction in the joints is proposed in this paper. This scheme presents the advantage of being robust in the sense that it minimizes the effects of the Coulomb friction existing in the motor and the effects of changes in the dynamic friction coefficient. A justification of the robustness properties of the scheme is given in terms of the sensitivity analysis.

An Orbit And Dispersion Correction Scheme for the PEP II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Y.; Donald, M.; Shoaee, H.

2011-09-01

To achieve optimum luminosity in a storage ring it is vital to control the residual vertical dispersion. In the original PEP storage ring, a scheme to control the residual dispersion function was implemented using the ring orbit as the controlling element. The 'best' orbit not necessarily giving the lowest vertical dispersion. A similar scheme has been implemented in both the on-line control code and in the simulation code LEGO. The method involves finding the response matrices (sensitivity of orbit/dispersion at each Beam-Position-Monitor (BPM) to each orbit corrector) and solving in a least squares sense for minimum orbit, dispersion function ormore » both. The optimum solution is usually a subset of the full least squares solution. A scheme of simultaneously correcting the orbits and dispersion has been implemented in the simulation code and on-line control system for PEP-II. The scheme is based on the eigenvector decomposition method. An important ingredient of the scheme is to choose the optimum eigenvectors that minimize the orbit, dispersion and corrector strength. Simulations indicate this to be a very effective way to control the vertical residual dispersion.« less

Dualities and emergent gravity: Gauge/gravity duality

NASA Astrophysics Data System (ADS)

de Haro, Sebastian

2017-08-01

In this paper I develop a framework for relating dualities and emergence: two notions that are close to each other but also exclude one another. I adopt the conception of duality as 'isomorphism', from the physics literature, cashing it out in terms of three conditions. These three conditions prompt two conceptually different ways in which a duality can be modified to make room for emergence; and I argue that this exhausts the possibilities for combining dualities and emergence (via coarse-graining). I apply this framework to gauge/gravity dualities, considering in detail three examples: AdS/CFT, Verlinde's scheme, and black holes. My main point about gauge/gravity dualities is that the theories involved, qua theories of gravity, must be background-independent. I distinguish two senses of background-independence: (i) minimalistic and (ii) extended. I argue that the former is sufficiently strong to allow for a consistent theory of quantum gravity; and that AdS/CFT is background-independent on this account; while Verlinde's scheme best fits the extended sense of background-independence. I argue that this extended sense should be applied with some caution: on pain of throwing the baby (general relativity) out with the bath-water (extended background-independence). Nevertheless, it is an interesting and potentially fruitful heuristic principle for quantum gravity theory construction. It suggests some directions for possible generalisations of gauge/gravity dualities. The interpretation of dualities is discussed; and the so-called 'internal' vs. 'external' viewpoints are articulated in terms of: (i) epistemic and metaphysical commitments; (ii) parts vs. wholes. I then analyse the emergence of gravity in gauge/gravity dualities in terms of the two available conceptualisations of emergence; and I show how emergence in AdS/CFT and in Verlinde's scenario differ from each other. Finally, I give a novel derivation of the Bekenstein-Hawking black hole entropy formula based on Verlinde's scheme; the derivation sheds light on several aspects of Verlinde's scheme and how it compares to Bekenstein's original calculation.

Dictionary-learning-based reconstruction method for electron tomography.

PubMed

Liu, Baodong; Yu, Hengyong; Verbridge, Scott S; Sun, Lizhi; Wang, Ge

2014-01-01

Electron tomography usually suffers from so-called “missing wedge” artifacts caused by limited tilt angle range. An equally sloped tomography (EST) acquisition scheme (which should be called the linogram sampling scheme) was recently applied to achieve 2.4-angstrom resolution. On the other hand, a compressive sensing inspired reconstruction algorithm, known as adaptive dictionary based statistical iterative reconstruction (ADSIR), has been reported for X-ray computed tomography. In this paper, we evaluate the EST, ADSIR, and an ordered-subset simultaneous algebraic reconstruction technique (OS-SART), and compare the ES and equally angled (EA) data acquisition modes. Our results show that OS-SART is comparable to EST, and the ADSIR outperforms EST and OS-SART. Furthermore, the equally sloped projection data acquisition mode has no advantage over the conventional equally angled mode in this context.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Stable integrated hyper-parametric oscillator based on coupled optical microcavities.

PubMed

Armaroli, Andrea; Feron, Patrice; Dumeige, Yannick

2015-12-01

We propose a flexible scheme based on three coupled optical microcavities that permits us to achieve stable oscillations in the microwave range, the frequency of which depends only on the cavity coupling rates. We find that the different dynamical regimes (soft and hard excitation) affect the oscillation intensity, but not their periods. This configuration may permit us to implement compact hyper-parametric sources on an integrated optical circuit with interesting applications in communications, sensing, and metrology.

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

PubMed Central

Tang, Chengpei; Shokla, Sanesy Kumcr; Modhawar, George; Wang, Qiang

2016-01-01

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain. PMID:26907285

[Modeling continuous scaling of NDVI based on fractal theory].

PubMed

Luan, Hai-Jun; Tian, Qing-Jiu; Yu, Tao; Hu, Xin-Li; Huang, Yan; Du, Ling-Tong; Zhao, Li-Min; Wei, Xi; Han, Jie; Zhang, Zhou-Wei; Li, Shao-Peng

2013-07-01

Scale effect was one of the very important scientific problems of remote sensing. The scale effect of quantitative remote sensing can be used to study retrievals' relationship between different-resolution images, and its research became an effective way to confront the challenges, such as validation of quantitative remote sensing products et al. Traditional up-scaling methods cannot describe scale changing features of retrievals on entire series of scales; meanwhile, they are faced with serious parameters correction issues because of imaging parameters' variation of different sensors, such as geometrical correction, spectral correction, etc. Utilizing single sensor image, fractal methodology was utilized to solve these problems. Taking NDVI (computed by land surface radiance) as example and based on Enhanced Thematic Mapper Plus (ETM+) image, a scheme was proposed to model continuous scaling of retrievals. Then the experimental results indicated that: (a) For NDVI, scale effect existed, and it could be described by fractal model of continuous scaling; (2) The fractal method was suitable for validation of NDVI. All of these proved that fractal was an effective methodology of studying scaling of quantitative remote sensing.

Fog-Based Two-Phase Event Monitoring and Data Gathering in Vehicular Sensor Networks

PubMed Central

Yang, Fan; Su, Jinsong; Zhou, Qifeng; Wang, Tian; Zhang, Lu; Xu, Yifan

2017-01-01

Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data. PMID:29286320

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Using a Novel Wireless-Networked Decentralized Control Scheme under Unpredictable Environmental Conditions

PubMed Central

Chang, Chung-Liang; Huang, Yi-Ming; Hong, Guo-Fong

2015-01-01

The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked decentralized fuzzy control scheme to regulate the environmental parameters of various culture zones within a greenhouse. The proposed scheme can create different environmental conditions for cultivating different crops in various zones and achieve diversification or standardization of crop production. A star-type wireless sensor network is utilized to communicate with each sensing node, actuator node, and control node in various zones within the greenhouse. The fuzzy rule-based inference system is used to regulate the environmental parameters for temperature and humidity based on real-time data of plant growth response provided by a growth stage selector. The growth stage selector defines the control ranges of temperature and humidity of the various culture zones according to the leaf area of the plant, the number of leaves, and the cumulative amount of light. The experimental results show that the proposed scheme is stable and robust and provides basis for future greenhouse applications. PMID:26569264

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

A High Noise Immunity, 28 × 16-Channel Finger Touch Sensing IC Using OFDM and Frequency Translation Technique

PubMed Central

Kim, SangYun; Samadpoor Rikan, Behnam; Pu, YoungGun; Yoo, Sang-Sun; Lee, Minjae; Yang, Youngoo; Lee, Kang-Yoon

2018-01-01

In this paper, a high noise immunity, 28 × 16-channel finger touch sensing IC for an orthogonal frequency division multiplexing (OFDM) touch sensing scheme is presented. In order to increase the signal-to-noise ratio (SNR), the OFDM sensing scheme is proposed. The transmitter (TX) transmits the orthogonal signal to each channels of the panel. The receiver (RX) detects the magnitude of the orthogonal frequency to be transmitted from the TX. Due to the orthogonal characteristics, it is robust to narrowband interference and noise. Therefore, the SNR can be improved. In order to reduce the noise effect of low frequencies, a mixer and high-pass filter are proposed as well. After the noise is filtered, the touch SNR attained is 60 dB, from 20 dB before the noise is filtered. The advantage of the proposed OFDM sensing scheme is its ability to detect channels of the panel simultaneously with the use of multiple carriers. To satisfy the linearity of the signal in the OFDM system, a high-linearity mixer and a rail-to-rail amplifier in the TX driver are designed. The proposed design is implemented in 90 nm CMOS process. The SNR is approximately 60 dB. The area is 13.6 mm2, and the power consumption is 62.4 mW. PMID:29883435

Integrated sensing and actuation of dielectric elastomer actuator

NASA Astrophysics Data System (ADS)

Ye, Zhihang; Chen, Zheng

2017-04-01

Dielectric elastomer (DE) is a type of soft actuating material, the shape of which can be changed under electrical voltage stimuli. DE materials have great potential in applications involving energy harvesters, micro-manipulators, and adaptive optics. In this paper, a stripe DE actuator with integrated sensing and actuation is designed and fabricated, and characterized through several experiments. Considering the actuator's capacitor-like structure and its deform mechanism, detecting the actuator's displacement through the actuator's circuit feature is a potential approach. A self-sensing scheme that adds a high frequency probing signal into actuation signal is developed. A fast Fourier transform (FFT) algorithm is used to extract the magnitude change of the probing signal, and a non-linear fitting method and artificial neural network (ANN) approach are utilized to reflect the relationship between the probing signal and the actuator's displacement. Experimental results showed this structure has capability of performing self-sensing and actuation, simultaneously. With an enhanced ANN, the self-sensing scheme can achieve 2.5% accuracy.

Exception handling for sensor fusion

NASA Astrophysics Data System (ADS)

Chavez, G. T.; Murphy, Robin R.

1993-08-01

This paper presents a control scheme for handling sensing failures (sensor malfunctions, significant degradations in performance due to changes in the environment, and errant expectations) in sensor fusion for autonomous mobile robots. The advantages of the exception handling mechanism are that it emphasizes a fast response to sensing failures, is able to use only a partial causal model of sensing failure, and leads to a graceful degradation of sensing if the sensing failure cannot be compensated for. The exception handling mechanism consists of two modules: error classification and error recovery. The error classification module in the exception handler attempts to classify the type and source(s) of the error using a modified generate-and-test procedure. If the source of the error is isolated, the error recovery module examines its cache of recovery schemes, which either repair or replace the current sensing configuration. If the failure is due to an error in expectation or cannot be identified, the planner is alerted. Experiments using actual sensor data collected by the CSM Mobile Robotics/Machine Perception Laboratory's Denning mobile robot demonstrate the operation of the exception handling mechanism.

Dynamical sensitivity control of a single-spin quantum sensor.

PubMed

Lazariev, Andrii; Arroyo-Camejo, Silvia; Rahane, Ganesh; Kavatamane, Vinaya Kumar; Balasubramanian, Gopalakrishnan

2017-07-26

The Nitrogen-Vacancy (NV) defect in diamond is a unique quantum system that offers precision sensing of nanoscale physical quantities at room temperature beyond the current state-of-the-art. The benchmark parameters for nanoscale magnetometry applications are sensitivity, spectral resolution, and dynamic range. Under realistic conditions the NV sensors controlled by conventional sensing schemes suffer from limitations of these parameters. Here we experimentally show a new method called dynamical sensitivity control (DYSCO) that boost the benchmark parameters and thus extends the practical applicability of the NV spin for nanoscale sensing. In contrast to conventional dynamical decoupling schemes, where π pulse trains toggle the spin precession abruptly, the DYSCO method allows for a smooth, analog modulation of the quantum probe's sensitivity. Our method decouples frequency selectivity and spectral resolution unconstrained over the bandwidth (1.85 MHz-392 Hz in our experiments). Using DYSCO we demonstrate high-accuracy NV magnetometry without |2π| ambiguities, an enhancement of the dynamic range by a factor of 4 · 10 3 , and interrogation times exceeding 2 ms in off-the-shelf diamond. In a broader perspective the DYSCO method provides a handle on the inherent dynamics of quantum systems offering decisive advantages for NV centre based applications notably in quantum information and single molecule NMR/MRI.

Long-gauge FBGs interrogated by DTR3 for dynamic distributed strain measurement of helicopter blade model

NASA Astrophysics Data System (ADS)

Nishiyama, M.; Igawa, H.; Kasai, T.; Watanabe, N.

2014-05-01

In this paper, we describe characteristics of distributed strain sensing based on a Delayed Transmission/Reflection Ratiometric Reflectometry (DTR3) scheme with a long-gauge Fiber Bragg Grating (FBG), which is attractive to dynamic structural deformation monitoring such as a helicopter blade and an airplane wing. The DTR3 interrogator using the longgauge FBG has capability of detecting distributed strain with 50 cm spatial resolution in 100 Hz sampling rate. We evaluated distributed strain sensing characteristics of the long-gauge FBG attached on a 5.5 m helicopter blade model in static tests and free vibration dynamic tests.

Compressive self-interference Fresnel digital holography with faithful reconstruction

NASA Astrophysics Data System (ADS)

Wan, Yuhong; Man, Tianlong; Han, Ying; Zhou, Hongqiang; Wang, Dayong

2017-05-01

We developed compressive self-interference digital holographic approach that allows retrieving three-dimensional information of the spatially incoherent objects from single-shot captured hologram. The Fresnel incoherent correlation holography is combined with parallel phase-shifting technique to instantaneously obtain spatial-multiplexed phase-shifting holograms. The recording scheme is regarded as compressive forward sensing model, thus the compressive-sensing-based reconstruction algorithm is implemented to reconstruct the original object from the under sampled demultiplexed sub-holograms. The concept was verified by simulations and experiments with simulating use of the polarizer array. The proposed technique has great potential to be applied in 3D tracking of spatially incoherent samples.

Four-level conservative finite-difference schemes for Boussinesq paradigm equation

NASA Astrophysics Data System (ADS)

Kolkovska, N.

2013-10-01

In this paper a two-parametric family of four level conservative finite difference schemes is constructed for the multidimensional Boussinesq paradigm equation. The schemes are explicit in the sense that no inner iterations are needed for evaluation of the numerical solution. The preservation of the discrete energy with this method is proved. The schemes have been numerically tested on one soliton propagation model and two solitons interaction model. The numerical experiments demonstrate that the proposed family of schemes has second order of convergence in space and time steps in the discrete maximal norm.

Recent Progress In Optical Oxygen Sensing

NASA Astrophysics Data System (ADS)

Wolfbeis, Otto S.; Leiner, Marc J. P.

1988-06-01

Following a brief review on the history of optical oxygen sensing (which shows that a variety of ideas exists in the literature that awaits the extension to fiber optic sensing schemes), the present state of probing oxygen by optical methods is discussed in terms of new methods and materials for sensor construction. Promising sensing schemes include simultaneous measurement of parameters such as oxygen and carbon dioxide with one fiber, measurement of fluorescence lifetimes and radiative energy transfer efficiency as well as phosphorescence quenching. New longwave-excitable fluorophores have been introduced recently, two-band emit-ting indicators can help to eliminate drift problems, and new methods have been found by which both indicators and enzymes may be entrapped in silicone rubber, which opens the way for the design of new biosensors. In a final chapter, the application of fiber optic oxygen sensors for blood gas measurement and as transducers in biosensors are presented.

Hyperspectral absorption and backscattering coefficients of bulk water retrieved from a combination of remote-sensing reflectance and attenuation coefficient.

PubMed

Lin, Junfang; Lee, Zhongping; Ondrusek, Michael; Liu, Xiaohan

2018-01-22

Absorption (a) and backscattering (bb) coefficients play a key role in determining the light field; they also serve as the link between remote sensing and concentrations of optically active water constituents. Here we present an updated scheme to derive hyperspectral a and bb with hyperspectral remote-sensing reflectance (Rrs) and diffuse attenuation coefficient (Kd) as the inputs. Results show that the system works very well from clear open oceans to highly turbid inland waters, with an overall difference less than 25% between these retrievals and those from instrument measurements. This updated scheme advocates the measurement and generation of hyperspectral a and bb from hyperspectral Rrs and Kd, as an independent data source for cross-evaluation of in situ measurements of a and bb and for the development and/or evaluation of remote sensing algorithms for such optical properties.

Implications of non-sustainable agricultural water policies for the water-food nexus in large-scale irrigation systems: A remote sensing approach

NASA Astrophysics Data System (ADS)

Al Zayed, Islam Sabry; Elagib, Nadir Ahmed

2017-12-01

This study proposes a novel monitoring tool based on Satellite Remote Sensing (SRS) data to examine the status of water distribution and Water Use Efficiency (WUE) under changing water policies in large-scale and complex irrigation schemes. The aim is to improve our understanding of the water-food nexus in such schemes. With a special reference to the Gezira Irrigation Scheme (GeIS) in Sudan during the period 2000-2014, the tool devised herein is well suited for cases where validation data are absent. First, it introduces an index, referred to as the Crop Water Consumption Index (CWCI), to assess the efficiency of water policies. The index is defined as the ratio of actual evapotranspiration (ETa) over agricultural areas to total ETa for the whole scheme where ETa is estimated using the Simplified Surface Energy Balance model (SSEB). Second, the tool uses integrated Normalized Difference Vegetation Index (iNDVI), as a proxy for crop productivity, and ETa to assess the WUE. Third, the tool uses SSEB ETa and NDVI in an attempt to detect wastage of water. Four key results emerged from this research as follows: 1) the WUE has not improved despite the changing agricultural and water policies, 2) the seasonal ETa can be used to detect the drier areas of GeIS, i.e. areas with poor irrigation water supply, 3) the decreasing trends of CWCI, slope of iNDVI-ETa linear regression and iNDVI are indicative of inefficient utilization of irrigation water in the scheme, and 4) it is possible to use SSEB ETa and NDVI to identify channels with spillover problems and detect wastage of rainwater that is not used as a source for irrigation. In conclusion, the innovative tool developed herein has provided important information on the efficiency of a large-scale irrigation scheme to help rationalize laborious water management processes and increase productivity.

Improving the representation of mixed-phase cloud microphysics in the ICON-LEM

NASA Astrophysics Data System (ADS)

Tonttila, Juha; Hoose, Corinna; Milbrandt, Jason; Morrison, Hugh

2017-04-01

The representation of ice-phase cloud microphysics in ICON-LEM (the Large-Eddy Model configuration of the ICOsahedral Nonhydrostatic model) is improved by implementing the recently published Predicted Particle Properties (P3) scheme into the model. In the typical two-moment microphysical schemes, such as that previously used in ICON-LEM, ice-phase particles must be partitioned into several prescribed categories. It is inherently difficult to distinguish between categories such as graupel and hail based on just the particle size, yet this partitioning may significantly affect the simulation of convective clouds. The P3 scheme avoids the problems associated with predefined ice-phase categories that are inherent in traditional microphysics schemes by introducing the concept of "free" ice-phase categories, whereby the prognostic variables enable the prediction of a wide range of smoothly varying physical properties and hence particle types. To our knowledge, this is the first application of the P3 scheme in a large-eddy model with horizontal grid spacings on the order of 100 m. We will present results from ICON-LEM simulations with the new P3 scheme comprising idealized stratiform and convective cloud cases. We will also present real-case limited-area simulations focusing on the HOPE (HD(CP)2 Observational Prototype Experiment) intensive observation campaign. The results are compared with a matching set of simulations employing the two-moment scheme and the performance of the model is also evaluated against observations in the context of the HOPE simulations, comprising data from ground based remote sensing instruments.

Cardiac induced localised motion of the human torso detected by a long period grating fibre optic sensing scheme

NASA Astrophysics Data System (ADS)

Allsop, T.; Lloyd, G.; Bhamber, R. S.; Hadzievski, L.; Halliday, M.; Webb, D. J.

2014-05-01

Cardiovascular health of the human population is a major concern for medical clinicians, with cardiovascular diseases responsible for 48% of all deaths worldwide, according to the World Health Organisation. Therefore the development of new practicable and economical diagnostic tools to scrutinise the cardiovascular health of humans is a major driver for clinicians. We offer a new technique to obtain seismocardiographic signals covering both ballistocardiography (below 20Hz) and audible heart sounds (20Hz upwards). The detection scheme is based upon an array of curvature/displacement sensors using fibre optic long period gratings interrogated using a variation of the derivative spectroscopy interrogation technique.

Zonal wavefront sensing with enhanced spatial resolution.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2016-12-01

In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.

An Efficient Semi-fragile Watermarking Scheme for Tamper Localization and Recovery

NASA Astrophysics Data System (ADS)

Hou, Xiang; Yang, Hui; Min, Lianquan

2018-03-01

To solve the problem that remote sensing images are vulnerable to be tampered, a semi-fragile watermarking scheme was proposed. Binary random matrix was used as the authentication watermark, which was embedded by quantizing the maximum absolute value of directional sub-bands coefficients. The average gray level of every non-overlapping 4×4 block was adopted as the recovery watermark, which was embedded in the least significant bit. Watermarking detection could be done directly without resorting to the original images. Experimental results showed our method was robust against rational distortions to a certain extent. At the same time, it was fragile to malicious manipulation, and realized accurate localization and approximate recovery of the tampered regions. Therefore, this scheme can protect the security of remote sensing image effectively.

Glucose Sensing with Phenylboronic Acid Functionalized Hydrogel-Based Optical Diffusers

PubMed Central

2018-01-01

Phenylboronic acids have emerged as synthetic receptors that can reversibly bind to cis-diols of glucose molecules. The incorporation of phenylboronic acids in hydrogels offers exclusive attributes; for example, the binding process with glucose induces Donnan osmotic pressure resulting in volumetric changes in the matrix. However, their practical applications are hindered because of complex readout approaches and their time-consuming fabrication processes. Here, we demonstrate a microimprinting method to fabricate densely packed concavities in phenylboronic acid functionalized hydrogel films. A microengineered optical diffuser structure was imprinted on a phenylboronic acid based cis-diol recognizing motif prepositioned in a hydrogel film. The diffuser structure engineered on the hydrogel was based on laser-inscribed arrays of imperfect microlenses that focused the incoming light at different focal lengths and direction resulting in a diffused profile of light in transmission and reflection readout modes. The signature of the dimensional modulation was detected in terms of changing focal lengths of the microlenses due to the volumetric expansion of the hydrogel that altered the diffusion spectra and transmitted beam profile. The transmitted optical light spread and intensity through the sensor was measured to determine variation in glucose concentrations at physiological conditions. The sensor was integrated in a contact lens and placed over an artificial eye. Artificial stimulation of variation in glucose concentration allowed quantitative measurements using a smartphone’s photodiode. A smartphone app was utilized to convert the received light intensity to quantitative glucose concentration values. The developed sensing platform offers low cost, rapid fabrication, and easy detection scheme as compared to other optical sensing counterparts. The presented detection scheme may have applications in wearable real-time biomarker monitoring devices at point-of-care settings. PMID:29529366

Binary counting with chemical reactions.

PubMed

Kharam, Aleksandra; Jiang, Hua; Riedel, Marc; Parhi, Keshab

2011-01-01

This paper describes a scheme for implementing a binary counter with chemical reactions. The value of the counter is encoded by logical values of "0" and "1" that correspond to the absence and presence of specific molecular types, respectively. It is incremented when molecules of a trigger type are injected. Synchronization is achieved with reactions that produce a sustained three-phase oscillation. This oscillation plays a role analogous to a clock signal in digital electronics. Quantities are transferred between molecular types in different phases of the oscillation. Unlike all previous schemes for chemical computation, this scheme is dependent only on coarse rate categories for the reactions ("fast" and "slow"). Given such categories, the computation is exact and independent of the specific reaction rates. Although conceptual for the time being, the methodology has potential applications in domains of synthetic biology such as biochemical sensing and drug delivery. We are exploring DNA-based computation via strand displacement as a possible experimental chassis.

A Legendre tau-spectral method for solving time-fractional heat equation with nonlocal conditions.

PubMed

Bhrawy, A H; Alghamdi, M A

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem.

A Legendre tau-Spectral Method for Solving Time-Fractional Heat Equation with Nonlocal Conditions

PubMed Central

Bhrawy, A. H.; Alghamdi, M. A.

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem. PMID:25057507

A comparative study of SAR data compression schemes

NASA Technical Reports Server (NTRS)

Lambert-Nebout, C.; Besson, O.; Massonnet, D.; Rogron, B.

1994-01-01

The amount of data collected from spaceborne remote sensing has substantially increased in the last years. During same time period, the ability to store or transmit data has not increased as quickly. At this time, there is a growing interest in developing compression schemes that could provide both higher compression ratios and lower encoding/decoding errors. In the case of the spaceborne Synthetic Aperture Radar (SAR) earth observation system developed by the French Space Agency (CNES), the volume of data to be processed will exceed both the on-board storage capacities and the telecommunication link. The objective of this paper is twofold: to present various compression schemes adapted to SAR data; and to define a set of evaluation criteria and compare the algorithms on SAR data. In this paper, we review two classical methods of SAR data compression and propose novel approaches based on Fourier Transforms and spectrum coding.

Practical scheme for optimal measurement in quantum interferometric devices

NASA Astrophysics Data System (ADS)

Takeoka, Masahiro; Ban, Masashi; Sasaki, Masahide

2003-06-01

We apply a Kennedy-type detection scheme, which was originally proposed for a binary communications system, to interferometric sensing devices. We show that the minimum detectable perturbation of the proposed system reaches the ultimate precision bound which is predicted by quantum Neyman-Pearson hypothesis testing. To provide concrete examples, we apply our interferometric scheme to phase shift detection by using coherent and squeezed probe fields.

Making Sense in the City: Dolly Parton, Early Reading and Educational Policy-Making

ERIC Educational Resources Information Center

Hall, Christine; Jones, Susan

2016-01-01

In this paper, we present a case study of a philanthropic literacy initiative, Dolly Parton's Imagination Library, a book-gifting scheme for under 5s, and consider the impact of the scheme on literacy policy in the English city where it was introduced. We bring four lenses to bear on the case study. First, we analyse the operation of the scheme in…

Monitoring of "all-weather" evapotranspiration using optical and passive microwave remote sensing imagery over the River Source Region in Southwest China

NASA Astrophysics Data System (ADS)

Ma, Y.; Liu, S.

2017-12-01

Accurate estimation of surface evapotranspiration (ET) with high quality is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. However, many aspects urgently need to deeply research, such as the applicability of the ET models, the parameterization schemes optimization at the regional scale, the temporal upscaling, the selecting and developing of the spatiotemporal data fusion method and ground-based validation over heterogeneous land surfaces. This project is based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism need further investigation, including the applicability and the influencing factors, such as local environment, and heterogeneity of the landscape, for improving estimation accuracy. Due to technical and budget limitations, so far, optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions in Southwest China. Here, a multi-source remote sensing data fusion method (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) method will be proposed through blending multi-source remote sensing data acquired by optical, and passive microwave remote sensors on board polar satellite platforms. The accurate "all-weather" ET estimation will be carried out for daily ET of the River Source Region in Southwest China, and then the remotely sensed ET results are overlapped with the footprint-weighted images of EC (eddy correlation) for ground-based validation.

Multi-parameter fiber optic sensors based on fiber random grating

NASA Astrophysics Data System (ADS)

Xu, Yanping; Zhang, Mingjiang; Lu, Ping; Mihailov, Stephen; Bao, Xiaoyi

2017-04-01

Two novel configurations of multi-parameter fiber-optic sensing systems based on the fiber random grating are reported. The fiber random grating is fabricated through femtosecond laser induced refractive index modification over a 10cm standard telecom single mode fiber. In one configuration, the reflective spectrum of the fiber random grating is directly detected and a wavelength-division spectral cross-correlation algorithm is adopted to extract the spectral shifts for simultaneous measurement of temperature, axial strain, and surrounding refractive index. In the other configuration, a random fiber ring laser is constructed by incorporating the random feedback from the random grating. Numerous polarization-dependent spectral filters are formed along the random grating and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which enables a high-fidelity multi-parameter sensing scheme by monitoring the spectral shifts of the lasing lines. Without the need of phase mask for fabrication and with the high physical strength, the random grating based sensors are much simpler and more compact, which could be potentially an excellent alternative for liquid medical sample sensing in biomedical and biochemical applications.

Dynamic interrogator for elastic wave sensing using Fabry Perot filters based on fiber Bragg gratings.

PubMed

Harish, Achar V; Varghese, Bibin; Rao, Babu; Balasubramaniam, Krishnan; Srinivasan, Balaji

2015-07-01

Use of in-fiber Fabry-Perot (FP) filters based on fiber Bragg gratings as both sensor as well as an interrogator for enhancing the detection limit of elastic wave sensing is investigated in this paper. The sensitivity of such a demodulation scheme depends on the spectral discrimination of the sensor and interrogator gratings. Simulations have shown that the use of in-fiber FP filters with high finesse provide better performance in terms of sensitivity compared to the demodulation using fiber Bragg gratings. Based on these results, a dynamic interrogator capable of sensing acoustic waves with amplitude of less than 1 micro-strain over frequencies of 10 kHz to several 100 kHz has been implemented. Frequency response of the fiber Bragg gratings in the given experimental setup has been compared to that of the conventional piezo sensors demonstrating that fiber Bragg gratings can be used over a relatively broad frequency range. Dynamic interrogator has been packaged in a compact box without any degradation in its performance. Copyright © 2015 Elsevier B.V. All rights reserved.

Mobile Phone Middleware Architecture for Energy and Context Awareness in Location-Based Services

PubMed Central

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-01-01

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution. PMID:25513821

Mobile phone middleware architecture for energy and context awareness in location-based services.

PubMed

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-12-10

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2013-03-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with embedded pore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a pore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can optically detect successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule. Furthermore, electrical measurements through the nanopore are performed, indicating that DNA sensing is feasible using the nanochannel-nanopore device.

Linear approximations of global behaviors in nonlinear systems with moderate or strong noise

NASA Astrophysics Data System (ADS)

Liang, Junhao; Din, Anwarud; Zhou, Tianshou

2018-03-01

While many physical or chemical systems can be modeled by nonlinear Langevin equations (LEs), dynamical analysis of these systems is challenging in the cases of moderate and strong noise. Here we develop a linear approximation scheme, which can transform an often intractable LE into a linear set of binomial moment equations (BMEs). This scheme provides a feasible way to capture nonlinear behaviors in the sense of probability distribution and is effective even when the noise is moderate or big. Based on BMEs, we further develop a noise reduction technique, which can effectively handle tough cases where traditional small-noise theories are inapplicable. The overall method not only provides an approximation-based paradigm to analysis of the local and global behaviors of nonlinear noisy systems but also has a wide range of applications.

Conjugated amplifying polymers for optical sensing applications.

PubMed

Rochat, Sébastien; Swager, Timothy M

2013-06-12

Thanks to their unique optical and electrochemical properties, conjugated polymers have attracted considerable attention over the last two decades and resulted in numerous technological innovations. In particular, their implementation in sensing schemes and devices was widely investigated and produced a multitude of sensory systems and transduction mechanisms. Conjugated polymers possess numerous attractive features that make them particularly suitable for a broad variety of sensing tasks. They display sensory signal amplification (compared to their small-molecule counterparts) and their structures can easily be tailored to adjust solubility, absorption/emission wavelengths, energy offsets for excited state electron transfer, and/or for use in solution or in the solid state. This versatility has made conjugated polymers a fluorescence sensory platform of choice in the recent years. In this review, we highlight a variety of conjugated polymer-based sensory mechanisms together with selected examples from the recent literature.

Application of a dual-resolution voxelization scheme to compressed-sensing (CS)-based iterative reconstruction in digital tomosynthesis (DTS)

NASA Astrophysics Data System (ADS)

Park, S. Y.; Kim, G. A.; Cho, H. S.; Park, C. K.; Lee, D. Y.; Lim, H. W.; Lee, H. W.; Kim, K. S.; Kang, S. Y.; Park, J. E.; Kim, W. S.; Jeon, D. H.; Je, U. K.; Woo, T. H.; Oh, J. E.

2018-02-01

In recent digital tomosynthesis (DTS), iterative reconstruction methods are often used owing to the potential to provide multiplanar images of superior image quality to conventional filtered-backprojection (FBP)-based methods. However, they require enormous computational cost in the iterative process, which has still been an obstacle to put them to practical use. In this work, we propose a new DTS reconstruction method incorporated with a dual-resolution voxelization scheme in attempt to overcome these difficulties, in which the voxels outside a small region-of-interest (ROI) containing target diagnosis are binned by 2 × 2 × 2 while the voxels inside the ROI remain unbinned. We considered a compressed-sensing (CS)-based iterative algorithm with a dual-constraint strategy for more accurate DTS reconstruction. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. Our results indicate that the proposed method seems to be effective for reducing computational cost considerably in iterative DTS reconstruction, keeping the image quality inside the ROI not much degraded. A binning size of 2 × 2 × 2 required only about 31.9% computational memory and about 2.6% reconstruction time, compared to those for no binning case. The reconstruction quality was evaluated in terms of the root-mean-square error (RMSE), the contrast-to-noise ratio (CNR), and the universal-quality index (UQI).

Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data

NASA Technical Reports Server (NTRS)

2000-01-01

Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.

Making sense of landscape change: Long-term perceptions among local residents following river restoration

NASA Astrophysics Data System (ADS)

Westling, Emma L.; Surridge, Ben W. J.; Sharp, Liz; Lerner, David N.

2014-11-01

Efforts to restore rivers are increasingly concerned with the social implications of landscape change. However, the fundamental issue of how people make sense of local riverine environments in the context of restoration remains poorly understood. Our research examined influences on perception among local residents 14 years after a restoration scheme on the River Dearne in the north of England. Human-landscape relationships emerging from semi-structured interviews with 16 local residents were analysed using an interpretive research framework. Nine recurring factors influenced perception among local residents: scenic beauty; the condition of riparian vegetation and of river channel morphology; opportunities to observe flora and fauna; cleanliness of the riverine environment; access available to the river; connections between the river and the surrounding landscape; disturbance and change in the familiarity of the landscape following restoration. These factors were not solely related to tangible outcomes of the restoration scheme, but were also influenced by history, memories, traditions and practices associated with the river. Critically, these factors also interacted rather than operating in isolation and two idealised perceptual frameworks were developed to map these interactions. Our research contributes to theoretical understanding of the relationships between humans and landscape change, whilst also considering how restoration practice may better reflect these relationships. The importance of a social dimension to the template of possibilities for restoring any given river emerges, underpinning place-based design and implementation of river restoration schemes.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things.

PubMed

Yi, Meng; Chen, Qingkui; Xiong, Neal N

2016-11-03

This paper considers the distributed access and control problem of massive wireless sensor networks' data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

Two-photon Shack-Hartmann wavefront sensor.

PubMed

Xia, Fei; Sinefeld, David; Li, Bo; Xu, Chris

2017-03-15

We introduce a simple wavefront sensing scheme for aberration measurement of pulsed laser beams in near-infrared wavelengths (<2200  nm), where detectors are not always available or are very expensive. The method is based on two-photon absorption in a silicon detector array for longer wavelengths detection. We demonstrate the simplicity of such implementations with a commercially available Shack-Hartmann wavefront sensor and discuss the detection sensitivity of this method.

Temperature dependent characteristics of the random telegraph noise on contact resistive random access memory

NASA Astrophysics Data System (ADS)

Chang, Liang-Shun; Lin, Chrong Jung; King, Ya-Chin

2014-01-01

The temperature dependent characteristics of the random telegraphic noise (RTN) on contact resistive random access memory (CRRAM) are studied in this work. In addition to the bi-level switching, the occurrences of the middle states in the RTN signal are investigated. Based on the unique its temperature dependent characteristics, a new temperature sensing scheme is proposed for applications in ultra-low power sensor modules.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

Molecular dispersion spectroscopy for chemical sensing using chirped mid-infrared quantum cascade laser.

PubMed

Wysocki, Gerard; Weidmann, Damien

2010-12-06

A spectroscopic method of molecular detection based on dispersion measurements using a frequency-chirped laser source is presented. An infrared quantum cascade laser emitting around 1912 cm(-1) is used as a tunable spectroscopic source to measure dispersion that occurs in the vicinity of molecular ro-vibrational transitions. The sample under study is a mixture of nitric oxide in dry nitrogen. Two experimental configurations based on a coherent detection scheme are investigated and discussed. The theoretical models, which describe the observed spectral signals, are developed and verified experimentally. The method is particularly relevant to optical sensing based on mid-infrared quantum cascade lasers as the high chirp rates available with those sources can significantly enhance the magnitude of the measured dispersion signals. The method relies on heterodyne beatnote frequency measurements and shows high immunity to variations in the optical power received by the photodetector.

High precision position sensor based on CPA in a composite multi-layered system.

PubMed

Dey, Sanjeeb; Singh, Suneel; Rao, Desai Narayana

2018-04-16

We propose a scheme for high precision position sensing based on coherent perfect absorption (CPA) in a five-layered structure comprising three layers of metal-dielectric composites and two spacer (air) layers. Both the outermost interfaces of the five layered medium are irradiated by two identical coherent light waves at the same angle of incidence. We first investigate the occurrence of CPA in a symmetric layered structure as a function of different system parameters for oblique incidence. Thereafter, by shifting the middle layer, beginning from one end of the structure to the other, we observe the periodic occurrence of extremely narrow CPA resonances at several positions of the middle layer. Moreover this phenomenon is seen to recur even at many other wavelengths. We discuss how the position sensitivity of this phenomenon can be utilized for designing a CPA based high precision position sensing device.

CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

NASA Astrophysics Data System (ADS)

Kuai, Xiao-yan; Sun, Hai-xin; Qi, Jie; Cheng, En; Xu, Xiao-ka; Guo, Yu-hui; Chen, You-gan

2014-06-01

In this paper, we investigate the performance of adaptive modulation (AM) orthogonal frequency division multiplexing (OFDM) system in underwater acoustic (UWA) communications. The aim is to solve the problem of large feedback overhead for channel state information (CSI) in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing (CS). We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate (BER) and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying (QPSK) modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform (DCT) method.

Robust Kalman filtering cooperated Elman neural network learning for vision-sensing-based robotic manipulation with global stability.

PubMed

Zhong, Xungao; Zhong, Xunyu; Peng, Xiafu

2013-10-08

In this paper, a global-state-space visual servoing scheme is proposed for uncalibrated model-independent robotic manipulation. The scheme is based on robust Kalman filtering (KF), in conjunction with Elman neural network (ENN) learning techniques. The global map relationship between the vision space and the robotic workspace is learned using an ENN. This learned mapping is shown to be an approximate estimate of the Jacobian in global space. In the testing phase, the desired Jacobian is arrived at using a robust KF to improve the ENN learning result so as to achieve robotic precise convergence of the desired pose. Meanwhile, the ENN weights are updated (re-trained) using a new input-output data pair vector (obtained from the KF cycle) to ensure robot global stability manipulation. Thus, our method, without requiring either camera or model parameters, avoids the corrupted performances caused by camera calibration and modeling errors. To demonstrate the proposed scheme's performance, various simulation and experimental results have been presented using a six-degree-of-freedom robotic manipulator with eye-in-hand configurations.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

PubMed

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Adaptive Multi-Node Multiple Input and Multiple Output (MIMO) Transmission for Mobile Wireless Multimedia Sensor Networks

PubMed Central

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-01-01

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920

On event-based optical flow detection

PubMed Central

Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

2015-01-01

Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

PubMed Central

Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

2009-01-01

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

Study and simulation of low rate video coding schemes

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Chen, Yun-Chung; Kipp, G.

1992-01-01

The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design.

Ultrahigh-sensitive multimode interference-based fiber optic liquid-level sensor realized using illuminating zero-order Bessel-Gauss beam

NASA Astrophysics Data System (ADS)

Saha, Ardhendu; Datta, Arijit; Kaman, Surjit

2018-03-01

A proposal toward the enhancement in the sensitivity of a multimode interference-based fiber optic liquid-level sensor is explored analytically using a zero-order Bessel-Gauss (BG) beam as the input source. The sensor head consists of a suitable length of no-core fiber (NCF) sandwiched between two specialty high-order mode fibers. The coupling efficiency of various order modes inside the sensor structure is assessed using guided-mode propagation analysis and the performance of the proposed sensor has been benchmarked against the conventional sensor using a Gaussian beam. Furthermore, the study has been corroborated using a finite-difference beam propagation method in Lumerical's Mode Solutions software to investigate the propagation of the zero-order BG beam inside the sensor structure. Based on the simulation outcomes, the proposed scheme yields a maximum absolute sensitivity of up to 3.551 dB / mm and a sensing resolution of 2.816 × 10 - 3 mm through the choice of an appropriate length of NCF at an operating wavelength of 1.55 μm. Owing to this superior sensing performance, the reported sensing technology expedites an avenue to devise a high-performance fiber optic-level sensor that finds profound implication in different physical, biological, and chemical sensing purposes.

Value-Based Caching in Information-Centric Wireless Body Area Networks

PubMed Central

Al-Turjman, Fadi M.; Imran, Muhammad; Vasilakos, Athanasios V.

2017-01-01

We propose a resilient cache replacement approach based on a Value of sensed Information (VoI) policy. To resolve and fetch content when the origin is not available due to isolated in-network nodes (fragmentation) and harsh operational conditions, we exploit a content caching approach. Our approach depends on four functional parameters in sensory Wireless Body Area Networks (WBANs). These four parameters are: age of data based on periodic request, popularity of on-demand requests, communication interference cost, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These parameters are considered together to assign a value to the cached data to retain the most valuable information in the cache for prolonged time periods. The higher the value, the longer the duration for which the data will be retained in the cache. This caching strategy provides significant availability for most valuable and difficult to retrieve data in the WBANs. Extensive simulations are performed to compare the proposed scheme against other significant caching schemes in the literature while varying critical aspects in WBANs (e.g., data popularity, cache size, publisher load, connectivity-degree, and severe probabilities of node failures). These simulation results indicate that the proposed VoI-based approach is a valid tool for the retrieval of cached content in disruptive and challenging scenarios, such as the one experienced in WBANs, since it allows the retrieval of content for a long period even while experiencing severe in-network node failures. PMID:28106817

Fluorescent biosensor for the detection of hyaluronidase: intensity-based ratiometric sensing and fluorescence lifetime-based sensing using a long lifetime azadioxatriangulenium (ADOTA) fluorophore.

PubMed

Chib, Rahul; Mummert, Mark; Bora, Ilkay; Laursen, Bo W; Shah, Sunil; Pendry, Robert; Gryczynski, Ignacy; Borejdo, Julian; Gryczynski, Zygmunt; Fudala, Rafal

2016-05-01

In this report, we have designed a rapid and sensitive, intensity-based ratiometric sensing as well as lifetime-based sensing probe for the detection of hyaluronidase activity. Hyaluronidase expression is known to be upregulated in various pathological conditions. We have developed a fluorescent probe by heavy labeling of hyaluronic acid with a new orange/red-emitting organic azadioxatriangulenium (ADOTA) fluorophore, which exhibits a long fluorescence lifetime (∼20 ns). The ADOTA fluorophore in water has a peak fluorescence lifetime of ∼20 ns and emission spectra centered at 560 nm. The heavily ADOTA-labeled hyaluronic acid (HA-ADOTA) shows a red shift in the peak emission wavelength (605 nm), a weak fluorescence signal, and a shorter fluorescence lifetime (∼4 ns) due to efficient self-quenching and formation of aggregates. In the presence of hyaluronidase, the brightness and fluorescence lifetime of the sample increase with a blue shift in the peak emission to its original wavelength at 560 nm. The ratio of the fluorescence intensity of the HA-ADOTA probe at 560 and 605 nm can be used as the sensing method for the detection of hyaluronidase. The cleavage of the hyaluronic acid macromolecule reduces the energy migration between ADOTA molecules, as well as the degree of self-quenching and aggregation. This probe can be efficiently used for both intensity-based ratiometric sensing as well as fluorescence lifetime-based sensing of hyaluronidase. The proposed method makes it a rapid and sensitive assay, useful for analyzing levels of hyaluronidase in relevant clinical samples like urine or plasma. Graphical Abstract Scheme showing cleavage of HA-ADOTA probe by hyaluronidase and the change in the emission spectrum of HA-ADOTA probe before and after cleavage by hyaluronidase.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

A modified JPEG-LS lossless compression method for remote sensing images

NASA Astrophysics Data System (ADS)

Deng, Lihua; Huang, Zhenghua

2015-12-01

As many variable length source coders, JPEG-LS is highly vulnerable to channel errors which occur in the transmission of remote sensing images. The error diffusion is one of the important factors which infect its robustness. The common method of improving the error resilience of JPEG-LS is dividing the image into many strips or blocks, and then coding each of them independently, but this method reduces the coding efficiency. In this paper, a block based JPEP-LS lossless compression method with an adaptive parameter is proposed. In the modified scheme, the threshold parameter RESET is adapted to an image and the compression efficiency is close to that of the conventional JPEG-LS.

Phase-shift detection in a Fourier-transform method for temperature sensing using a tapered fiber microknot resonator.

PubMed

Larocque, Hugo; Lu, Ping; Bao, Xiaoyi

2016-04-01

Phase-shift detection in a fast-Fourier-transform (FFT)-based spectrum analysis technique for temperature sensing using a tapered fiber microknot resonator is proposed and demonstrated. Multiple transmission peaks in the FFT spectrum of the device were identified as optical modes having completed different amounts of round trips within the ring structure. Temperature variation induced phase shifts for each set of peaks were characterized, and experimental results show that different peaks have distinct temperature sensitivities reaching values up to -0.542  rad/°C, which is about 10 times greater than that of a regular adiabatic taper Mach-Zehnder interferometer when using similar phase-tracking schemes.

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Development of optical micro resonance based sensor for detection and identification of microparticles and biological agents

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Schweiger, Gustav

2009-05-01

A novel emerging technique for the label-free analysis of nanoparticles including biomolecules using optical micro cavity resonance of whispering-gallery-type modes is being developed. Schemes of such a method based on microsphere melted by laser on the tip of a standard single mode fiber optical cable with a laser and free microsphere matrix have been developed. Using a calibration principal of ultra high resolution spectroscopy based on such a scheme the method is being transformed to make further development for microbial application. The sensitivity of developed schemes has been tested to refractive index changes by monitoring the magnitude of the whispering gallery modes spectral shift. Water solutions of ethanol, glucose, vitamin C and biotin have been used. Some other schemes using similar principals: stand-alone, array and matrix microsphere resonators, liquid core optical ring resonators are also being under development. The influences of the gap in whispering-gallery modes on energy coupling, resonance quality and frequency have been investigated. An optimum gap for sensing applications has been defined at the half maximum energy coupling where both the Q factor and coupling efficiency are high and the resonance frequency is little affected by the gap variation. Developed schemes have been demonstrated to be a promising technology platform for sensitive, lab-on-chip type sensor which can be used for development of diagnostic tools for different biological molecules, e.g. proteins, oligonucleotides, oligosaccharides, lipids, small molecules, viral particles, cells as well as in different experimental contexts e.g. proteomics, genomics, drug discovery, and membrane studies.

Proposal for a broadband THz refractive-index sensor based on quantum-cascade laser arrays.

PubMed

Zhao, Le; Khanal, Sudeep; Wu, Chongzhao; Kumar, Sushil

2015-02-23

Many molecules have strong and characteristic rotational and vibrational transitions at terahertz (THz) frequencies, which makes this frequency range unique for applications in spectroscopic sensing of chemical and biological species. Here, we propose a broadband THz sensor based on arrays of single-mode QCLs, which could be utilized for sensing of the refractive-index of solids or liquids in reflection geometry. The proposed scheme does not require expensive THz detectors and consists of no movable parts. A recently developed antenna-feedback geometry is utilized to enhance optical coupling between two single-mode QCLs, which facilitates optical downconversion of the THz frequency signal to microwave regime. Arrays of THz QCLs emitting at discrete frequencies could be utilized to provide more than 2 THz of spectral coverage to realize a broadband, low-cost, and portable THz sensor.

Issues in measure-preserving three dimensional flow integrators: Self-adjointness, reversibility, and non-uniform time stepping

DOE PAGES

Finn, John M.

2015-03-01

Properties of integration schemes for solenoidal fields in three dimensions are studied, with a focus on integrating magnetic field lines in a plasma using adaptive time stepping. It is shown that implicit midpoint (IM) and a scheme we call three-dimensional leapfrog (LF) can do a good job (in the sense of preserving KAM tori) of integrating fields that are reversible, or (for LF) have a 'special divergence-free' property. We review the notion of a self-adjoint scheme, showing that such schemes are at least second order accurate and can always be formed by composing an arbitrary scheme with its adjoint. Wemore » also review the concept of reversibility, showing that a reversible but not exactly volume-preserving scheme can lead to a fractal invariant measure in a chaotic region, although this property may not often be observable. We also show numerical results indicating that the IM and LF schemes can fail to preserve KAM tori when the reversibility property (and the SDF property for LF) of the field is broken. We discuss extensions to measure preserving flows, the integration of magnetic field lines in a plasma and the integration of rays for several plasma waves. The main new result of this paper relates to non-uniform time stepping for volume-preserving flows. We investigate two potential schemes, both based on the general method of Ref. [11], in which the flow is integrated in split time steps, each Hamiltonian in two dimensions. The first scheme is an extension of the method of extended phase space, a well-proven method of symplectic integration with non-uniform time steps. This method is found not to work, and an explanation is given. The second method investigated is a method based on transformation to canonical variables for the two split-step Hamiltonian systems. This method, which is related to the method of non-canonical generating functions of Ref. [35], appears to work very well.« less

Galerkin finite element scheme for magnetostrictive structures and composites

NASA Astrophysics Data System (ADS)

Kannan, Kidambi Srinivasan

The ever increasing-role of magnetostrictives in actuation and sensing applications is an indication of their importance in the emerging field of smart structures technology. As newer, and more complex, applications are developed, there is a growing need for a reliable computational tool that can effectively address the magneto-mechanical interactions and other nonlinearities in these materials and in structures incorporating them. This thesis presents a continuum level quasi-static, three-dimensional finite element computational scheme for modeling the nonlinear behavior of bulk magnetostrictive materials and particulate magnetostrictive composites. Models for magnetostriction must deal with two sources of nonlinearities-nonlinear body forces/moments in equilibrium equations governing magneto-mechanical interactions in deformable and magnetized bodies; and nonlinear coupled magneto-mechanical constitutive models for the material of interest. In the present work, classical differential formulations for nonlinear magneto-mechanical interactions are recast in integral form using the weighted-residual method. A discretized finite element form is obtained by applying the Galerkin technique. The finite element formulation is based upon three dimensional eight-noded (isoparametric) brick element interpolation functions and magnetostatic infinite elements at the boundary. Two alternative possibilities are explored for establishing the nonlinear incremental constitutive model-characterization in terms of magnetic field or in terms of magnetization. The former methodology is the one most commonly used in the literature. In this work, a detailed comparative study of both methodologies is carried out. The computational scheme is validated, qualitatively and quantitatively, against experimental measurements published in the literature on structures incorporating the magnetostrictive material Terfenol-D. The influence of nonlinear body forces and body moments of magnetic origin, on the response of magnetostrictive structures to complex mechanical and magnetic loading conditions, is carefully examined. While monolithic magnetostrictive materials have been commercially-available since the late eighties, attention in the smart structures research community has recently focussed upon building and using magnetostrictive particulate composite structures for conventional actuation applications and novel sensing methodologies in structural health monitoring. A particulate magnetostrictive composite element has been developed in the present work to model such structures. This composite element incorporates interactions between magnetostrictive particles by combining a numerical micromechanical analysis based on magneto-mechanical Green's functions, with a homogenization scheme based upon the Mori-Tanaka approach. This element has been applied to the simulation of particulate actuators and sensors reported in the literature. Simulation results are compared to experimental data for validation purposes. The computational schemes developed, for bulk materials and for composites, are expected to be of great value to researchers and designers of novel applications based on magnetostrictives.

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

A distributed model predictive control scheme for leader-follower multi-agent systems

NASA Astrophysics Data System (ADS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2018-02-01

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader-follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the 'better' control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.

Distributed fiber-optic laser-ultrasound generation based on ghost-mode of tilted fiber Bragg gratings.

PubMed

Tian, Jiajun; Zhang, Qi; Han, Ming

2013-03-11

Active ultrasonic testing is widely used for medical diagnosis, material characterization and structural health monitoring. Ultrasonic transducer is a key component in active ultrasonic testing. Due to their many advantages such as small size, light weight, and immunity to electromagnetic interference, fiber-optic ultrasonic transducers are particularly attractive for permanent, embedded applications in active ultrasonic testing for structural health monitoring. However, current fiber-optic transducers only allow effective ultrasound generation at a single location of the fiber end. Here we demonstrate a fiber-optic device that can effectively generate ultrasound at multiple, selected locations along a fiber in a controllable manner based on a smart light tapping scheme that only taps out the light of a particular wavelength for laser-ultrasound generation and allow light of longer wavelengths pass by without loss. Such a scheme may also find applications in remote fiber-optic device tuning and quasi-distributed biochemical fiber-optic sensing.

Considerations on fundamental issues in establishing a universal coverage system for health in China.

PubMed

Lei, Hai Chao

2008-11-01

This study discusses basic health services in China. In this study common sense and international experience in establishing a high-performing health system were introduced. Five components are identified: basic qualified human resources for health; basic infrastructure; essential medicines; essential technology and procedures; and basic service pathways. Recommendations were presented based upon the Chinese situation. They are: increase public financing and lower private out-of-pocket payment for services; revitalize the functions of public facilities; merge different health financing schemes; co-ordinate public fiscal and pricing policies; prioritize public financing to preventive and primary healthcare; establish and strengthen the partnership between public and private facilities and insurance schemes; and re-organize the administrative system in health-based upon the rules of simplicity, unity, and efficiency. © 2008 Blackwell Publishing Asia Pty Ltd and Chinese Cochrane Center, West China Hospital of Sichuan University.

Mobile devices for community-based REDD+ monitoring: a case study for Central Vietnam.

PubMed

Pratihast, Arun Kumar; Herold, Martin; Avitabile, Valerio; de Bruin, Sytze; Bartholomeus, Harm; Souza, Carlos M; Ribbe, Lars

2012-12-20

Monitoring tropical deforestation and forest degradation is one of the central elements for the Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD+) scheme. Current arrangements for monitoring are based on remote sensing and field measurements. Since monitoring is the periodic process of assessing forest stands properties with respect to reference data, adopting the current REDD+ requirements for implementing monitoring at national levels is a challenging task. Recently, the advancement in Information and Communications Technologies (ICT) and mobile devices has enabled local communities to monitor their forest in a basic resource setting such as no or slow internet connection link, limited power supply, etc. Despite the potential, the use of mobile device system for community based monitoring (CBM) is still exceptional and faces implementation challenges. This paper presents an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. This paper also assesses the accuracy and reliability of CBM data and proposes a way to fit them into national REDD+ Monitoring, Reporting and Verification (MRV) scheme. The system performance is evaluated at Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were tracked. The results show that the local community is able to provide data with accuracy comparable to expert measurements (index of agreement greater than 0.88), but against lower costs. Furthermore, the results confirm that communities are more effective to monitor small scale forest degradation due to subsistence fuel wood collection and selective logging, than high resolution remote sensing SPOT imagery.

Mobile Devices for Community-Based REDD+ Monitoring: A Case Study for Central Vietnam

PubMed Central

Pratihast, Arun Kumar; Herold, Martin; Avitabile, Valerio; de Bruin, Sytze; Bartholomeus, Harm; Souza, Carlos M.; Ribbe, Lars

2013-01-01

Monitoring tropical deforestation and forest degradation is one of the central elements for the Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD+) scheme. Current arrangements for monitoring are based on remote sensing and field measurements. Since monitoring is the periodic process of assessing forest stands properties with respect to reference data, adopting the current REDD+ requirements for implementing monitoring at national levels is a challenging task. Recently, the advancement in Information and Communications Technologies (ICT) and mobile devices has enabled local communities to monitor their forest in a basic resource setting such as no or slow internet connection link, limited power supply, etc. Despite the potential, the use of mobile device system for community based monitoring (CBM) is still exceptional and faces implementation challenges. This paper presents an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. This paper also assesses the accuracy and reliability of CBM data and proposes a way to fit them into national REDD+ Monitoring, Reporting and Verification (MRV) scheme. The system performance is evaluated at Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were tracked. The results show that the local community is able to provide data with accuracy comparable to expert measurements (index of agreement greater than 0.88), but against lower costs. Furthermore, the results confirm that communities are more effective to monitor small scale forest degradation due to subsistence fuel wood collection and selective logging, than high resolution remote sensing SPOT imagery. PMID:23344371

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three Justifications for Effectively Teaching Exceptional Babies to Third Grade with Respect to Their Characteristics, an Effective Curricula, and an Exceptional-Research Data Base

ERIC Educational Resources Information Center

Jaramillo, James Anthony Montrose

2013-01-01

Both Pre-K and K-3rd grade exceptional or talented children/students not only want but need more of an "accommodative" ambiance where their senses are given novel multiple-intelligences data so that they can continue to intellectually grow with respect to Piaget, Erickson, and Vygotsky's developmental schemes. Thus, to do this requires us to…

Restoration of Wavelet-Compressed Images and Motion Imagery

DTIC Science & Technology

2004-01-01

SECURITY CLASSIFICATION OF REPORT UNCLASSIFIED 18. SECURITY CLASSIFICATION OF THIS PAGE UNCLASSIFIED 19. SECURITY CLASSIFICATION...images is that they are global translates of each other, where 29 the global motion parameters are known. In a very simple sense , these five images form...Image Proc., vol. 1, Oct. 2001, pp. 185–188. [2] J. W. Woods and T. Naveen, “A filter based bit allocation scheme for subband compresion of HDTV,” IEEE

Multi-source and multi-angle remote sensing image data collection, application and sharing of Beichuan National Earthquake Ruins Museum

NASA Astrophysics Data System (ADS)

Lin, Yueguan; Wang, Wei; Wen, Qi; Huang, He; Lin, Jingli; Zhang, Wei

2015-12-01

Ms8.0 Wenchuan earthquake that occurred on May 12, 2008 brought huge casualties and property losses to the Chinese people, and Beichuan County was destroyed in the earthquake. In order to leave a site for commemorate of the people, and for science propaganda and research of earthquake science, Beichuan National Earthquake Ruins Museum has been built on the ruins of Beichuan county. Based on the demand for digital preservation of the earthquake ruins park and collection of earthquake damage assessment of research and data needs, we set up a data set of Beichuan National Earthquake Ruins Museum, including satellite remote sensing image, airborne remote sensing image, ground photogrammetry data and ground acquisition data. At the same time, in order to make a better service for earthquake science research, we design the sharing ideas and schemes for this scientific data set.

Comparison of sensor structures for the signal amplification of surface plasmon resonance immunoassay using enzyme precipitation

NASA Astrophysics Data System (ADS)

Yang, Chih-Tsung; Thierry, Benjamin

2015-12-01

Surface plasmon resonance (SPR) biosensing has been successfully applied for the label-free detection of a broad range of bioanalytes ranging from bacteria, cell, exosome, protein and nucleic acids. When it comes to the detection of small molecules or analytes found at low concentration, amplification schemes are desirable to enhance binding signals and in turn increase sensitivity. A number of SPR signal amplification schemes have been developed and validated; however, little effort has been devoted to understanding the effect of the SPR sensor structures on the amplification of binding signals and therefore on the overall sensing performance. The physical phenomenon of long-range SPR (LRSPR) relies on the propagation of coupled surface plasmonic waves on the opposite sides of a nanoscale-thick noble metal film suspended between two dielectrics with similar refractive indices. Importantly, as compared with commonly used conventional SPR (cSPR), LRSPR is not only characterized by a longer penetration depth of the plasmonic waves in the analyzed medium but also by a greater sensitivity to bulk refractive index changes. In this work, an immunoassay signal amplification platform based on horseradish peroxidase (HRP) catalyzed precipitation was utilized to investigate the sensing performance with regards to cSPR and LRSPR. The enzymatic precipitation of 3, 3'-diaminobenzidine tetrahydrochloride (DAB)/H2O2 was used to amplify SPR signals. The structure-function relationship of cSPR and LRSPR sensors is presented for both standard refractometric measurements and the enzymatic precipitation scheme. Experimental data shows that despite its inherent higher sensitivity to bulk refractive index changes and higher figure of merit, LRSPR was characterized by a lower angular sensitivity in the model enzymatic amplification scheme used here.

Generalized interpretation scheme for arbitrary HR InSAR image pairs

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten

2013-10-01

Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status

NASA Astrophysics Data System (ADS)

Schmidt, Johannes; Fassnacht, Fabian Ewald; Neff, Christophe; Lausch, Angela; Kleinschmit, Birgit; Förster, Michael; Schmidtlein, Sebastian

2017-08-01

Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing. Hence, the transfer of field guidelines to remote sensing indicators was rather successful in this case but needs further evaluation for other habitats.

Molecular sensing with magnetic nanoparticles using magnetic spectroscopy of nanoparticle Brownian motion.

PubMed

Zhang, Xiaojuan; Reeves, Daniel B; Perreard, Irina M; Kett, Warren C; Griswold, Karl E; Gimi, Barjor; Weaver, John B

2013-12-15

Functionalized magnetic nanoparticles (mNPs) have shown promise in biosensing and other biomedical applications. Here we use functionalized mNPs to develop a highly sensitive, versatile sensing strategy required in practical biological assays and potentially in vivo analysis. We demonstrate a new sensing scheme based on magnetic spectroscopy of nanoparticle Brownian motion (MSB) to quantitatively detect molecular targets. MSB uses the harmonics of oscillating mNPs as a metric for the freedom of rotational motion, thus reflecting the bound state of the mNP. The harmonics can be detected in vivo from nanogram quantities of iron within 5s. Using a streptavidin-biotin binding system, we show that the detection limit of the current MSB technique is lower than 150 pM (0.075 pmole), which is much more sensitive than previously reported techniques based on mNP detection. Using mNPs conjugated with two anti-thrombin DNA aptamers, we show that thrombin can be detected with high sensitivity (4 nM or 2 pmole). A DNA-DNA interaction was also investigated. The results demonstrated that sequence selective DNA detection can be achieved with 100 pM (0.05 pmole) sensitivity. The results of using MSB to sense these interactions, show that the MSB based sensing technique can achieve rapid measurement (within 10s), and is suitable for detecting and quantifying a wide range of biomarkers or analytes. It has the potential to be applied in variety of biomedical applications or diagnostic analyses. © 2013 Elsevier B.V. All rights reserved.

Strain Wave Acquisition by a Fiber Optic Coherent Sensor for Impact Monitoring

PubMed Central

Sbarufatti, Claudio; Beligni, Alessio; Gilioli, Andrea; Ferrario, Maddalena; Mattarei, Marco; Martinelli, Mario; Giglio, Marco

2017-01-01

A novel fiber optic sensing technology for high frequency dynamics detection is proposed in this paper, specifically tailored for structural health monitoring applications based on strain wave analysis, for both passive impact identification and active Lamb wave monitoring. The sensing solution relies on a fiber optic-based interferometric architecture associated to an innovative coherent detection scheme, which retrieves in a completely passive way the high-frequency phase information of the received optical signal. The sensing fiber can be arranged into different layouts, depending on the requirement of the specific application, in order to enhance the sensor sensitivity while still ensuring a limited gauge length if punctual measures are required. For active Lamb wave monitoring, this results in a sensing fiber arranged in multiple loops glued on an aluminum thin panel in order to increase the phase signal only in correspondence to the sensing points of interest. Instead, for passive impact identification, the required sensitivity is guaranteed by simply exploiting a longer gauge length glued to the structure. The fiber optic coherent (FOC) sensor is exploited to detect the strain waves emitted by a piezoelectric transducer placed on the aluminum panel or generated by an impulse hammer, respectively. The FOC sensor measurements have been compared with both a numerical model based on Finite Elements and traditional piezoelectric sensors, confirming a good agreement between experimental and simulated results for both active and passive impact monitoring scenarios. PMID:28773154

Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks

PubMed Central

Yoon, Ikjune; Kim, Hyeok; Noh, Dong Kun

2017-01-01

A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically determines its energy budget, which takes into account its residual energy, and its likely acquisition and consumption. If it expects to acquire more energy than it can store, the data which has it has sensed is aggregated with data from other nodes, compressed, and transmitted. Otherwise, the node continues to sense data, but turns off its wireless communication to reduce energy consumption. We compared several schemes by simulation. Our scheme reduced the number of nodes forced to black out due to lack of energy so that more data arrives at the sink node. PMID:28555010

Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks.

PubMed

Yoon, Ikjune; Kim, Hyeok; Noh, Dong Kun

2017-05-27

A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically determines its energy budget, which takes into account its residual energy, and its likely acquisition and consumption. If it expects to acquire more energy than it can store, the data which has it has sensed is aggregated with data from other nodes, compressed, and transmitted. Otherwise, the node continues to sense data, but turns off its wireless communication to reduce energy consumption. We compared several schemes by simulation. Our scheme reduced the number of nodes forced to black out due to lack of energy so that more data arrives at the sink node.

Novel electrochemical sensing platform for ultrasensitive detection of cardiac troponin I based on aptamer-MoS2 nanoconjugates.

PubMed

Qiao, Xiujuan; Li, Kunxia; Xu, Jinqiong; Cheng, Ni; Sheng, Qinglin; Cao, Wei; Yue, Tianli; Zheng, Jianbin

2018-08-15

Cardiac troponin I (cTnI) is a specific and sensitive biomarker for the early diagnosis of acute myocardial infarction and for the subsequent clinical treatments. In this work, novel electrochemical sensing platform for sensing of cTnI based on aptamer-MoS 2 nanoconjugates was proposed. For comparison, core-shell Au@SiO 2 @Au nanoparticles were also used for sensing of cTnI. The sensing schemes and electrochemical responses of the proposed sensors were investigated by electrochemical impedance spectroscopy (EIS) in 5.0 mM K 3 [Fe(CN) 6 ]/K 4 [Fe(CN) 6 ] (1:1) solution containing 0.1 M KCl, respectively. Results showed that the aptamer-Au@SiO 2 @Au based aptasensor shows a linear rage of 10 pM-10.0 μM with the detection limits of 1.23 pM For the aptamer-MoS 2 nanosheets based aptasensor, the linear range for cTnI detection was from 10 pM to 1.0 μM with a lower detection limit of 0.95 pM Meanwhile, both the sensors were successfully applied for detection of cTnI in human blood samples. The two kinds of aptsensors have been successfully used for detecting of cTnI in human blood serums. Moreover, no negligible signal changes could be observed in the presence of non-targets of CK-MB and Myo, suggesting the good potential for clinic diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Multichannel blind iterative image restoration.

PubMed

Sroubek, Filip; Flusser, Jan

2003-01-01

Blind image deconvolution is required in many applications of microscopy imaging, remote sensing, and astronomical imaging. Unfortunately in a single-channel framework, serious conceptual and numerical problems are often encountered. Very recently, an eigenvector-based method (EVAM) was proposed for a multichannel framework which determines perfectly convolution masks in a noise-free environment if channel disparity, called co-primeness, is satisfied. We propose a novel iterative algorithm based on recent anisotropic denoising techniques of total variation and a Mumford-Shah functional with the EVAM restoration condition included. A linearization scheme of half-quadratic regularization together with a cell-centered finite difference discretization scheme is used in the algorithm and provides a unified approach to the solution of total variation or Mumford-Shah. The algorithm performs well even on very noisy images and does not require an exact estimation of mask orders. We demonstrate capabilities of the algorithm on synthetic data. Finally, the algorithm is applied to defocused images taken with a digital camera and to data from astronomical ground-based observations of the Sun.

Proceedings of the International Conference on Stiff Computation, April 12-14, 1982, Park City, Utah. Volume II.

DTIC Science & Technology

1982-01-01

concepts. Fatunla (1981) proposed symmetric hybrid schemes well suited to periodic initial value problems. A generalization of this idea is proposed...one time step to another was kept below a prescribed value. Obviously this limits the truncation error only in some vague, general sense. The schemes ...STIFFLY STABLE LINEAR MULTISTEP METHODS. S.O. FATUNLA, Trinity College, Dublin: P-STABLE HYBRID SCHEMES FOR INITIAL VALUE PROBLEMS APRIL 13, 1982 G

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

NASA Technical Reports Server (NTRS)

Kovalskyy, V.; Henebry, G. M.; Adusei, B.; Hansen, M.; Roy, D. P.; Senay, G.; Mocko, D. M.

2011-01-01

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Bioanalytical and chemical sensors using living taste, olfactory, and neural cells and tissues: a short review.

PubMed

Wu, Chunsheng; Lillehoj, Peter B; Wang, Ping

2015-11-07

Biosensors utilizing living tissues and cells have recently gained significant attention as functional devices for chemical sensing and biochemical analysis. These devices integrate biological components (i.e. single cells, cell networks, tissues) with micro-electro-mechanical systems (MEMS)-based sensors and transducers. Various types of cells and tissues derived from natural and bioengineered sources have been used as recognition and sensing elements, which are generally characterized by high sensitivity and specificity. This review summarizes the state of the art in tissue- and cell-based biosensing platforms with an emphasis on those using taste, olfactory, and neural cells and tissues. Many of these devices employ unique integration strategies and sensing schemes based on sensitive transducers including microelectrode arrays (MEAs), field effect transistors (FETs), and light-addressable potentiometric sensors (LAPSs). Several groups have coupled these hybrid biosensors with microfluidics which offers added benefits of small sample volumes and enhanced automation. While this technology is currently limited to lab settings due to the limited stability of living biological components, further research to enhance their robustness will enable these devices to be employed in field and clinical settings.

Integrated quantum photonic sensor based on Hong-Ou-Mandel interference.

PubMed

Basiri-Esfahani, Sahar; Myers, Casey R; Armin, Ardalan; Combes, Joshua; Milburn, Gerard J

2015-06-15

Photonic-crystal-based integrated optical systems have been used for a broad range of sensing applications with great success. This has been motivated by several advantages such as high sensitivity, miniaturization, remote sensing, selectivity and stability. Many photonic crystal sensors have been proposed with various fabrication designs that result in improved optical properties. In parallel, integrated optical systems are being pursued as a platform for photonic quantum information processing using linear optics and Fock states. Here we propose a novel integrated Fock state optical sensor architecture that can be used for force, refractive index and possibly local temperature detection. In this scheme, two coupled cavities behave as an "effective beam splitter". The sensor works based on fourth order interference (the Hong-Ou-Mandel effect) and requires a sequence of single photon pulses and consequently has low pulse power. Changes in the parameter to be measured induce variations in the effective beam splitter reflectivity and result in changes to the visibility of interference. We demonstrate this generic scheme in coupled L3 photonic crystal cavities as an example and find that this system, which only relies on photon coincidence detection and does not need any spectral resolution, can estimate forces as small as 10(-7) Newtons and can measure one part per million change in refractive index using a very low input power of 10(-10)W. Thus linear optical quantum photonic architectures can achieve comparable sensor performance to semiclassical devices.

DRDT: distributed and reliable data transmission with cooperative nodes for lossy wireless sensor networks.

PubMed

Seo, Jaewan; Kim, Moonseong; Hur, In; Choi, Wook; Choo, Hyunseung

2010-01-01

Recent studies have shown that in realistic wireless sensor network environments links are extremely unreliable. To recover from corrupted packets, most routing schemes with an assumption of ideal radio environments use a retransmission mechanism, which may cause unnecessary retransmissions. Therefore, guaranteeing energy-efficient reliable data transmission is a fundamental routing issue in wireless sensor networks. However, it is not encouraged to propose a new reliable routing scheme in the sense that every existing routing scheme cannot be replaced with the new one. This paper proposes a Distributed and Reliable Data Transmission (DRDT) scheme with a goal to efficiently guarantee reliable data transmission. In particular, this is based on a pluggable modular approach so that it can be extended to existing routing schemes. DRDT offers reliable data transmission using neighbor nodes, i.e., helper nodes. A helper node is selected among the neighbor nodes of the receiver node which overhear the data packet in a distributed manner. DRDT effectively reduces the number of retransmissions by delegating the retransmission task from the sender node to the helper node that has higher link quality to the receiver node when the data packet reception fails due to the low link quality between the sender and the receiver nodes. Comprehensive simulation results show that DRDT improves end-to-end transmission cost by up to about 45% and reduces its delay by about 40% compared to existing schemes.

Distributed dynamic strain measurement using long-gauge FBG and DTR3 interrogator based on delayed transmission/reflection ratiometric reflectometry

NASA Astrophysics Data System (ADS)

Nishiyama, M.; Igawa, H.; Kasai, T.; Watanabe, N.

2013-09-01

In this paper, we reveal characteristics of static and dynamic distributed strain measurement using a long-gauge fiber Bragg grating (FBG) and a Delayed Transmission/Reflection Ratiometric Reflectometry (DTR3) scheme. The DTR3 scheme has capability of detecting distributed strain using the long-gauge FBG with 50-cm spatial resolution. Additionally, dynamic strain measurement can be achieved using this technique in 100-Hz sampling rate. We evaluated strain sensing characteristics of the long-gauge FBG attached on 2.5-m aluminum bar by a four-point bending equipment. Experimental results showed that the DTR3 using the long-gauge FBG could detect distributed strain in static tests and resonance frequency of structure in free vibration tests. As a result, it is suggested that the DTR3 scheme using the longgauge FBG is attractive to structural health monitoring (SHM) as dynamic deformation detection of a few and tensmeters structure such as the airplane wing and the helicopter blade.

Symmetry-breaking inelastic wave-mixing atomic magnetometry.

PubMed

Zhou, Feng; Zhu, Chengjie J; Hagley, Edward W; Deng, Lu

2017-12-01

The nonlinear magneto-optical rotation (NMOR) effect has prolific applications ranging from precision mapping of Earth's magnetic field to biomagnetic sensing. Studies on collisional spin relaxation effects have led to ultrahigh magnetic field sensitivities using a single-beam Λ scheme with state-of-the-art magnetic shielding/compensation techniques. However, the NMOR effect in this widely used single-beam Λ scheme is peculiarly small, requiring complex radio-frequency phase-locking protocols. We show the presence of a previously unknown energy symmetry-based nonlinear propagation blockade and demonstrate an optical inelastic wave-mixing NMOR technique that breaks this NMOR blockade, resulting in an NMOR optical signal-to-noise ratio (SNR) enhancement of more than two orders of magnitude never before seen with the single-beam Λ scheme. The large SNR enhancement was achieved simultaneously with a nearly two orders of magnitude reduction in laser power while preserving the magnetic resonance linewidth. This new method may open a myriad of applications ranging from biomagnetic imaging to precision measurement of the magnetic properties of subatomic particles.

Symmetry-breaking inelastic wave-mixing atomic magnetometry

PubMed Central

Zhou, Feng; Zhu, Chengjie J.; Hagley, Edward W.; Deng, Lu

2017-01-01

The nonlinear magneto-optical rotation (NMOR) effect has prolific applications ranging from precision mapping of Earth’s magnetic field to biomagnetic sensing. Studies on collisional spin relaxation effects have led to ultrahigh magnetic field sensitivities using a single-beam Λ scheme with state-of-the-art magnetic shielding/compensation techniques. However, the NMOR effect in this widely used single-beam Λ scheme is peculiarly small, requiring complex radio-frequency phase-locking protocols. We show the presence of a previously unknown energy symmetry–based nonlinear propagation blockade and demonstrate an optical inelastic wave-mixing NMOR technique that breaks this NMOR blockade, resulting in an NMOR optical signal-to-noise ratio (SNR) enhancement of more than two orders of magnitude never before seen with the single-beam Λ scheme. The large SNR enhancement was achieved simultaneously with a nearly two orders of magnitude reduction in laser power while preserving the magnetic resonance linewidth. This new method may open a myriad of applications ranging from biomagnetic imaging to precision measurement of the magnetic properties of subatomic particles. PMID:29214217

Measuring aberrations in the rat brain by coherence-gated wavefront sensing using a Linnik interferometer

PubMed Central

Wang, Jinyu; Léger, Jean-François; Binding, Jonas; Boccara, A. Claude; Gigan, Sylvain; Bourdieu, Laurent

2012-01-01

Aberrations limit the resolution, signal intensity and achievable imaging depth in microscopy. Coherence-gated wavefront sensing (CGWS) allows the fast measurement of aberrations in scattering samples and therefore the implementation of adaptive corrections. However, CGWS has been demonstrated so far only in weakly scattering samples. We designed a new CGWS scheme based on a Linnik interferometer and a SLED light source, which is able to compensate dispersion automatically and can be implemented on any microscope. In the highly scattering rat brain tissue, where multiply scattered photons falling within the temporal gate of the CGWS can no longer be neglected, we have measured known defocus and spherical aberrations up to a depth of 400 µm. PMID:23082292

Measuring aberrations in the rat brain by coherence-gated wavefront sensing using a Linnik interferometer.

PubMed

Wang, Jinyu; Léger, Jean-François; Binding, Jonas; Boccara, A Claude; Gigan, Sylvain; Bourdieu, Laurent

2012-10-01

Aberrations limit the resolution, signal intensity and achievable imaging depth in microscopy. Coherence-gated wavefront sensing (CGWS) allows the fast measurement of aberrations in scattering samples and therefore the implementation of adaptive corrections. However, CGWS has been demonstrated so far only in weakly scattering samples. We designed a new CGWS scheme based on a Linnik interferometer and a SLED light source, which is able to compensate dispersion automatically and can be implemented on any microscope. In the highly scattering rat brain tissue, where multiply scattered photons falling within the temporal gate of the CGWS can no longer be neglected, we have measured known defocus and spherical aberrations up to a depth of 400 µm.

CENet: A Cabinet Environmental Sensing Network

PubMed Central

Zhang, Zusheng; Yu, Fengqi; Chen, Liang; Cao, Guangmin

2010-01-01

For data center cooling and intelligent substation systems, real time cabinet environmental monitoring is a strong requirement. Monitoring data, such as temperature, humidity, and noise, is important for operators to manage the facilities in cabinets. We here propose a sensing network, called CENet, which is energy efficient and reliable for cabinet environmental monitoring. CENet achieves above 93% reliable data yield and sends fewer beacons compared to periodic beaconing. It does so through a data-aided routing protocol. In addition, based on B-MAC, we propose a scheduling scheme to increase the lifetime of the network by reducing unnecessary message snooping and channel listening, thus it is more energy efficient than B-MAC. The performance of CENet is evaluated by simulations and experiments. PMID:22205856

Dissipative quantum error correction and application to quantum sensing with trapped ions.

PubMed

Reiter, F; Sørensen, A S; Zoller, P; Muschik, C A

2017-11-28

Quantum-enhanced measurements hold the promise to improve high-precision sensing ranging from the definition of time standards to the determination of fundamental constants of nature. However, quantum sensors lose their sensitivity in the presence of noise. To protect them, the use of quantum error-correcting codes has been proposed. Trapped ions are an excellent technological platform for both quantum sensing and quantum error correction. Here we present a quantum error correction scheme that harnesses dissipation to stabilize a trapped-ion qubit. In our approach, always-on couplings to an engineered environment protect the qubit against spin-flips or phase-flips. Our dissipative error correction scheme operates in a continuous manner without the need to perform measurements or feedback operations. We show that the resulting enhanced coherence time translates into a significantly enhanced precision for quantum measurements. Our work constitutes a stepping stone towards the paradigm of self-correcting quantum information processing.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

PubMed Central

Yi, Meng; Chen, Qingkui; Xiong, Neal N.

2016-01-01

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate. PMID:27827878

Sensitivity Simulation of Compressed Sensing Based Electronic Warfare Receiver Using Orthogonal Matching Pursuit Algorithm

DTIC Science & Technology

2016-02-01

algorithm is used to process CS data. The insufficient nature of the sparcity of the signal adversely affects the signal detection probability for...with equal probability. The scheme was proposed [2] for image processing using single pixel camera, where the field of view was masked by a grid...modulation. The orthogonal matching pursuit (OMP) algorithm is used to process CS data. The insufficient nature of the sparcity of the signal

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

PubMed Central

Zhang, Jinhuan; Long, Jun; Zhang, Chengyuan; Zhao, Guihu

2017-01-01

Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction. PMID:28218668

Surface Profile and Stress Field Evaluation using Digital Gradient Sensing Method

DOE PAGES

Miao, C.; Sundaram, B. M.; Huang, L.; ...

2016-08-09

Shape and surface topography evaluation from measured orthogonal slope/gradient data is of considerable engineering significance since many full-field optical sensors and interferometers readily output accurate data of that kind. This has applications ranging from metrology of optical and electronic elements (lenses, silicon wafers, thin film coatings), surface profile estimation, wave front and shape reconstruction, to name a few. In this context, a new methodology for surface profile and stress field determination based on a recently introduced non-contact, full-field optical method called digital gradient sensing (DGS) capable of measuring small angular deflections of light rays coupled with a robust finite-difference-based least-squaresmore » integration (HFLI) scheme in the Southwell configuration is advanced here. The method is demonstrated by evaluating (a) surface profiles of mechanically warped silicon wafers and (b) stress gradients near growing cracks in planar phase objects.« less

Robust, Brillouin Active Embedded Fiber-Is-The-Sensor System in Smart Composite Structures

NASA Technical Reports Server (NTRS)

Yu, Chung

1996-01-01

Extensive review of our proposed sensing scheme, based mainly on the forward Guided Acoustic Wave Brillouin Scattering (GAWBS) with backward stimulated Brillouin scattering (sBs) as an auxiliary scheme for system fault tolerance has been completed during this project period. This preliminary study is conducted for a number of reasons. The most significant reasons lie in the essential capability of the system to measure temperature and pressure. These two measurands have been proposed to be sensed by sBs in our proposal. Temperature and pressure/strain are important measurands in structural monitoring, so that the effectiveness of sensing by sBs needs to be further examined. It has been pointed out initially that sBs shift will be dependent on temperature and pressure/strain simultaneously. The shift versus temperature or strain is linear. Now, the question is how can these two measurands be separated when sBs is used to sense an environment, in which both temperature and strain are changing simultaneously. Typical sBs shift plotted versus strain and varying temperature is shown in Fig. 1. As is clear, a fiber initially stressed will relax with rising temperature. This is verified by a displacement to the right with rising temperature of the sBs shift vs strain curves in the figure. A way to circumvent this ambiguity is by employing two fibers, one pre-stressed and the other is a free fiber. The latter will measure temperature and subtracting data in the latter fiber from those of the former will give us net strain readings. This is a laborious approach, since it involves the use of two identical fibers, and this is hard to accomplish, especially when many sensors are needed. Additional multiplexing of the data stream for data subtraction becomes a necessity.

FBG Interrogation Method with High Resolution and Response Speed Based on a Reflective-Matched FBG Scheme

PubMed Central

Cui, Jiwen; Hu, Yang; Feng, Kunpeng; Li, Junying; Tan, Jiubin

2015-01-01

In this paper, a high resolution and response speed interrogation method based on a reflective-matched Fiber Bragg Grating (FBG) scheme is investigated in detail. The nonlinear problem of the reflective-matched FBG sensing interrogation scheme is solved by establishing and optimizing the mathematical model. A mechanical adjustment to optimize the interrogation method by tuning the central wavelength of the reference FBG to improve the stability and anti-temperature perturbation performance is investigated. To satisfy the measurement requirements of optical and electric signal processing, a well- designed acquisition circuit board is prepared, and experiments on the performance of the interrogation method are carried out. The experimental results indicate that the optical power resolution of the acquisition circuit border is better than 8 pW, and the stability of the interrogation method with the mechanical adjustment can reach 0.06%. Moreover, the nonlinearity of the interrogation method is 3.3% in the measurable range of 60 pm; the influence of temperature is significantly reduced to 9.5%; the wavelength resolution and response speed can achieve values of 0.3 pm and 500 kHz, respectively. PMID:26184195

FBG Interrogation Method with High Resolution and Response Speed Based on a Reflective-Matched FBG Scheme.

PubMed

Cui, Jiwen; Hu, Yang; Feng, Kunpeng; Li, Junying; Tan, Jiubin

2015-07-08

In this paper, a high resolution and response speed interrogation method based on a reflective-matched Fiber Bragg Grating (FBG) scheme is investigated in detail. The nonlinear problem of the reflective-matched FBG sensing interrogation scheme is solved by establishing and optimizing the mathematical model. A mechanical adjustment to optimize the interrogation method by tuning the central wavelength of the reference FBG to improve the stability and anti-temperature perturbation performance is investigated. To satisfy the measurement requirements of optical and electric signal processing, a well- designed acquisition circuit board is prepared, and experiments on the performance of the interrogation method are carried out. The experimental results indicate that the optical power resolution of the acquisition circuit border is better than 8 pW, and the stability of the interrogation method with the mechanical adjustment can reach 0.06%. Moreover, the nonlinearity of the interrogation method is 3.3% in the measurable range of 60 pm; the influence of temperature is significantly reduced to 9.5%; the wavelength resolution and response speed can achieve values of 0.3 pm and 500 kHz, respectively.

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network

PubMed Central

You, Hongjian

2018-01-01

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach. PMID:29364194

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

PubMed

An, Quanzhi; Pan, Zongxu; You, Hongjian

2018-01-24

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

Coupling reconstruction and motion estimation for dynamic MRI through optical flow constraint

NASA Astrophysics Data System (ADS)

Zhao, Ningning; O'Connor, Daniel; Gu, Wenbo; Ruan, Dan; Basarab, Adrian; Sheng, Ke

2018-03-01

This paper addresses the problem of dynamic magnetic resonance image (DMRI) reconstruction and motion estimation jointly. Because of the inherent anatomical movements in DMRI acquisition, reconstruction of DMRI using motion estimation/compensation (ME/MC) has been explored under the compressed sensing (CS) scheme. In this paper, by embedding the intensity based optical flow (OF) constraint into the traditional CS scheme, we are able to couple the DMRI reconstruction and motion vector estimation. Moreover, the OF constraint is employed in a specific coarse resolution scale in order to reduce the computational complexity. The resulting optimization problem is then solved using a primal-dual algorithm due to its efficiency when dealing with nondifferentiable problems. Experiments on highly accelerated dynamic cardiac MRI with multiple receiver coils validate the performance of the proposed algorithm.

Sensing cocaine in saliva with infrared laser spectroscopy

NASA Astrophysics Data System (ADS)

Hans, Kerstin M.-C.; Müller, Matthias; Gianella, Michele; Wägli, Ph.; Sigrist, Markus W.

2013-02-01

Increasing numbers of accidents caused by drivers under the influence of drugs, raise drug tests to worldwide interest. We developed a one-step extraction technique for cocaine in saliva and analyzed reference samples with laser spectroscopy employing two different schemes. The first is based on attenuated total reflection (ATR), which is applied to dried samples. The second scheme uses transmission measurements for the analysis of liquid samples. ATR spectroscopy achieved a limit of detection (LOD) of 3μg/ml. The LOD for the transmission approach in liquid samples is < 10 μg/ml. These LODs are realistic as such concentration ranges are encountered in the saliva of drug users after the administration of a single dose of cocaine. An improved stabilization of the set-up should lower the limit of detection significantly.

Plasmonic interferometers: From physics to biosensing applications

NASA Astrophysics Data System (ADS)

Zeng, Xie

Optical interferometry has a long history and wide range of applications. In recent years, plasmonic interferometer arouses great interest due to its compact size and enhanced light-matter interaction. They have demonstrated attractive applications in biomolecule sensing, optical modulation/switching, and material characterization, etc. In this work, we first propose a practical far-field method to extract the intrinsic phase dispersion, revealing important phase information during interactions among free-space light, nanostructure, and SPs. The proposed approach is confirmed by both simulation and experiment. Then we design novel plasmonic interferometer structure for sensitive optical sensing applications. To overcome two major limitations suffered by previously reported double-slit plasmonic Mach-Zehnder interferometer (PMZI), two new schemes are proposed and investigated. (1) A PMZI based on end-fire coupling improves the SP coupling efficiency and enhance the interference contrast more than 50 times. (2) In another design, a multi-layered metal-insulator-metal PMZI releases the requirement for single-slit illumination, which enables sensitive, high-throughput sensing applications based on intensity modulation. We develop a sensitive, low-cost and high-throughput biosensing platform based on intensity modulation using ring-hole plasmonic interferometers. This biosensor is then integrated with cell-phone-based microscope, which is promising to develop a portable sensor for point-of-care diagnostics, epidemic disease control and food safety monitoring.

Identification of the optimal spectral region for plasmonic and nanoplasmonic sensing.

PubMed

Otte, Marinus A; Sepúlveda, Borja; Ni, Weihai; Juste, Jorge Pérez; Liz-Marzán, Luis M; Lechuga, Laura M

2010-01-26

We present a theoretical and experimental study involving the sensing characteristics of wavelength-interrogated plasmonic sensors based on surface plasmon polaritons (SPP) in planar gold films and on localized surface plasmon resonances (LSPR) of single gold nanorods. The tunability of both sensing platforms allowed us to analyze their bulk and surface sensing characteristics as a function of the plasmon resonance position. We demonstrate that a general figure of merit (FOM), which is equivalent in wavelength and energy scales, can be employed to mutually compare both sensing schemes. Most interestingly, this FOM has revealed a spectral region for which the surface sensitivity performance of both sensor types is optimized, which we attribute to the intrinsic dielectric properties of plasmonic materials. Additionally, in good agreement with theoretical predictions, we experimentally demonstrate that, although the SPP sensor offers a much better bulk sensitivity, the LSPR sensor shows an approximately 15% better performance for surface sensitivity measurements when its FOM is optimized. However, optimization of the substrate refractive index and the accessibility of the relevant molecules to the nanoparticles can lead to a total 3-fold improvement of the FOM in LSPR sensors.

The Sky Is the Limit: Reconstructing Physical Geography from an Aerial Perspective

ERIC Educational Resources Information Center

Williams, Richard D.; Tooth, Stephen; Gibson, Morgan

2017-01-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned Aerial Vehicles (UAVs) provide a relatively inexpensive opportunity to introduce…

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Calibration of the degree of linear polarization measurements of the polarized Sun-sky radiometer based on the POLBOX system.

PubMed

Li, Zhengqiang; Li, Kaitao; Li, Li; Xu, Hua; Xie, Yisong; Ma, Yan; Li, Donghui; Goloub, Philippe; Yuan, Yinlin; Zheng, Xiaobing

2018-02-10

Polarization observation of sky radiation is the frontier approach to improve the remote sensing of atmospheric components, e.g., aerosol and clouds. The polarization calibration of the ground-based Sun-sky radiometer is the basis for obtaining accurate degree of linear polarization (DOLP) measurement. In this paper, a DOLP calibration method based on a laboratory polarized light source (POLBOX) is introduced in detail. Combined with the CE318-DP Sun-sky polarized radiometer, a calibration scheme for DOLP measurement is established for the spectral range of 440-1640 nm. Based on the calibration results of the Sun-sky radiometer observation network, the polarization calibration coefficient and the DOLP calibration residual are analyzed statistically. The results show that the DOLP residual of the calibration scheme is about 0.0012, and thus it can be estimated that the final DOLP calibration accuracy of this method is about 0.005. Finally, it is verified that the accuracy of the calibration results is in accordance with the expected results by comparing the simulated DOLP with the vector radiative transfer calculations.

Design and evaluation of prosthetic shoulder controller

PubMed Central

Barton, Joseph E.; Sorkin, John D.

2015-01-01

We developed a 2-degree-of-freedom (DOF) shoulder position transducer (sensing shoulder protraction-retraction and elevation-depression) that can be used to control two of a powered prosthetic humerus' DOFs. We also developed an evaluation protocol based on Fitts' law to assess the performance of our device. The primary motivation for this work was to support development of powered prosthetic shoulder joints of a new generation of prosthetic arms for people with shoulder disarticulation and very high-level transhumeral amputation. We found that transducers that provided resistance to shoulder movement performed better than those providing no resistance. We also found that a position control scheme, where effector position is proportional to shoulder position, performed better than a velocity control scheme, where effector velocity is proportional to shoulder position. More generally, our transducer can be used to control motion along any two DOFs. It can also be used in a more general 4-DOF control scheme by sequentially controlling two DOFs at a time. The evaluation protocol has general applicability for researchers and practitioners. Researchers can employ it to compare different prosthesis designs and control schemes, while practitioners may find the evaluation protocol useful in evaluating and training people with amputation in the use of prostheses. PMID:25357185

Laser based structural health monitoring for civil, mechanical, and aerospace systems

NASA Astrophysics Data System (ADS)

Sohn, Hoon

2012-04-01

This paper provides an overview of ongoing laser ultrasonics based structural health monitoring (SHM) activities being performed by the author. Particular focus is given to (1) the development of a fully noncontact laser ultrasonic system that can easily visualize defects with high spatial resolution, (2) laser based wireless power and data transmission schemes for remote guided waves and impedance measurements, (3) minimization of false alarms due to varying operational and environmental conditions, and (4) extension to embedded laser ultrasonic excitation and sensing. SHM examples ranging from bridges to airplanes, as well as nuclear power plants, high-speed rails and wind turbines are also presented.

Advanced control architecture for autonomous vehicles

NASA Astrophysics Data System (ADS)

Maurer, Markus; Dickmanns, Ernst D.

1997-06-01

An advanced control architecture for autonomous vehicles is presented. The hierarchical architecture consists of four levels: a vehicle level, a control level, a rule-based level and a knowledge-based level. A special focus is on forms of internal representation, which have to be chosen adequately for each level. The control scheme is applied to VaMP, a Mercedes passenger car which autonomously performs missions on German freeways. VaMP perceives the environment with its sense of vision and conventional sensors. It controls its actuators for locomotion and attention focusing. Modules for perception, cognition and action are discussed.

Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groat, Michael; Forrest, Stephanie; Horey, James L

2012-01-01

Participatory sensing applications rely on individuals to share local and personal data with others to produce aggregated models and knowledge. In this setting, privacy is an important consideration, and lack of privacy could discourage widespread adoption of many exciting applications. We present a privacy-preserving participatory sensing scheme for multidimensional data which uses negative surveys. Multidimensional data, such as vectors of attributes that include location and environment fields, pose a particular challenge for privacy protection and are common in participatory sensing applications. When reporting data in a negative survey, an individual participant randomly selects a value from the set complement ofmore » the sensed data value, once for each dimension, and returns the negative values to a central collection server. Using algorithms described in this paper, the server can reconstruct the probability density functions of the original distributions of sensed values, without knowing the participants actual data. As a consequence, complicated encryption and key management schemes are avoided, conserving energy. We study trade-offs between accuracy and privacy, and their relationships to the number of dimensions, categories, and participants. We introduce dimensional adjustment, a method that reduces the magnification of error associated with earlier work. Two simulation scenarios illustrate how the approach can protect the privacy of a participant's multidimensional data while allowing useful population information to be aggregated.« less

Media Access Time-Rearrangement of Wireless LAN for a Multi-Radio Collocated Platform

NASA Astrophysics Data System (ADS)

Shin, Sang-Heon; Kim, Chul; Park, Sang Kyu

With the advent of new Radio Access Technologies (RATs), it is inevitable that several RATs will co-exist, especially in the license-exempt band. In this letter, we present an in-depth adaptation of the proactive time-rearrangement (PATRA) scheme for IEEE 802.11 WLAN. The PATRA is a time division approach for reducing interference from a multi-radio device. Because IEEE 802.11 is based on carrier sensing and contention mechanism, it is the most suitable candidate to adapt the PATRA.

Architectures and algorithms for digital image processing; Proceedings of the Meeting, Cannes, France, December 5, 6, 1985

NASA Technical Reports Server (NTRS)

Duff, Michael J. B. (Editor); Siegel, Howard J. (Editor); Corbett, Francis J. (Editor)

1986-01-01

The conference presents papers on the architectures, algorithms, and applications of image processing. Particular attention is given to a very large scale integration system for image reconstruction from projections, a prebuffer algorithm for instant display of volume data, and an adaptive image sequence filtering scheme based on motion detection. Papers are also presented on a simple, direct practical method of sensing local motion and analyzing local optical flow, image matching techniques, and an automated biological dosimetry system.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2012-02-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We will discuss our recent progress on device fabrication and characterization. In particular, we demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the embedded pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule.

Issues in measure-preserving three dimensional flow integrators: Self-adjointness, reversibility, and non-uniform time stepping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finn, John M., E-mail: finn@lanl.gov

2015-03-15

Properties of integration schemes for solenoidal fields in three dimensions are studied, with a focus on integrating magnetic field lines in a plasma using adaptive time stepping. It is shown that implicit midpoint (IM) and a scheme we call three-dimensional leapfrog (LF) can do a good job (in the sense of preserving KAM tori) of integrating fields that are reversible, or (for LF) have a “special divergence-free” (SDF) property. We review the notion of a self-adjoint scheme, showing that such schemes are at least second order accurate and can always be formed by composing an arbitrary scheme with its adjoint.more » We also review the concept of reversibility, showing that a reversible but not exactly volume-preserving scheme can lead to a fractal invariant measure in a chaotic region, although this property may not often be observable. We also show numerical results indicating that the IM and LF schemes can fail to preserve KAM tori when the reversibility property (and the SDF property for LF) of the field is broken. We discuss extensions to measure preserving flows, the integration of magnetic field lines in a plasma and the integration of rays for several plasma waves. The main new result of this paper relates to non-uniform time stepping for volume-preserving flows. We investigate two potential schemes, both based on the general method of Feng and Shang [Numer. Math. 71, 451 (1995)], in which the flow is integrated in split time steps, each Hamiltonian in two dimensions. The first scheme is an extension of the method of extended phase space, a well-proven method of symplectic integration with non-uniform time steps. This method is found not to work, and an explanation is given. The second method investigated is a method based on transformation to canonical variables for the two split-step Hamiltonian systems. This method, which is related to the method of non-canonical generating functions of Richardson and Finn [Plasma Phys. Controlled Fusion 54, 014004 (2012)], appears to work very well.« less

Continuous-Reading Cryogen Level Sensor

NASA Technical Reports Server (NTRS)

Barone, F. E.; Fox, E.; Macumber, S.

1984-01-01

Two pressure transducers used in system for measuring amount of cryogenic liquid in tank. System provides continuous measurements accurate within 0.03 percent. Sensors determine pressure in liquid and vapor in tank. Microprocessor uses pressure difference to compute mass of cryogenic liquid in tank. New system allows continuous sensing; unaffected by localized variations in composition and density as are capacitance-sensing schemes.

Inversion Schemes to Retrieve Atmospheric and Oceanic Parameters from SeaWiFS Data

NASA Technical Reports Server (NTRS)

Deschamps, P.-Y.; Frouin, R.

1997-01-01

The investigation focuses on two key issues in satellite ocean color remote sensing, namely the presence of whitecaps on the sea surface and the validity of the aerosol models selected for the atmospheric correction of SeaWiFS data. Experiments were designed and conducted at the Scripps Institution of Oceanography to measure the optical properties of whitecaps and to study the aerosol optical properties in a typical mid-latitude coastal environment. CIMEL Electronique sunphotometers, now integrated in the AERONET network, were also deployed permanently in Bermuda and in Lanai, calibration/validation sites for SeaWiFS and MODIS. Original results were obtained on the spectral reflectance of whitecaps and on the choice of aerosol models for atmospheric correction schemes and the type of measurements that should be made to verify those schemes. Bio-optical algorithms to remotely sense primary productivity from space were also evaluated, as well as current algorithms to estimate PAR at the earth's surface.

Multiple-correction hybrid k-exact schemes for high-order compressible RANS-LES simulations on fully unstructured grids

NASA Astrophysics Data System (ADS)

Pont, Grégoire; Brenner, Pierre; Cinnella, Paola; Maugars, Bruno; Robinet, Jean-Christophe

2017-12-01

A Godunov's type unstructured finite volume method suitable for highly compressible turbulent scale-resolving simulations around complex geometries is constructed by using a successive correction technique. First, a family of k-exact Godunov schemes is developed by recursively correcting the truncation error of the piecewise polynomial representation of the primitive variables. The keystone of the proposed approach is a quasi-Green gradient operator which ensures consistency on general meshes. In addition, a high-order single-point quadrature formula, based on high-order approximations of the successive derivatives of the solution, is developed for flux integration along cell faces. The proposed family of schemes is compact in the algorithmic sense, since it only involves communications between direct neighbors of the mesh cells. The numerical properties of the schemes up to fifth-order are investigated, with focus on their resolvability in terms of number of mesh points required to resolve a given wavelength accurately. Afterwards, in the aim of achieving the best possible trade-off between accuracy, computational cost and robustness in view of industrial flow computations, we focus more specifically on the third-order accurate scheme of the family, and modify locally its numerical flux in order to reduce the amount of numerical dissipation in vortex-dominated regions. This is achieved by switching from the upwind scheme, mostly applied in highly compressible regions, to a fourth-order centered one in vortex-dominated regions. An analytical switch function based on the local grid Reynolds number is adopted in order to warrant numerical stability of the recentering process. Numerical applications demonstrate the accuracy and robustness of the proposed methodology for compressible scale-resolving computations. In particular, supersonic RANS/LES computations of the flow over a cavity are presented to show the capability of the scheme to predict flows with shocks, vortical structures and complex geometries.

Texture mapping via optimal mass transport.

PubMed

Dominitz, Ayelet; Tannenbaum, Allen

2010-01-01

In this paper, we present a novel method for texture mapping of closed surfaces. Our method is based on the technique of optimal mass transport (also known as the "earth-mover's metric"). This is a classical problem that concerns determining the optimal way, in the sense of minimal transportation cost, of moving a pile of soil from one site to another. In our context, the resulting mapping is area preserving and minimizes angle distortion in the optimal mass sense. Indeed, we first begin with an angle-preserving mapping (which may greatly distort area) and then correct it using the mass transport procedure derived via a certain gradient flow. In order to obtain fast convergence to the optimal mapping, we incorporate a multiresolution scheme into our flow. We also use ideas from discrete exterior calculus in our computations.

Biomimicry of quorum sensing using bacterial lifecycle model.

PubMed

Niu, Ben; Wang, Hong; Duan, Qiqi; Li, Li

2013-01-01

Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems.

Biomimicry of quorum sensing using bacterial lifecycle model

PubMed Central

2013-01-01

Background Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. Results In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Conclusions Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems. PMID:23815296

Transparent Fingerprint Sensor System for Large Flat Panel Display.

PubMed

Seo, Wonkuk; Pi, Jae-Eun; Cho, Sung Haeung; Kang, Seung-Youl; Ahn, Seong-Deok; Hwang, Chi-Sun; Jeon, Ho-Sik; Kim, Jong-Uk; Lee, Myunghee

2018-01-19

In this paper, we introduce a transparent fingerprint sensing system using a thin film transistor (TFT) sensor panel, based on a self-capacitive sensing scheme. An armorphousindium gallium zinc oxide (a-IGZO) TFT sensor array and associated custom Read-Out IC (ROIC) are implemented for the system. The sensor panel has a 200 × 200 pixel array and each pixel size is as small as 50 μm × 50 μm. The ROIC uses only eight analog front-end (AFE) amplifier stages along with a successive approximation analog-to-digital converter (SAR ADC). To get the fingerprint image data from the sensor array, the ROIC senses a capacitance, which is formed by a cover glass material between a human finger and an electrode of each pixel of the sensor array. Three methods are reviewed for estimating the self-capacitance. The measurement result demonstrates that the transparent fingerprint sensor system has an ability to differentiate a human finger's ridges and valleys through the fingerprint sensor array.

Transparent Fingerprint Sensor System for Large Flat Panel Display

PubMed Central

Seo, Wonkuk; Pi, Jae-Eun; Cho, Sung Haeung; Kang, Seung-Youl; Ahn, Seong-Deok; Hwang, Chi-Sun; Jeon, Ho-Sik; Kim, Jong-Uk

2018-01-01

In this paper, we introduce a transparent fingerprint sensing system using a thin film transistor (TFT) sensor panel, based on a self-capacitive sensing scheme. An armorphousindium gallium zinc oxide (a-IGZO) TFT sensor array and associated custom Read-Out IC (ROIC) are implemented for the system. The sensor panel has a 200 × 200 pixel array and each pixel size is as small as 50 μm × 50 μm. The ROIC uses only eight analog front-end (AFE) amplifier stages along with a successive approximation analog-to-digital converter (SAR ADC). To get the fingerprint image data from the sensor array, the ROIC senses a capacitance, which is formed by a cover glass material between a human finger and an electrode of each pixel of the sensor array. Three methods are reviewed for estimating the self-capacitance. The measurement result demonstrates that the transparent fingerprint sensor system has an ability to differentiate a human finger’s ridges and valleys through the fingerprint sensor array. PMID:29351218

Nonlocally sensing the magnetic states of nanoscale antiferromagnets with an atomic spin sensor

PubMed Central

Yan, Shichao; Malavolti, Luigi; Burgess, Jacob A. J.; Droghetti, Andrea; Rubio, Angel; Loth, Sebastian

2017-01-01

The ability to sense the magnetic state of individual magnetic nano-objects is a key capability for powerful applications ranging from readout of ultradense magnetic memory to the measurement of spins in complex structures with nanometer precision. Magnetic nano-objects require extremely sensitive sensors and detection methods. We create an atomic spin sensor consisting of three Fe atoms and show that it can detect nanoscale antiferromagnets through minute, surface-mediated magnetic interaction. Coupling, even to an object with no net spin and having vanishing dipolar stray field, modifies the transition matrix element between two spin states of the Fe atom–based spin sensor that changes the sensor’s spin relaxation time. The sensor can detect nanoscale antiferromagnets at up to a 3-nm distance and achieves an energy resolution of 10 μeV, surpassing the thermal limit of conventional scanning probe spectroscopy. This scheme permits simultaneous sensing of multiple antiferromagnets with a single-spin sensor integrated onto the surface. PMID:28560346

Glucose monitoring using a polymer brush modified polypropylene hollow fiber-based hydraulic flow sensor.

PubMed

Fortin, Nicolas; Klok, Harm-Anton

2015-03-04

Tight regulation of blood glucose levels of diabetic patients requires durable and robust continuous glucose sensing schemes. This manuscript reports the fabrication of ultrathin, phenylboronic acid (PBA) functionalized polymer brushes that swell upon glucose binding and which were integrated as the sensing interface in a new polypropylene hollow fiber (PPHF)-based hydraulic flow glucose sensor prototype. The polymer brushes were prepared via surface-initiated atom transfer radical polymerization of sodium methacrylate followed by postpolymerization modification with 3-aminophenyl boronic acid. In a first series of experiments, the glucose-response of PBA-functionalized poly(methacrylic acid) (PMAA) brushes grafted from planar silicon surfaces was investigated by quartz crystal microbalance with dissipation (QCM-D) and atomic force microscopy (AFM) experiments. The QCM-D experiments revealed a more or less linear change of the frequency shift for glucose concentrations up to ∼10 mM and demonstrated that glucose binding was completely reversible for up to seven switching cycles. The AFM experiments indicated that glucose binding was accompanied by an increase in the film thickness of the PBA functionalized PMAA brushes. The PBA functionalized PMAA brushes were subsequently grafted from the surface of PPHF membranes. The hydraulic permeability of these porous fibers depends on the thickness and swelling of the PMAA brush coating. PBA functionalized brush-coated PPHFs showed a decrease in flux upon exposure to glucose, which is consistent with swelling of the brush coating. Because they avoid the use of enzymes and do not rely on an electrochemical transduction scheme, these PPHF-based hydraulic flow sensors could represent an interesting alternative class of continuous glucose sensors.

Estimation of Rainfall Rates from Passive Microwave Remote Sensing.

NASA Astrophysics Data System (ADS)

Sharma, Awdhesh Kumar

Rainfall rates have been estimated using the passive microwave and visible/infrared remote sensing techniques. Data of September 14, 1978 from the Scanning Multichannel Microwave Radiometer (SMMR) on board SEA SAT-A and the Visible and Infrared Spin Scan Radiometer (VISSR) on board GOES-W (Geostationary Operational Environmental Satellite - West) was obtained and analyzed for rainfall rate retrieval. Microwave brightness temperatures (MBT) are simulated, using the microwave radiative transfer model (MRTM) and atmospheric scattering models. These MBT were computed as a function of rates of rainfall from precipitating clouds which are in a combined phase of ice and water. Microwave extinction due to ice and liquid water are calculated using Mie-theory and Gamma drop size distributions. Microwave absorption due to oxygen and water vapor are based on the schemes given by Rosenkranz, and Barret and Chung. The scattering phase matrix involved in the MRTM is found using Eddington's two stream approximation. The surface effects due to winds and foam are included through the ocean surface emissivity model. Rainfall rates are then inverted from MBT using the optimization technique "Leaps and Bounds" and multiple linear regression leading to a relationship between the rainfall rates and MBT. This relationship has been used to infer the oceanic rainfall rates from SMMR data. The VISSR data has been inverted for the rainfall rates using Griffith's scheme. This scheme provides an independent means of estimating rainfall rates for cross checking SMMR estimates. The inferred rainfall rates from both techniques have been plotted on a world map for comparison. A reasonably good correlation has been obtained between the two estimates.

Experimental scheme and restoration algorithm of block compression sensing

NASA Astrophysics Data System (ADS)

Zhang, Linxia; Zhou, Qun; Ke, Jun

2018-01-01

Compressed Sensing (CS) can use the sparseness of a target to obtain its image with much less data than that defined by the Nyquist sampling theorem. In this paper, we study the hardware implementation of a block compression sensing system and its reconstruction algorithms. Different block sizes are used. Two algorithms, the orthogonal matching algorithm (OMP) and the full variation minimum algorithm (TV) are used to obtain good reconstructions. The influence of block size on reconstruction is also discussed.

Quantum Sensors for the Generating Functional of Interacting Quantum Field Theories

NASA Astrophysics Data System (ADS)

Bermudez, A.; Aarts, G.; Müller, M.

2017-10-01

Difficult problems described in terms of interacting quantum fields evolving in real time or out of equilibrium abound in condensed-matter and high-energy physics. Addressing such problems via controlled experiments in atomic, molecular, and optical physics would be a breakthrough in the field of quantum simulations. In this work, we present a quantum-sensing protocol to measure the generating functional of an interacting quantum field theory and, with it, all the relevant information about its in- or out-of-equilibrium phenomena. Our protocol can be understood as a collective interferometric scheme based on a generalization of the notion of Schwinger sources in quantum field theories, which make it possible to probe the generating functional. We show that our scheme can be realized in crystals of trapped ions acting as analog quantum simulators of self-interacting scalar quantum field theories.

Fast and Robust Registration of Multimodal Remote Sensing Images via Dense Orientated Gradient Feature

NASA Astrophysics Data System (ADS)

Ye, Y.

2017-09-01

This paper presents a fast and robust method for the registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR and map). The proposed method is based on the hypothesis that structural similarity between images is preserved across different modalities. In the definition of the proposed method, we first develop a pixel-wise feature descriptor named Dense Orientated Gradient Histogram (DOGH), which can be computed effectively at every pixel and is robust to non-linear intensity differences between images. Then a fast similarity metric based on DOGH is built in frequency domain using the Fast Fourier Transform (FFT) technique. Finally, a template matching scheme is applied to detect tie points between images. Experimental results on different types of multimodal remote sensing images show that the proposed similarity metric has the superior matching performance and computational efficiency than the state-of-the-art methods. Moreover, based on the proposed similarity metric, we also design a fast and robust automatic registration system for multimodal images. This system has been evaluated using a pair of very large SAR and optical images (more than 20000 × 20000 pixels). Experimental results show that our system outperforms the two popular commercial software systems (i.e. ENVI and ERDAS) in both registration accuracy and computational efficiency.

Interrogation of miniature extrinsic Fabry-Pérot sensor using path matched differential interferometer and phase generated carrier scheme

NASA Astrophysics Data System (ADS)

Wang, Fuyin; Xie, Jiehui; Hu, Zhengliang; Xiong, Shuidong; Luo, Hong; Hu, Yongming

2014-05-01

Study of fiber optic extrinsic Fabry-Pérot sensors utilizing state-of-the-art MEMS technology mostly focus on sensor fabrication for various applications, while the signal interrogation is still insatiable to current application. In this paper, we propose a white light path matched differential interferometer dynamic sensing system utilizing phase generated carrier demodulation scheme. A step motor with a movable mirror and a fiber-wound piezoelectric transducer string are used to act path matching and phase modulation respectively. Experimental results show that the sensing signal could be correctly recovered with low distortion and the phase noise spectrum level is less than -100 dB re. rad/√Hz above 2.5 kHz.

Differential laser-induced perturbation spectroscopy and fluorescence imaging for biological and materials sensing

NASA Astrophysics Data System (ADS)

Burton, Dallas Jonathan

The field of laser-based diagnostics has been a topic of research in various fields, more specifically for applications in environmental studies, military defense technologies, and medicine, among many others. In this dissertation, a novel laser-based optical diagnostic method, differential laser-induced perturbation spectroscopy (DLIPS), has been implemented in a spectroscopy mode and expanded into an imaging mode in combination with fluorescence techniques. The DLIPS method takes advantage of deep ultraviolet (UV) laser perturbation at sub-ablative energy fluences to photochemically cleave bonds and alter fluorescence signal response before and after perturbation. The resulting difference spectrum or differential image adds more information about the target specimen, and can be used in combination with traditional fluorescence techniques for detection of certain materials, characterization of many materials and biological specimen, and diagnosis of various human skin conditions. The differential aspect allows for mitigation of patient or sample variation, and has the potential to develop into a powerful, noninvasive optical sensing tool. The studies in this dissertation encompass efforts to continue the fundamental research on DLIPS including expansion of the method to an imaging mode. Five primary studies have been carried out and presented. These include the use of DLIPS in a spectroscopy mode for analysis of nitrogen-based explosives on various substrates, classification of Caribbean fruit flies versus Caribbean fruit flies that have been irradiated with gamma rays, and diagnosis of human skin cancer lesions. The nitrogen-based explosives and Caribbean fruit flies have been analyzed with the DLIPS scheme using the imaging modality, providing complementary information to the spectroscopic scheme. In each study, a comparison between absolute fluorescence signals and DLIPS responses showed that DLIPS statistically outperformed traditional fluorescence techniques with regards to regression error and classification.

Investigating the differences of cirrus cloud properties in nucleation, growth and sublimation regions based on airborne water vapor lidar measurements

NASA Astrophysics Data System (ADS)

Urbanek, Benedikt; Groß, Silke; Wirth, Martin

2017-04-01

Cirrus clouds impose high uncertainties on weather and climate prediction, as knowledge on important processes is still incomplete. For instance it remains unclear how cloud optical, microphysical, and radiative properties change as the cirrus evolves. To gain better understanding of cirrus clouds, their optical and microphysical properties and their changes with cirrus cloud evolution the ML-CIRRUS campaign was conducted in March and April 2014. Measurements with a combined in-situ and remote sensing payload were performed with the German research aircraft HALO based in Oberpfaffenhofen. 16 research flights with altogether 88 flight hours were performed over the North-Atlantic, western and central Europe to probe different cirrus cloud regimes and cirrus clouds at different stages of evolution. One of the key remotes sensing instruments during ML-CIRRUS was the airborne differential absorption and high spectral lidar system WALES. It measures the 2-dimensional distribution of water vapor inside and outside of cirrus clouds as well as the optical properties of the clouds. Bases on these airborne lidar measurements a novel classification scheme to derive the stage of cirrus cloud evolution was developed. It identifies regions of ice nucleation, particle growth by deposition of water vapor, and ice sublimation. This method is used to investigate differences in the distribution and value of optical properties as well as in the distribution of water vapor and relative humidity depending on the stage of evolution of the cloud. We will present the lidar based classification scheme and its application on a wave driven cirrus cloud case, and we will show first results of the dependence of optical cloud properties and relative humidity distributions on the determined stage of evolution.

Modeling and Detection of Ice Particle Accretion in Aircraft Engine Compression Systems

NASA Technical Reports Server (NTRS)

May, Ryan D.; Simon, Donald L.; Guo, Ten-Huei

2012-01-01

The accretion of ice particles in the core of commercial aircraft engines has been an ongoing aviation safety challenge. While no accidents have resulted from this phenomenon to date, numerous engine power loss events ranging from uneventful recoveries to forced landings have been recorded. As a first step to enabling mitigation strategies during ice accretion, a detection scheme must be developed that is capable of being implemented on board modern engines. In this paper, a simple detection scheme is developed and tested using a realistic engine simulation with approximate ice accretion models based on data from a compressor design tool. These accretion models are implemented as modified Low Pressure Compressor maps and have the capability to shift engine performance based on a specified level of ice blockage. Based on results from this model, it is possible to detect the accretion of ice in the engine core by observing shifts in the typical sensed engine outputs. Results are presented in which, for a 0.1 percent false positive rate, a true positive detection rate of 98 percent is achieved.

Detection of TNT using a sensitive two-photon organic dendrimer for remote sensing

NASA Astrophysics Data System (ADS)

Narayanan, Aditya; Varnavski, Oleg; Mongin, Oliver; Majoral, Jean-Pierre; Blanchard-Desce, Mireille; Goodson, Theodore, III

2008-03-01

There is currently a need for superior stand-off detection schemes for protection against explosive weapons of mass destruction. Fluorescence detection at small distances from the target has proven to be attractive. A novel unexplored route in fluorescence chemical sensing that utilizes the exceptional spectroscopic capabilities of nonlinear optical methods is two-photon excited fluorescence. This approach utilizes infra-red light for excitation of remote sensors. Infra-red light suffers less scattering in porous materials which is beneficial for vapor sensing and has greater depth of penetration through the atmosphere, and there are fewer concerns regarding eye safety in remote detection schemes. We demonstrate this method using a novel dendritic system which possesses both excellent fluorescence sensitivity to the presence of TNT with infra-red pulses of light and high two-photon absorption (TPA) response. This illustrates the use of TPA for potential stand-off detection of energetic materials in the infra-red spectral regions in a highly two-photon responsive dendrimer.

RCTS: A flexible environment for sensor integration and control of robot systems; the distributed processing approach

NASA Technical Reports Server (NTRS)

Allard, R.; Mack, B.; Bayoumi, M. M.

1989-01-01

Most robot systems lack a suitable hardware and software environment for the efficient research of new control and sensing schemes. Typically, engineers and researchers need to be experts in control, sensing, programming, communication and robotics in order to implement, integrate and test new ideas in a robot system. In order to reduce this time, the Robot Controller Test Station (RCTS) has been developed. It uses a modular hardware and software architecture allowing easy physical and functional reconfiguration of a robot. This is accomplished by emphasizing four major design goals: flexibility, portability, ease of use, and ease of modification. An enhanced distributed processing version of RCTS is described. It features an expanded and more flexible communication system design. Distributed processing results in the availability of more local computing power and retains the low cost of microprocessors. A large number of possible communication, control and sensing schemes can therefore be easily introduced and tested, using the same basic software structure.

Graphene-deposited photonic crystal fibers for continuous refractive index sensing applications.

PubMed

Tan, Y C; Tou, Z Q; Chow, K K; Chan, C C

2015-11-30

We present a pilot demonstration of an optical fiber based refractive index (RI) sensor involving the deposition of graphene onto the surface of a segment of a photonic crystal fiber (PCF) in a fiber-based Mach-Zehnder Interferometer (MZI). The fabrication process is relatively simple and only involves the fusion splicing of a PCF between two single mode fibers. The deposition process relies only on the cold transfer of graphene onto the PCF segment, without the need for further physical or chemical treatment. The graphene overlay modified the sensing scheme of the MZI RI sensor, allowing the sensor to overcome limitations to its detectable RI range due to free spectral range issues. This modification also allows for continuous measurements to be obtained without the need for reference values for the range of RIs studied and brings to light the potential for simultaneous dual parameter sensing. The sensor was able to achieve a RI sensitivity of 9.4 dB/RIU for the RIs of 1.33-1.38 and a sensitivity of 17.5 dB/RIU for the RIs of 1.38-1.43. It also displayed good repeatability and the results obtained were consistent with the modeling.

A Classification Methodology and Retrieval Model to Support Software Reuse

DTIC Science & Technology

1988-01-01

Dewey Decimal Classification ( DDC 18), an enumerative scheme, occupies 40 pages [Buchanan 19791. Langridge [19731 states that the facets listed in the...sense of historical importance or wide spread use. The schemes are: Dewey Decimal Classification ( DDC ), Universal Decimal Classification (UDC...Classification Systems ..... ..... 2.3.3 Library Classification__- .52 23.3.1 Dewey Decimal Classification -53 2.33.2 Universal Decimal Classification 55 2333

Compressive Sampling based Image Coding for Resource-deficient Visual Communication.

PubMed

Liu, Xianming; Zhai, Deming; Zhou, Jiantao; Zhang, Xinfeng; Zhao, Debin; Gao, Wen

2016-04-14

In this paper, a new compressive sampling based image coding scheme is developed to achieve competitive coding efficiency at lower encoder computational complexity, while supporting error resilience. This technique is particularly suitable for visual communication with resource-deficient devices. At the encoder, compact image representation is produced, which is a polyphase down-sampled version of the input image; but the conventional low-pass filter prior to down-sampling is replaced by a local random binary convolution kernel. The pixels of the resulting down-sampled pre-filtered image are local random measurements and placed in the original spatial configuration. The advantages of local random measurements are two folds: 1) preserve high-frequency image features that are otherwise discarded by low-pass filtering; 2) remain a conventional image and can therefore be coded by any standardized codec to remove statistical redundancy of larger scales. Moreover, measurements generated by different kernels can be considered as multiple descriptions of the original image and therefore the proposed scheme has the advantage of multiple description coding. At the decoder, a unified sparsity-based soft-decoding technique is developed to recover the original image from received measurements in a framework of compressive sensing. Experimental results demonstrate that the proposed scheme is competitive compared with existing methods, with a unique strength of recovering fine details and sharp edges at low bit-rates.

A three stage sampling model for remote sensing applications

NASA Technical Reports Server (NTRS)

Eisgruber, L. M.

1972-01-01

A conceptual model and an empirical application of the relationship between the manner of selecting observations and its effect on the precision of estimates from remote sensing are reported. This three stage sampling scheme considers flightlines, segments within flightlines, and units within these segments. The error of estimate is dependent on the number of observations in each of the stages.

'Just another incentive scheme': a qualitative interview study of a local pay-for-performance scheme for primary care.

PubMed

Hackett, Julia; Glidewell, Liz; West, Robert; Carder, Paul; Doran, Tim; Foy, Robbie

2014-10-25

A range of policy initiatives have addressed inequalities in healthcare and health outcomes. Local pay-for-performance schemes for primary care have been advocated as means of enhancing clinical ownership of the quality agenda and better targeting local need compared with national schemes such as the UK Quality and Outcomes Framework (QOF). We investigated whether professionals' experience of a local scheme in one English National Health Service (NHS) former primary care trust (PCT) differed from that of the national QOF in relation to the goal of reducing inequalities. We conducted retrospective semi-structured interviews with primary care professionals implementing the scheme and those involved in its development. We purposively sampled practices with varying levels of population socio-economic deprivation and achievement. Interviews explored perceptions of the scheme and indicators, likely mechanisms of influence on practice, perceived benefits and harms, and how future schemes could be improved. We used a framework approach to analysis. Thirty-eight professionals from 16 general practices and six professionals involved in developing local indicators participated. Our findings cover four themes: ownership, credibility of the indicators, influences on behaviour, and exacerbated tensions. We found little evidence that the scheme engendered any distinctive sense of ownership or experiences different from the national scheme. Although the indicators and their evidence base were seldom actively questioned, doubts were expressed about their focus on health promotion given that eventual benefits relied upon patient action and availability of local resources. Whilst practices serving more affluent populations reported status and patient benefit as motivators for participating in the scheme, those serving more deprived populations highlighted financial reward. The scheme exacerbated tensions between patient and professional consultation agendas, general practitioners benefitting directly from incentives and nurses who did much of the work, and practices serving more and less affluent populations which faced different challenges in achieving targets. The contentious nature of pay-for-performance was not necessarily reduced by local adaptation. Those developing future schemes should consider differential rewards and supportive resources for practices serving more deprived populations, and employing a wider range of levers to promote professional understanding and ownership of indicators.

Discrete cosine transform and hash functions toward implementing a (robust-fragile) watermarking scheme

NASA Astrophysics Data System (ADS)

Al-Mansoori, Saeed; Kunhu, Alavi

2013-10-01

This paper proposes a blind multi-watermarking scheme based on designing two back-to-back encoders. The first encoder is implemented to embed a robust watermark into remote sensing imagery by applying a Discrete Cosine Transform (DCT) approach. Such watermark is used in many applications to protect the copyright of the image. However, the second encoder embeds a fragile watermark using `SHA-1' hash function. The purpose behind embedding a fragile watermark is to prove the authenticity of the image (i.e. tamper-proof). Thus, the proposed technique was developed as a result of new challenges with piracy of remote sensing imagery ownership. This led researchers to look for different means to secure the ownership of satellite imagery and prevent the illegal use of these resources. Therefore, Emirates Institution for Advanced Science and Technology (EIAST) proposed utilizing existing data security concept by embedding a digital signature, "watermark", into DubaiSat-1 satellite imagery. In this study, DubaiSat-1 images with 2.5 meter resolution are used as a cover and a colored EIAST logo is used as a watermark. In order to evaluate the robustness of the proposed technique, a couple of attacks are applied such as JPEG compression, rotation and synchronization attacks. Furthermore, tampering attacks are applied to prove image authenticity.

Inter-satellite laser link acquisition with dual-way scanning for Space Advanced Gravity Measurements mission

NASA Astrophysics Data System (ADS)

Zhang, Jing-Yi; Ming, Min; Jiang, Yuan-Ze; Duan, Hui-Zong; Yeh, Hsien-Chi

2018-06-01

Laser link acquisition is a key technology for inter-satellite laser ranging and laser communication. In this paper, we present an acquisition scheme based on the differential power sensing method with dual-way scanning, which will be used in the next-generation gravity measurement mission proposed in China, called Space Advanced Gravity Measurements (SAGM). In this scheme, the laser beams emitted from two satellites are power-modulated at different frequencies to enable the signals of the two beams to be measured distinguishably, and their corresponding pointing angles are determined by using the differential power sensing method. As the master laser beam and the slave laser beam are decoupled, the dual-way scanning method, in which the laser beams of both the master and the slave satellites scan uncertainty cones simultaneously and independently, can be used, instead of the commonly used single-way scanning method, in which the laser beam of one satellite scans and that of the other one stares. Therefore, the acquisition time is reduced significantly. Numerical simulation and experiments of the acquisition process are performed using the design parameters of the SAGM mission. The results show that the average acquisition time is less than 10 s for a scanning range of 1-mrad radius with a success rate of more than 99%.

Modeling and Analysis of Micro-Spacecraft Attitude Sensing with Gyrowheel.

PubMed

Liu, Xiaokun; Zhao, Hui; Yao, Yu; He, Fenghua

2016-08-19

This paper proposes two kinds of approaches of angular rate sensing for micro-spacecraft with a gyrowheel (GW), which can combine attitude sensing with attitude control into one single device to achieve a compact micro-spacecraft design. In this implementation, during the three-dimensional attitude control torques being produced, two-dimensional spacecraft angular rates can be sensed from the signals of the GW sensors, such as the currents of the torque coils, the tilt angles of the rotor, the motor rotation, etc. This paper focuses on the problems of the angular rate sensing with the GW at large tilt angles of the rotor. For this purpose, a novel real-time linearization approach based on Lyapunov's linearization theory is proposed, and a GW linearized measurement model at arbitrary tilt angles of the rotor is derived. Furthermore, by representing the two-dimensional rotor tilt angles and tilt control torques as complex quantities and separating the twice periodic terms about the motor spin speed, the linearized measurement model at smaller tilt angles of the rotor is given and simplified. According to the respective characteristics, the application schemes of the two measurement models are analyzed from the engineering perspective. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed strategy.

Modeling and Analysis of Micro-Spacecraft Attitude Sensing with Gyrowheel

PubMed Central

Liu, Xiaokun; Zhao, Hui; Yao, Yu; He, Fenghua

2016-01-01

This paper proposes two kinds of approaches of angular rate sensing for micro-spacecraft with a gyrowheel (GW), which can combine attitude sensing with attitude control into one single device to achieve a compact micro-spacecraft design. In this implementation, during the three-dimensional attitude control torques being produced, two-dimensional spacecraft angular rates can be sensed from the signals of the GW sensors, such as the currents of the torque coils, the tilt angles of the rotor, the motor rotation, etc. This paper focuses on the problems of the angular rate sensing with the GW at large tilt angles of the rotor. For this purpose, a novel real-time linearization approach based on Lyapunov’s linearization theory is proposed, and a GW linearized measurement model at arbitrary tilt angles of the rotor is derived. Furthermore, by representing the two-dimensional rotor tilt angles and tilt control torques as complex quantities and separating the twice periodic terms about the motor spin speed, the linearized measurement model at smaller tilt angles of the rotor is given and simplified. According to the respective characteristics, the application schemes of the two measurement models are analyzed from the engineering perspective. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed strategy. PMID:27548178

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Coarse graining Escherichia coli chemotaxis: from multi-flagella propulsion to logarithmic sensing.

PubMed

Curk, Tine; Matthäus, Franziska; Brill-Karniely, Yifat; Dobnikar, Jure

2012-01-01

Various sensing mechanisms in nature can be described by the Weber-Fechner law stating that the response to varying stimuli is proportional to their relative rather than absolute changes. The chemotaxis of bacteria Escherichia coli is an example where such logarithmic sensing enables sensitivity over large range of concentrations. It has recently been experimentally demonstrated that under certain conditions E. coli indeed respond to relative gradients of ligands. We use numerical simulations of bacteria in food gradients to investigate the limits of validity of the logarithmic behavior. We model the chemotactic signaling pathway reactions, couple them to a multi-flagella model for propelling and take the effects of rotational diffusion into account to accurately reproduce the experimental observations of single cell swimming. Using this simulation scheme we analyze the type of response of bacteria subject to exponential ligand profiles and identify the regimes of absolute gradient sensing, relative gradient sensing, and a rotational diffusion dominated regime. We explore dependance of the swimming speed, average run time and the clockwise (CW) bias on ligand variation and derive a small set of relations that define a coarse grained model for bacterial chemotaxis. Simulations based on this coarse grained model compare well with microfluidic experiments on E. coli diffusion in linear and exponential gradients of aspartate.

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

DOE PAGES

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.; ...

2018-04-05

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

The influence of the surface roughness parameterization on remote sensing-based estimates of evapotranspiration from vineyards

NASA Astrophysics Data System (ADS)

Alfieri, J. G.; Kustas, W. P.; Gao, F.; Nieto, H.; Prueger, J. H.; Hipps, L.

2017-12-01

Because the judicious application of water is key to ensuring berry quality, information regarding evapotranspiration (ET) is critical when making irrigation and other crop management decisions for vineyards. Increasingly, wine grape producers seek to use remote sensing-based models to monitor ET and inform management decisions. However, the parameterization schemes used by these models do not fully account for the effects of the highly-structured canopy architecture on either the roughness characteristics of the vineyard or the turbulent transport and exchange within and above the vines. To investigate the effects of vineyard structure on the roughness length (zo) and displacement height (do) of vineyards, data collected from 2013 to 2016 as a part of the Grape Remote Sensing Atmospheric Profiling and Evapotranspiration Experiment (GRAPEX), an ongoing multi-agency field campaign conducted in the Central Valley of California, was used. Specifically, vertical profiles (2.5 m, 3.75 m, 5 m, and 8 m, agl) of wind velocity collected under near-neutral conditions were used to estimate do and zo and characterize how these roughness parameters vary in response changing environmental conditions. The roughness length was found to vary as a function of wind direction. It increased sigmoidally from a minimum near 0.15 m when the wind direction was parallel to the vine rows to a maximum between 0.3 m and 0.4 m when the winds were perpendicularly to the rows. Similarly, do was found responds strongly to changes in vegetation density as measured via leaf area index (LAI). Although the maximum varied from year-to-year, do increased rapidly after bud break in all cases and then remained constant for the remainder of the growing season. A comparison of the model output from the remote sensing-based two-source energy balance (TSEB) model using the standard roughness parameterization scheme and the empirical relationships derived from observations indicates a that the modeled ET estimates decrease by 10% to 40%. These results not only demonstrate the unique effects of highly-structured canopies on aerodynamic characteristics, they also provide well-behaved relationships that may be used to improve the accuracy of the model parameterization of do and zo, thus the turbulent fluxes including ET, within vineyards.

Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets

DOE PAGES

Wang, Kai; Mao, Jiafu; Dickinson, Robert; ...

2013-06-05

This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR ’s seasonal cycle, diurnal cycle, long-term trends and spatial patterns. These findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns,more » but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. Here, we identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.« less

A new numerical approach to solve Thomas-Fermi model of an atom using bio-inspired heuristics integrated with sequential quadratic programming.

PubMed

Raja, Muhammad Asif Zahoor; Zameer, Aneela; Khan, Aziz Ullah; Wazwaz, Abdul Majid

2016-01-01

In this study, a novel bio-inspired computing approach is developed to analyze the dynamics of nonlinear singular Thomas-Fermi equation (TFE) arising in potential and charge density models of an atom by exploiting the strength of finite difference scheme (FDS) for discretization and optimization through genetic algorithms (GAs) hybrid with sequential quadratic programming. The FDS procedures are used to transform the TFE differential equations into a system of nonlinear equations. A fitness function is constructed based on the residual error of constituent equations in the mean square sense and is formulated as the minimization problem. Optimization of parameters for the system is carried out with GAs, used as a tool for viable global search integrated with SQP algorithm for rapid refinement of the results. The design scheme is applied to solve TFE for five different scenarios by taking various step sizes and different input intervals. Comparison of the proposed results with the state of the art numerical and analytical solutions reveals that the worth of our scheme in terms of accuracy and convergence. The reliability and effectiveness of the proposed scheme are validated through consistently getting optimal values of statistical performance indices calculated for a sufficiently large number of independent runs to establish its significance.

Evaluation of a new microphysical aerosol module in the ECMWF Integrated Forecasting System

NASA Astrophysics Data System (ADS)

Woodhouse, Matthew; Mann, Graham; Carslaw, Ken; Morcrette, Jean-Jacques; Schulz, Michael; Kinne, Stefan; Boucher, Olivier

2013-04-01

The Monitoring Atmospheric Composition and Climate II (MACC-II) project will provide a system for monitoring and predicting atmospheric composition. As part of the first phase of MACC, the GLOMAP-mode microphysical aerosol scheme (Mann et al., 2010, GMD) was incorporated within the ECMWF Integrated Forecasting System (IFS). The two-moment modal GLOMAP-mode scheme includes new particle formation, condensation, coagulation, cloud-processing, and wet and dry deposition. GLOMAP-mode is already incorporated as a module within the TOMCAT chemistry transport model and within the UK Met Office HadGEM3 general circulation model. The microphysical, process-based GLOMAP-mode scheme allows an improved representation of aerosol size and composition and can simulate aerosol evolution in the troposphere and stratosphere. The new aerosol forecasting and re-analysis system (known as IFS-GLOMAP) will also provide improved boundary conditions for regional air quality forecasts, and will benefit from assimilation of observed aerosol optical depths in near real time. Presented here is an evaluation of the performance of the IFS-GLOMAP system in comparison to in situ aerosol mass and number measurements, and remotely-sensed aerosol optical depth measurements. Future development will provide a fully-coupled chemistry-aerosol scheme, and the capability to resolve nitrate aerosol.

Exploiting the wavelet structure in compressed sensing MRI.

PubMed

Chen, Chen; Huang, Junzhou

2014-12-01

Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of an embedded thin-film strain-gauge-based SHM network into 3D-woven composite structure for wind turbine blades

NASA Astrophysics Data System (ADS)

Zhao, Dongning; Rasool, Shafqat; Forde, Micheal; Weafer, Bryan; Archer, Edward; McIlhagger, Alistair; McLaughlin, James

2017-04-01

Recently, there has been increasing demand in developing low-cost, effective structure health monitoring system to be embedded into 3D-woven composite wind turbine blades to determine structural integrity and presence of defects. With measuring the strain and temperature inside composites at both in-situ blade resin curing and in-service stages, we are developing a novel scheme to embed a resistive-strain-based thin-metal-film sensory into the blade spar-cap that is made of composite laminates to determine structural integrity and presence of defects. Thus, with fiberglass, epoxy, and a thinmetal- film sensing element, a three-part, low-cost, smart composite laminate is developed. Embedded strain sensory inside composite laminate prototype survived after laminate curing process. The internal strain reading from embedded strain sensor under three-point-bending test standard is comparable. It proves that our proposed method will provide another SHM alternative to reduce sensing costs during the renewable green energy generation.

Monolithically integrated tri-axis shock accelerometers with MHz-level high resonant-frequency

NASA Astrophysics Data System (ADS)

Zou, Hongshuo; Wang, Jiachou; Chen, Fang; Bao, Haifei; Jiao, Ding; Zhang, Kun; Song, Zhaohui; Li, Xinxin

2017-07-01

This paper reports a novel monolithically integrated tri-axis high-shock accelerometer with high resonant-frequency for the detection of a broad frequency-band shock signal. For the first time, a resonant-frequency as high as about 1.4 MHz is designed for all the x-, y- and z-axis accelerometers of the integrated tri-axis sensor. In order to achieve a wide frequency-band detection performance, all the three sensing structures are designed into an axially compressed/stretched tiny-beam sensing scheme, where the p  +  -doped tiny-beams are connected into a Wheatstone bridge for piezoresistive output. By using ordinary (1 1 1) silicon wafer (i.e. non-SOI wafer), a single-wafer based fabrication technique is developed to monolithically integrate the three sensing structures for the tri-axis sensor. Testing results under high-shock acceleration show that each of the integrated three-axis accelerometers exhibit about 1.4 MHz resonant-frequency and 0.2-0.4 µV/V/g sensitivity. The achieved high frequencies for all the three sensing units make the tri-axis sensor promising in high fidelity 3D high-shock detection applications.

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

NASA Astrophysics Data System (ADS)

Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun

2017-01-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.

Comparing Aircraft Observations of Snowfall to Forecasts Using Single or Two Moment Bulk Water Microphysics Schemes

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.

2010-01-01

High resolution weather forecast models with explicit prediction of hydrometeor type, size distribution, and fall speed may be useful in the development of precipitation retrievals, by providing representative characteristics of frozen hydrometeors. Several single or double-moment microphysics schemes are currently available within the Weather Research and Forecasting (WRF) model, allowing for the prediction of up to three ice species. Each scheme incorporates different assumptions regarding the characteristics of their ice classes, particularly in terms of size distribution, density, and fall speed. In addition to the prediction of hydrometeor content, these schemes must accurately represent the vertical profile of water vapor to account for possible attenuation, along with the size distribution, density, and shape characteristics of ice crystals that are relevant to microwave scattering. An evaluation of a particular scheme requires the availability of field campaign measurements. The Canadian CloudSat/CALIPSO Validation Project (C3VP) obtained measurements of ice crystal shapes, size distributions, fall speeds, and precipitation during several intensive observation periods. In this study, C3VP observations obtained during the 22 January 2007 synoptic-scale snowfall event are compared against WRF model output, based upon forecasts using four single-moment and two double-moment schemes available as of version 3.1. Schemes are compared against aircraft observations by examining differences in size distribution, density, and content. In addition to direct measurements from aircraft probes, simulated precipitation can also be converted to equivalent, remotely sensed characteristics through the use of the NASA Goddard Satellite Data Simulator Unit. Outputs from high resolution forecasts are compared against radar and satellite observations emphasizing differences in assumed crystal shape and size distribution characteristics.

Polarization-independent transparent effect in windmill-like metasurface

NASA Astrophysics Data System (ADS)

Zhu, Lei; Dong, Liang; Guo, Jing; Meng, Fan Yi; He, Xun Jun; Hao Wu, Tian

2018-07-01

A windmill-like metasurface featuring a polarization-independent electromagnetically induced transparency (EIT) at microwave frequencies is numerically and experimentally demonstrated. The unit cell of the metasurface consists of four rotated identical metal wires, with a 45° angle between the adjacent wires. Destructive coupling between the resonance modes of the metal wires results in the emergence of a transparent window. By combining the metal wires with different degrees of symmetry, EIT effects in the metasurface show polarization-independent properties to incident linear and circular polarization waves. In addition, it is numerically demonstrated that the metasurface possesses a low-loss slow wave property with a group index of 125 and sensing capability based on the refractive index with a figure of merit of 8.73. Such a scheme may lead to many potential applications in areas of slow light and sensing.

Control of spin ambiguity during reorientation of an energy dissipating body

NASA Technical Reports Server (NTRS)

Kaplan, M. H.; Cenker, R. J.

1973-01-01

A quasi-rigid body initially spinning about its minor principal axis and experiencing energy dissipation will enter a tumbling mode and eventually reorient itself such that stable spin about its major principal axis is achieved. However, in this final state the body may be spinning in a positive or negative sense with respect to its major axis and aligned in a positive or negative sense with the inertially fixed angular momentum vector. This ambiguity can be controlled only through an active system. The associated dynamical formulations and simulations of uncontrolled reorientations are presented. Three control schemes are discussed and results offered for specific examples. These schemes include displacement of internal masses, spinning up of internal inertia, and reaction jets, all of which have demonstrated the ability to control spin ambiguity.

Fiber-Optic Distribution Of Pulsed Power To Multiple Sensors

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1996-01-01

Optoelectronic systems designed according to time-sharing scheme distribute optical power to multiple integrated-circuit-based sensors in fiber-optic networks. Networks combine flexibility of electronic sensing circuits with advantage of electrical isolation afforded by use of optical fibers instead of electrical conductors to transmit both signals and power. Fiber optics resist corrosion and immune to electromagnetic interference. Sensor networks of this type useful in variety of applications; for example, in monitoring strains in aircraft, buildings, and bridges, and in monitoring and controlling shapes of flexible structures.

Reflection-induced linear polarization rotation and phase modulation between orthogonal waves for refractive index variation measurement.

PubMed

Twu, Ruey-Ching; Wang, Jhao-Sheng

2016-04-01

An optical phase interrogation is proposed to study reflection-induced linear polarization rotation in a common-path homodyne interferometer. This optical methodology can also be applied to the measurement of the refractive index variation of a liquid solution. The performance of the refractive index sensing structure is discussed theoretically, and the experimental results demonstrated a very good ability based on the proposed schemes. Compared with a conventional common-path heterodyne interferometer, the proposed homodyne interferometer with only a single channel reduced the usage of optic elements.

Large time-step stability of explicit one-dimensional advection schemes

NASA Technical Reports Server (NTRS)

Leonard, B. P.

1993-01-01

There is a wide-spread belief that most explicit one-dimensional advection schemes need to satisfy the so-called 'CFL condition' - that the Courant number, c = udelta(t)/delta(x), must be less than or equal to one, for stability in the von Neumann sense. This puts severe limitations on the time-step in high-speed, fine-grid calculations and is an impetus for the development of implicit schemes, which often require less restrictive time-step conditions for stability, but are more expensive per time-step. However, it turns out that, at least in one dimension, if explicit schemes are formulated in a consistent flux-based conservative finite-volume form, von Neumann stability analysis does not place any restriction on the allowable Courant number. Any explicit scheme that is stable for c is less than 1, with a complex amplitude ratio, G(c), can be easily extended to arbitrarily large c. The complex amplitude ratio is then given by exp(- (Iota)(Nu)(Theta)) G(delta(c)), where N is the integer part of c, and delta(c) = c - N (less than 1); this is clearly stable. The CFL condition is, in fact, not a stability condition at all, but, rather, a 'range restriction' on the 'pieces' in a piece-wise polynomial interpolation. When a global view is taken of the interpolation, the need for a CFL condition evaporates. A number of well-known explicit advection schemes are considered and thus extended to large delta(t). The analysis also includes a simple interpretation of (large delta(t)) total-variation-diminishing (TVD) constraints.

Explicit and implicit compact high-resolution shock-capturing methods for multidimensional Euler equations 1: Formulation

NASA Technical Reports Server (NTRS)

Yee, H. C.

1995-01-01

Two classes of explicit compact high-resolution shock-capturing methods for the multidimensional compressible Euler equations for fluid dynamics are constructed. Some of these schemes can be fourth-order accurate away from discontinuities. For the semi-discrete case their shock-capturing properties are of the total variation diminishing (TVD), total variation bounded (TVB), total variation diminishing in the mean (TVDM), essentially nonoscillatory (ENO), or positive type of scheme for 1-D scalar hyperbolic conservation laws and are positive schemes in more than one dimension. These fourth-order schemes require the same grid stencil as their second-order non-compact cousins. One class does not require the standard matrix inversion or a special numerical boundary condition treatment associated with typical compact schemes. Due to the construction, these schemes can be viewed as approximations to genuinely multidimensional schemes in the sense that they might produce less distortion in spherical type shocks and are more accurate in vortex type flows than schemes based purely on one-dimensional extensions. However, one class has a more desirable high-resolution shock-capturing property and a smaller operation count in 3-D than the other class. The extension of these schemes to coupled nonlinear systems can be accomplished using the Roe approximate Riemann solver, the generalized Steger and Warming flux-vector splitting or the van Leer type flux-vector splitting. Modification to existing high-resolution second- or third-order non-compact shock-capturing computer codes is minimal. High-resolution shock-capturing properties can also be achieved via a variant of the second-order Lax-Friedrichs numerical flux without the use of Riemann solvers for coupled nonlinear systems with comparable operations count to their classical shock-capturing counterparts. The simplest extension to viscous flows can be achieved by using the standard fourth-order compact or non-compact formula for the viscous terms.

Concurrent-scene/alternate-pattern analysis for robust video-based docking systems

NASA Technical Reports Server (NTRS)

Udomkesmalee, Suraphol

1991-01-01

A typical docking target employs a three-point design of retroreflective tape, one at each endpoint of the center-line, and one on the tip of the central post. Scenes, sensed via laser diode illumination, produce pictures with spots corresponding to desired reflection from the retroreflectors and other reflections. Control corrections for each axis of the vehicle can then be properly applied if the desired spots are accurately tracked. However, initial acquisition of these three spots (detection and identification problem) are non-trivial under a severe noise environment. Signal-to-noise enhancement, accomplished by subtracting the non-illuminated scene from the target scene illuminated by laser diodes, can not eliminate every false spot. Hence, minimization of docking failures due to target mistracking would suggest needed inclusion of added processing features pertaining to target locations. In this paper, we present a concurrent processing scheme for a modified docking target scene which could lead to a perfect docking system. Since the non-illuminated target scene is already available, adding another feature to the three-point design by marking two non-reflective lines, one between the two end-points and one from the tip of the central post to the center-line, would allow this line feature to be picked-up only when capturing the background scene (sensor data without laser illumination). Therefore, instead of performing the image subtraction to generate a picture with a high signal-to-noise ratio, a processed line-image based on the robust line detection technique (Hough transform) can be used to fuse with the actively sensed three-point target image to deduce the true locations of the docking target. This dual-channel confirmation scheme is necessary if a fail-safe system is to be realized from both the sensing and processing point-of-views. Detailed algorithms and preliminary results are presented.

Designing and implementing a trust-wide quality assurance programme.

PubMed

Coope, Sally-Ann

2018-04-02

Derbyshire Community Health Services (DCHS) NHS Foundation Trust provides a wide range of community-based health services. After the Care Quality Commission (CQC) found gaps in the trust's assurance process, its board decided to develop a method of continuous quality improvements that could be used as a basis for the trust's quality assurance system. The trust adapted and built on an acute model so it was suitable for community services. The final assurance system, Quality Always, has four elements: the clinical assessment and accreditation scheme; leadership development; 'champions' within clinical teams to support and promote the scheme; and dashboards to record and monitor progress. A system to recognise and reward achievement was essential for success. Quality Always has resulted in better care quality, an improved CQC rating, a sense of achievement among staff, the development of support networks, learning (especially among support staff) and good practice being shared.

Gaming across different consoles: exploring the influence of control scheme on game-player enjoyment.

PubMed

Limperos, Anthony M; Schmierbach, Michael G; Kegerise, Andrew D; Dardis, Frank E

2011-06-01

Many studies have investigated how different technological features impact the experience of playing video games, yet few have focused on how control schemes may affect the play experience. This research employed a between-subjects design to explore the relationship between the type of console played (Nintendo Wii, Playstation 2) and feelings of flow and enjoyment during the game-play experience. Results indicated that participants reported greater feelings of control and enjoyment with a traditional control scheme (Playstation 2) than with the more technologically advanced control scheme (Nintendo Wii). Further mediation analysis showed that enjoyment was driven by the sense of control that participants experienced and not simply by whether they won the game. Theoretical and practical implications are discussed.

Infrared laser spectroscopic trace gas sensing

NASA Astrophysics Data System (ADS)

Sigrist, Markus

2016-04-01

Chemical sensing and analyses of gas samples by laser spectroscopic methods are attractive owing to several advantages such as high sensitivity and specificity, large dynamic range, multi-component capability, and lack of pretreatment or preconcentration procedures. The preferred wavelength range comprises the fundamental molecular absorption range in the mid-infared between 3 and 15 μm, whereas the near-infrared range covers the (10-100 times weaker) higher harmonics and combination bands. The availability of near-infrared and, particularly, of broadly tunable mid-infrared sources like external cavity quantum cascade lasers (EC-QCLs), interband cascade lasers (ICLs), difference frequency generation (DFG), optical parametric oscillators (OPOs), recent developments of diode-pumped lead salt semiconductor lasers, of supercontinuum sources or of frequency combs have eased the implementation of laser-based sensing devices. Sensitive techniques for molecular absorption measurements include multipass absorption, various configurations of cavity-enhanced techniques such as cavity ringdown (CRD), or of photoacoustic spectroscopy (PAS) including quartz-enhanced (QEPAS) or cantilever-enhanced (CEPAS) techniques. The application requirements finally determine the optimum selection of laser source and detection scheme. In this tutorial talk I shall discuss the basic principles, present various experimental setups and illustrate the performance of selected systems for chemical sensing of selected key atmospheric species. Applications include an early example of continuous vehicle emission measurements with a mobile CO2-laser PAS system [1]. The fast analysis of C1-C4 alkanes at sub-ppm concentrations in gas mixtures is of great interest for the petrochemical industry and was recently achieved with a new type of mid-infrared diode-pumped piezoelectrically tuned lead salt vertical external cavity surface emitting laser (VECSEL) [2]. Another example concerns measurements on short-lived species like nitrous acid (HONO) with a QCL-based QEPAS system where the small gas sampling volume and hence short gas residence time are of particular importance [3]. A true analysis of gas mixtures has been performed with a widely tunable DFG system in a medical application that could also be adapted to atmospheric species [4]. It is demonstrated that a laser-based narrowband system with broad tunability combined with an appropriate detection scheme is feasible for the chemical analysis of multi-component gas mixtures even with an a priori unknown composition. Most recent examples will further confirm the great potential of infrared laser-based devices for trace species sensing. References 1. D. Marinov and M.W. Sigrist: "Monitoring of road-traffic emission with mobile photoacoustic system", Photochem. and Photobiol. Sciences 2, 774-778 (2003) 2. J.M. Rey, M. Fill, F. Felder and M.W. Sigrist: "Broadly tunable mid-infrared VECSEL for multiple components hydrocarbons gas sensing", Appl. Phys. B 117, 935-939 (2014) 3. H. Yi, R. Maamary, X. Gao, M.W. Sigrist, E. Fertein, and W. Chen: "Short-lived species detection of nitrous acid by external-cavity quantum cascade laser based quartz-enhanced photoacoustic absorption spectroscopy", Appl. Phys. Lett. 106, 101109 (2015) 4. M. Gianella and M.W. Sigrist: "Chemical Analysis of Surgical Smoke by Infrared Laser Spectroscopy", Appl. Phys. B 109, 485-496 (2012)

All sky imaging observations in visible and infrared waveband for validation of satellite cloud and aerosol products

NASA Astrophysics Data System (ADS)

Lu, Daren; Huo, Juan; Zhang, W.; Liu, J.

A series of satellite sensors in visible and infrared wavelengths have been successfully operated on board a number of research satellites, e.g. NOAA/AVHRR, the MODIS onboard Terra and Aqua, etc. A number of cloud and aerosol products are produced and released in recent years. However, the validation of the product quality and accuracy are still a challenge to the atmospheric remote sensing community. In this paper, we suggest a ground based validation scheme for satellite-derived cloud and aerosol products by using combined visible and thermal infrared all sky imaging observations as well as surface meteorological observations. In the scheme, a visible digital camera with a fish-eye lens is used to continuously monitor the all sky with the view angle greater than 180 deg. The digital camera system is calibrated for both its geometry and radiance (broad blue, green, and red band) so as to a retrieval method can be used to detect the clear and cloudy sky spatial distribution and their temporal variations. A calibrated scanning thermal infrared thermometer is used to monitor the all sky brightness temperature distribution. An algorithm is developed to detect the clear and cloudy sky as well as cloud base height by using sky brightness distribution and surface temperature and humidity as input. Based on these composite retrieval of clear and cloudy sky distribution, it can be used to validate the satellite retrievals in the sense of real-simultaneous comparison and statistics, respectively. What will be presented in this talk include the results of the field observations and comparisons completed in Beijing (40 deg N, 116.5 deg E) in year 2003 and 2004. This work is supported by NSFC grant No. 4002700, and MOST grant No 2001CCA02200

Magnetic Viruses: Utilizing Self-Assembly for Biomedical Applications

NASA Astrophysics Data System (ADS)

Hoffmann, Axel

2006-03-01

Magnetic nanoparticles coated with biochemical surfactants have emerged recently as an important component for enabling many biological and medical applications. We implemented a biotemplating approach to create such magnetic nanoparticles by utilizing native protein capsid shells derived in high yield from the T7 bacteriophage virus. The magnetic nanoparticles are grown via bio-mineralization reactions inside of hollowed-out capsids that retain their original chemical recognition properties. The resultant ``magnetic viruses'' are uniform in geometry, physical properties, and biochemical functionality. This makes these viruses ideally suited for many biomedical applications among which we investigated specifically a novel sensing scheme for target recognition based on Brownian relaxation. For this scheme we use the ac-susceptibility of the functionalized magnetic nanoparticles suspended in liquid. Upon binding the target of interest to the particles, their Brownian relaxation time is modified, which is readily detected by a change of the frequency dependence of the magnetic susceptibility. This scheme has several advantages; (i) it requires only one binding event for sensing; (ii) there is a useful signal both in the absence and presence of the target; (iii) the signal contains information about the size of the target besides the biochemical affinity; and (iv) since the binding modifies the magnetic susceptibility of the magnetic particles there is no need for removing unbound labels. C. Liu, S.-H. Chung, Q. Jin, A. Sutton, F. Yan, B. K. Kay, S. D. Bader, L. Makowski, and L. Chen, J. Magn. Magn. Mater, in press. S.H. Chung, A. Hoffmann, S. D. Bader, C. Liu, B. Kay, L. Makowski, and L. Chen, Appl. Phys. Lett. 85, 2971 (2004) ; S. H. Chung, A. Hoffmann, K. Guslienko, S. D. Bader, C. Liu, B. Kay, L. Makowski, and L. Chen, J. Appl. Phys. 97, 10R101 (2005).

Cluster-based single-sink wireless sensor networks and passive optical network converged network incorporating sideband modulation schemes

NASA Astrophysics Data System (ADS)

Kumar, Love; Sharma, Vishal; Singh, Amarpal

2018-02-01

Wireless sensor networks have tremendous applications, such as civil, military, and environmental monitoring. In most of the applications, sensor data are required to be propagated over the internet/core networks, which result in backhaul setback. Subsequently, there is a necessity to backhaul the sensed information of such networks together with prolonging of the transmission link. Passive optical network (PON) is next-generation access technology emerging as a potential candidate for convergence of the sensed data to the core system. Earlier, the work with single-optical line terminal-PON was demonstrated and investigated merely analytically. This work is an attempt to demonstrate a practical model of a bidirectional single-sink wireless sensor network-PON converged network in which the collected data from cluster heads are transmitted over PON networks. Further, modeled converged structure has been investigated under the influence of double, single, and tandem sideband modulation schemes incorporating a corresponding phase-delay to the sensor data entities that have been overlooked in the past. The outcome illustrates the successful fusion of the sensor data entities over PON with acceptable bit error rate and signal to noise ratio serving as a potential development in the sphere of such converged networks. It has also been revealed that the data entities treated with tandem side band modulation scheme help in improving the performance of the converged structure. Additionally, analysis for uplink transmission reported with queue theory in terms of time cycle, average time delay, data packet generation, and bandwidth utilization. An analytical analysis of proposed converged network shows that average time delay for data packet transmission is less as compared with time cycle delay.

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

2017-12-01

The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks, RNVCF shows significant overestimation in summer, perhaps due to RNVCF ignores the growing characteristics of vegetation (mainly grass) in these two regions. Our results demonstrate that VCF schemes have significant influence on LSM performance, and indicate that it is important to consider vegetation growing characteristics in VCF schemes for different LCs.

Wave Scattering and Sensing Strategies in Intermittent Terrestrial Environments

DTIC Science & Technology

2008-01-01

objects and signal coherence (a measure of sig- nal randomness, which usually determines the sensing sys- tem performance) is strongly degraded...3.1 What are Quasi-Wavelets? Until this point, the objects in the cascades have not been explicitly described. We now associate them with wavelet, or...unsupervised clas- sification scheme used the intensity of the lidar returns to map the material types. 4.2 Seismic Measurement Procedure Thirty-six

PAVS: A New Privacy-Preserving Data Aggregation Scheme for Vehicle Sensing Systems.

PubMed

Xu, Chang; Lu, Rongxing; Wang, Huaxiong; Zhu, Liehuang; Huang, Cheng

2017-03-03

Air pollution has become one of the most pressing environmental issues in recent years. According to a World Health Organization (WHO) report, air pollution has led to the deaths of millions of people worldwide. Accordingly, expensive and complex air-monitoring instruments have been exploited to measure air pollution. Comparatively, a vehicle sensing system (VSS), as it can be effectively used for many purposes and can bring huge financial benefits in reducing high maintenance and repair costs, has received considerable attention. However, the privacy issues of VSS including vehicles' location privacy have not been well addressed. Therefore, in this paper, we propose a new privacy-preserving data aggregation scheme, called PAVS, for VSS. Specifically, PAVS combines privacy-preserving classification and privacy-preserving statistics on both the mean E(·) and variance Var(·), which makes VSS more promising, as, with minimal privacy leakage, more vehicles are willing to participate in sensing. Detailed analysis shows that the proposed PAVS can achieve the properties of privacy preservation, data accuracy and scalability. In addition, the performance evaluations via extensive simulations also demonstrate its efficiency.

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

NASA Technical Reports Server (NTRS)

Molthan, A. L.; Haynes, J. A.; Jedlovec, G. L.; Lapenta, W. M.

2009-01-01

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Odor-Sensing System to Support Social Participation of People Suffering from Incontinence

PubMed Central

Ortiz Pérez, Alvaro; Kallfaß-de Frenes, Vera; Filbert, Alexander; Kneer, Janosch; Bierer, Benedikt; Held, Pirmin; Klein, Philipp; Wöllenstein, Jürgen; Benyoucef, Dirk; Kallfaß, Sigrid; Mescheder, Ulrich; Palzer, Stefan

2016-01-01

This manuscript describes the design considerations, implementation, and laboratory validation of an odor sensing module whose purpose is to support people that suffer from incontinence. Because of the requirements expressed by the affected end-users the odor sensing unit is realized as a portable accessory that may be connected to any pre-existing smart device. We have opted for a low-cost, low-power consuming metal oxide based gas detection approach to highlight the viability of developing an inexpensive yet helpful odor recognition technology. The system consists of a hotplate employing, inkjet-printed p-type semiconducting layers of copper(II) oxide, and chromium titanium oxide. Both functional layers are characterized with respect to their gas-sensitive behavior towards humidity, ammonia, methylmercaptan, and dimethylsulfide and we demonstrate detection limits in the parts-per-billion range for the two latter gases. Employing a temperature variation scheme that reads out the layer’s resistivity in a steady-state, we use each sensor chip as a virtual array. With this setup, we demonstrate the feasibility of detecting odors associated with incontinence. PMID:28036081

Odor-Sensing System to Support Social Participation of People Suffering from Incontinence.

PubMed

Ortiz Pérez, Alvaro; Kallfaß-de Frenes, Vera; Filbert, Alexander; Kneer, Janosch; Bierer, Benedikt; Held, Pirmin; Klein, Philipp; Wöllenstein, Jürgen; Benyoucef, Dirk; Kallfaß, Sigrid; Mescheder, Ulrich; Palzer, Stefan

2016-12-29

This manuscript describes the design considerations, implementation, and laboratory validation of an odor sensing module whose purpose is to support people that suffer from incontinence. Because of the requirements expressed by the affected end-users the odor sensing unit is realized as a portable accessory that may be connected to any pre-existing smart device. We have opted for a low-cost, low-power consuming metal oxide based gas detection approach to highlight the viability of developing an inexpensive yet helpful odor recognition technology. The system consists of a hotplate employing, inkjet-printed p-type semiconducting layers of copper(II) oxide, and chromium titanium oxide. Both functional layers are characterized with respect to their gas-sensitive behavior towards humidity, ammonia, methylmercaptan, and dimethylsulfide and we demonstrate detection limits in the parts-per-billion range for the two latter gases. Employing a temperature variation scheme that reads out the layer's resistivity in a steady-state, we use each sensor chip as a virtual array. With this setup, we demonstrate the feasibility of detecting odors associated with incontinence.

Interferometer design and controls for pulse stacking in high power fiber lasers

NASA Astrophysics Data System (ADS)

Wilcox, Russell; Yang, Yawei; Dahlen, Dar; Xu, Yilun; Huang, Gang; Qiang, Du; Doolittle, Lawrence; Byrd, John; Leemans, Wim; Ruppe, John; Zhou, Tong; Sheikhsofla, Morteza; Nees, John; Galvanauskas, Almantas; Dawson, Jay; Chen, Diana; Pax, Paul

2017-03-01

In order to develop a design for a laser-plasma accelerator (LPA) driver, we demonstrate key technologies that enable fiber lasers to produce high energy, ultrafast pulses. These technologies must be scalable, and operate in the presence of thermal drift, acoustic noise, and other perturbations typical of an operating system. We show that coherent pulse stacking (CPS), which requires optical interferometers, can be made robust by image-relaying, multipass optical cavities, and by optical phase control schemes that sense pulse train amplitudes from each cavity. A four-stage pulse stacking system using image-relaying cavities is controlled for 14 hours using a pulse-pattern sensing algorithm. For coherent addition of simultaneous ultrafast pulses, we introduce a new scheme using diffractive optics, and show experimentally that four pulses can be added while a preserving pulse width of 128 fs.

An Entropy-Based Approach to Nonlinear Stability

NASA Technical Reports Server (NTRS)

Merriam, Marshal L.

1989-01-01

Many numerical methods used in computational fluid dynamics (CFD) incorporate an artificial dissipation term to suppress spurious oscillations and control nonlinear instabilities. The same effect can be accomplished by using upwind techniques, sometimes augmented with limiters to form Total Variation Diminishing (TVD) schemes. An analysis based on numerical satisfaction of the second law of thermodynamics allows many such methods to be compared and improved upon. A nonlinear stability proof is given for discrete scalar equations arising from a conservation law. Solutions to such equations are bounded in the L sub 2 norm if the second law of thermodynamics is satisfied in a global sense over a periodic domain. It is conjectured that an analogous statement is true for discrete equations arising from systems of conservation laws. Analysis and numerical experiments suggest that a more restrictive condition, a positive entropy production rate in each cell, is sufficient to exclude unphysical phenomena such as oscillations and expansion shocks. Construction of schemes which satisfy this condition is demonstrated for linear and nonlinear wave equations and for the one-dimensional Euler equations.

An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

PubMed Central

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-01-01

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

PubMed

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-02-11

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

Bond graph modelling of multibody dynamics and its symbolic scheme

NASA Astrophysics Data System (ADS)

Kawase, Takehiko; Yoshimura, Hiroaki

A bond graph method of modeling multibody dynamics is demonstrated. Specifically, a symbolic generation scheme which fully utilizes the bond graph information is presented. It is also demonstrated that structural understanding and representation in bond graph theory is quite powerful for the modeling of such large scale systems, and that the nonenergic multiport of junction structure, which is a multiport expression of the system structure, plays an important role, as first suggested by Paynter. The principal part of the proposed symbolic scheme, that is, the elimination of excess variables, is done through tearing and interconnection in the sense of Kron using newly defined causal and causal coefficient arrays.

Laboratory validation of MEMS-based sensors for post-earthquake damage assessment image

NASA Astrophysics Data System (ADS)

Pozzi, Matteo; Zonta, Daniele; Santana, Juan; Colin, Mikael; Saillen, Nicolas; Torfs, Tom; Amditis, Angelos; Bimpas, Matthaios; Stratakos, Yorgos; Ulieru, Dumitru; Bairaktaris, Dimitirs; Frondistou-Yannas, Stamatia; Kalidromitis, Vasilis

2011-04-01

The evaluation of seismic damage is today almost exclusively based on visual inspection, as building owners are generally reluctant to install permanent sensing systems, due to their high installation, management and maintenance costs. To overcome this limitation, the EU-funded MEMSCON project aims to produce small size sensing nodes for measurement of strain and acceleration, integrating Micro-Electro-Mechanical Systems (MEMS) based sensors and Radio Frequency Identification (RFID) tags in a single package that will be attached to reinforced concrete buildings. To reduce the impact of installation and management, data will be transmitted to a remote base station using a wireless interface. During the project, sensor prototypes were produced by assembling pre-existing components and by developing ex-novo miniature devices with ultra-low power consumption and sensing performance beyond that offered by sensors available on the market. The paper outlines the device operating principles, production scheme and working at both unit and network levels. It also reports on validation campaigns conducted in the laboratory to assess system performance. Accelerometer sensors were tested on a reduced scale metal frame mounted on a shaking table, back to back with reference devices, while strain sensors were embedded in both reduced and full-scale reinforced concrete specimens undergoing increasing deformation cycles up to extensive damage and collapse. The paper assesses the economical sustainability and performance of the sensors developed for the project and discusses their applicability to long-term seismic monitoring.

Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

DOE PAGES

Sarna, Karolina; Russchenberg, Herman W. J.

2016-03-14

A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius ( r e) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m -2 wide. For every LWP bin we present the correlation coefficient between ln r e and ln ATB, as well as ACI r (defined as ACI r = -d ln r e d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACI r are in the range 0.01–0.1. In conclusion, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

A unified framework for image retrieval using keyword and visual features.

PubMed

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

Adjacency Matrix-Based Transmit Power Allocation Strategies in Wireless Sensor Networks

PubMed Central

Consolini, Luca; Medagliani, Paolo; Ferrari, Gianluigi

2009-01-01

In this paper, we present an innovative transmit power control scheme, based on optimization theory, for wireless sensor networks (WSNs) which use carrier sense multiple access (CSMA) with collision avoidance (CA) as medium access control (MAC) protocol. In particular, we focus on schemes where several remote nodes send data directly to a common access point (AP). Under the assumption of finite overall network transmit power and low traffic load, we derive the optimal transmit power allocation strategy that minimizes the packet error rate (PER) at the AP. This approach is based on modeling the CSMA/CA MAC protocol through a finite state machine and takes into account the network adjacency matrix, depending on the transmit power distribution and determining the network connectivity. It will be then shown that the transmit power allocation problem reduces to a convex constrained minimization problem. Our results show that, under the assumption of low traffic load, the power allocation strategy, which guarantees minimal delay, requires the maximization of network connectivity, which can be equivalently interpreted as the maximization of the number of non-zero entries of the adjacency matrix. The obtained theoretical results are confirmed by simulations for unslotted Zigbee WSNs. PMID:22346705

Characteristics of several NIR tuneable diode lasers for spectroscopic based gas sensing: a comparison.

PubMed

Weldon, Vincent; McInerney, David; Phelan, Richard; Lynch, Michael; Donegan, John

2006-04-01

Tuneable laser diodes were characterized and compared for use as tuneable sources in gas absorption spectroscopy. Specifically, the characteristics of monolithic widely tuneable single frequency lasers, such as sampled grating distributed Bragg reflector laser and modulated grating Y-branch laser diodes, recently developed for optical communications, with operating wavelengths in the 1,520 nm

Blind Compressed Sensing Enables 3-Dimensional Dynamic Free Breathing Magnetic Resonance Imaging of Lung Volumes and Diaphragm Motion.

PubMed

Bhave, Sampada; Lingala, Sajan Goud; Newell, John D; Nagle, Scott K; Jacob, Mathews

2016-06-01

The objective of this study was to increase the spatial and temporal resolution of dynamic 3-dimensional (3D) magnetic resonance imaging (MRI) of lung volumes and diaphragm motion. To achieve this goal, we evaluate the utility of the proposed blind compressed sensing (BCS) algorithm to recover data from highly undersampled measurements. We evaluated the performance of the BCS scheme to recover dynamic data sets from retrospectively and prospectively undersampled measurements. We also compared its performance against that of view-sharing, the nuclear norm minimization scheme, and the l1 Fourier sparsity regularization scheme. Quantitative experiments were performed on a healthy subject using a fully sampled 2D data set with uniform radial sampling, which was retrospectively undersampled with 16 radial spokes per frame to correspond to an undersampling factor of 8. The images obtained from the 4 reconstruction schemes were compared with the fully sampled data using mean square error and normalized high-frequency error metrics. The schemes were also compared using prospective 3D data acquired on a Siemens 3 T TIM TRIO MRI scanner on 8 healthy subjects during free breathing. Two expert cardiothoracic radiologists (R1 and R2) qualitatively evaluated the reconstructed 3D data sets using a 5-point scale (0-4) on the basis of spatial resolution, temporal resolution, and presence of aliasing artifacts. The BCS scheme gives better reconstructions (mean square error = 0.0232 and normalized high frequency = 0.133) than the other schemes in the 2D retrospective undersampling experiments, producing minimally distorted reconstructions up to an acceleration factor of 8 (16 radial spokes per frame). The prospective 3D experiments show that the BCS scheme provides visually improved reconstructions than the other schemes do. The BCS scheme provides improved qualitative scores over nuclear norm and l1 Fourier sparsity regularization schemes in the temporal blurring and spatial blurring categories. The qualitative scores for aliasing artifacts in the images reconstructed by nuclear norm scheme and BCS scheme are comparable.The comparisons of the tidal volume changes also show that the BCS scheme has less temporal blurring as compared with the nuclear norm minimization scheme and the l1 Fourier sparsity regularization scheme. The minute ventilation estimated by BCS for tidal breathing in supine position (4 L/min) and the measured supine inspiratory capacity (1.5 L) is in good correlation with the literature. The improved performance of BCS can be explained by its ability to efficiently adapt to the data, thus providing a richer representation of the signal. The feasibility of the BCS scheme was demonstrated for dynamic 3D free breathing MRI of lung volumes and diaphragm motion. A temporal resolution of ∼500 milliseconds, spatial resolution of 2.7 × 2.7 × 10 mm, with whole lung coverage (16 slices) was achieved using the BCS scheme.

Fiber optic distributed temperature sensing for fire source localization

NASA Astrophysics Data System (ADS)

Sun, Miao; Tang, Yuquan; Yang, Shuang; Sigrist, Markus W.; Li, Jun; Dong, Fengzhong

2017-08-01

A method for localizing a fire source based on a distributed temperature sensor system is proposed. Two sections of optical fibers were placed orthogonally to each other as the sensing elements. A tray of alcohol was lit to act as a fire outbreak in a cabinet with an uneven ceiling to simulate a real scene of fire. Experiments were carried out to demonstrate the feasibility of the method. Rather large fluctuations and systematic errors with respect to predicting the exact room coordinates of the fire source caused by the uneven ceiling were observed. Two mathematical methods (smoothing recorded temperature curves and finding temperature peak positions) to improve the prediction accuracy are presented, and the experimental results indicate that the fluctuation ranges and systematic errors are significantly reduced. The proposed scheme is simple and appears reliable enough to locate a fire source in large spaces.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

A long-range and long-life telemetry data-acquisition system for heart rate and multiple body temperatures from free-ranging animals

NASA Technical Reports Server (NTRS)

Lund, G. F.; Westbrook, R. M.; Fryer, T. B.; Miranda, R. F.

1979-01-01

The system includes an implantable transmitter, external receiver-retransmitter collar, and a microprocessor-controlled demodulator. The size of the implant is suitable for animals with body weights of a few kilograms or more; further size reduction of the implant is possible. The ECG is sensed by electrodes designed for internal telemetry and to reduce movement artifacts. The R-wave characteristics are then specifically selected to trigger a short radio frequency pulse. Temperatures are sensed at desired locations by thermistors and then, based on a heartbeat counter, transmitted intermittently via pulse interval modulation. This modulation scheme includes first and last calibration intervals for a reference by ratios with the temperature intervals to achieve good accuracy even over long periods. Pulse duration and pulse sequencing are used to discriminate between heart rate and temperature pulses as well as RF interference.

An adaptive image sparse reconstruction method combined with nonlocal similarity and cosparsity for mixed Gaussian-Poisson noise removal

NASA Astrophysics Data System (ADS)

Chen, Yong-fei; Gao, Hong-xia; Wu, Zi-ling; Kang, Hui

2018-01-01

Compressed sensing (CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation (NCSR), in terms of both visual results and quantitative measures.

Terahertz Active Photonic Crystals for Condensed Gas Sensing

PubMed Central

Benz, Alexander; Deutsch, Christoph; Brandstetter, Martin; Andrews, Aaron M.; Klang, Pavel; Detz, Hermann; Schrenk, Werner; Strasser, Gottfried; Unterrainer, Karl

2011-01-01

The terahertz (THz) spectral region, covering frequencies from 1 to 10 THz, is highly interesting for chemical sensing. The energy of rotational and vibrational transitions of molecules lies within this frequency range. Therefore, chemical fingerprints can be derived, allowing for a simple detection scheme. Here, we present an optical sensor based on active photonic crystals (PhCs), i.e., the pillars are fabricated directly from an active THz quantum-cascade laser medium. The individual pillars are pumped electrically leading to laser emission at cryogenic temperatures. There is no need to couple light into the resonant structure because the PhC itself is used as the light source. An injected gas changes the resonance condition of the PhC and thereby the laser emission frequency. We achieve an experimental frequency shift of 10−3 times the center lasing frequency. The minimum detectable refractive index change is 1.6 × 10−5 RIU. PMID:22163939

The investigation of an LSPR refractive index sensor based on periodic gold nanorings array

NASA Astrophysics Data System (ADS)

Wang, Shuai; Sun, Xiaohong; Ding, Mingjie; Peng, Gangding; Qi, Yongle; Wang, Yile; Ren, Jie

2018-01-01

An on-chip refractive index (RI) sensor, which is based on the localized surface plasmon resonance (LSPR) of periodic gold nanorings array, is presented. The structure parameters and performance of LSPR-based sensors are optimized by analyzing and comparing the LSPR extinction spectra. The mechanism of the enhancement of plasma resonance in a ring array is discussed by the simulation results. A feasible preparation scheme of the nanorings array is proposed and verified by coating a gold film and etching on the photonic crystals. Based on the optimum sensing structure, an RI sensor is constructed with a RI sensitivity of 577 nm/refractive index unit (RIU) and a figure of merit (FOM) of 6.1, which is approximately 2 times that of previous reports.

Diagnostic grade wireless ECG monitoring.

PubMed

Garudadri, Harinath; Chi, Yuejie; Baker, Steve; Majumdar, Somdeb; Baheti, Pawan K; Ballard, Dan

2011-01-01

In remote monitoring of Electrocardiogram (ECG), it is very important to ensure that the diagnostic integrity of signals is not compromised by sensing artifacts and channel errors. It is also important for the sensors to be extremely power efficient to enable wearable form factors and long battery life. We present an application of Compressive Sensing (CS) as an error mitigation scheme at the application layer for wearable, wireless sensors in diagnostic grade remote monitoring of ECG. In our previous work, we described an approach to mitigate errors due to packet losses by projecting ECG data to a random space and recovering a faithful representation using sparse reconstruction methods. Our contributions in this work are twofold. First, we present an efficient hardware implementation of random projection at the sensor. Second, we validate the diagnostic integrity of the reconstructed ECG after packet loss mitigation. We validate our approach on MIT and AHA databases comprising more than 250,000 normal and abnormal beats using EC57 protocols adopted by the Food and Drug Administration (FDA). We show that sensitivity and positive predictivity of a state-of-the-art ECG arrhythmia classifier is essentially invariant under CS based packet loss mitigation for both normal and abnormal beats even at high packet loss rates. In contrast, the performance degrades significantly in the absence of any error mitigation scheme, particularly for abnormal beats such as Ventricular Ectopic Beats (VEB).

ESA GlobPermafrost - mapping the extent and thermal state of permafrost with satellite data

NASA Astrophysics Data System (ADS)

Westermann, Sebastian; Obu, Jaroslav; Aalstad, Kristoffer; Bartsch, Annett; Kääb, Andreas

2017-04-01

The ESA GlobPermafrost initiative (2016-2019) aims at developing, validating and implementing information products based on remote sensing data to support permafrost research. Mapping of permafrost extent and ground temperatures is conducted at 1 km scale using remotely sensed land surface temperatures (MODIS), snow water equivalent (ESA GlobSnow) and land cover (ESA CCI landcover) in conjunction with a simple ground thermal model (CryoGrid 1). The spatial variability of the ground thermal regime at scales smaller than the model resolution is explicitly taken into account by considering an ensemble of realizations with different model properties. The approach has been tested for the unglacierized land areas in the North Atlantic region, an area of more than 5 million km2. The results have been compared to in-situ temperature measurements in more than 100 boreholes, indicating an accuracy of approximately 2.5°C. Within GlobPermafrost, the scheme will be extended to cover the entire the circum-polar permafrost area. Here, we provide an evaluation of the first prototype covering "lowland" permafrost areas north of 40° latitude (available on www.globpermafrost.info in early 2017). We give a feasibility assessment for extending the scheme to global scale, including both mountain and Antarctic permafrost. Finally, we discuss the potential and limitations for estimating changes of permafrost extent on decadal timescales.

Vapor sensing using polymer/carbon black composites in the percolative conduction regime.

PubMed

Sisk, Brian C; Lewis, Nathan S

2006-08-29

To investigate the behavior of chemiresistive vapor sensors operating below or around the percolation threshold, chemiresistors have been formed from composites of insulating organic polymers and low mass fractions of conductive carbon black (CB, 1-12% w/w). Such sensors produced extremely large relative differential resistance changes above certain threshold vapor concentrations. At high analyte partial pressures, these sensors exhibited better signal/noise characteristics and were typically less mutually correlated in their vapor response properties than composites formed using higher mass fractions of CB in the same set of polymer sorption layers. The responses of the low-mass-fraction CB sensors were, however, less repeatable, and their nonlinear response as a function of analyte concentration required more complicated calibration schemes to identify and quantify analyte vapors to compensate for drift of a sensor array and to compensate for variability in response between sensor arrays. Because of their much larger response signals, the low-mass-fraction CB sensors might be especially well suited for use with low-precision analog-to-digital signal readout electronics. These sensors serve well as a complement to composites formed from higher mass fractions of CB and have yielded insight into the tradeoffs of signal-to-noise improvements vs complexity of signal processing algorithms necessitated by the use of nonlinearly responding detectors in array-based sensing schemes.

High accuracy demodulation for twin-grating based sensor network with hybrid TDM/FDM

NASA Astrophysics Data System (ADS)

Ai, Fan; Sun, Qizhen; Cheng, Jianwei; Luo, Yiyang; Yan, Zhijun; Liu, Deming

2017-04-01

We demonstrate a high accuracy demodulation platform with a tunable Fabry-Perot filter (TFF) for twin-grating based fiber optic sensing network with hybrid TDM/FDM. The hybrid TDM/FDM scheme can improve the spatial resolution to centimeter but increases the requirement of high spectrum resolution. To realize the demodulation of the complex twin-grating spectrum, we adopt the TFF demodulation method and compensate the environmental temperature change and nonlinear effect through calibration FBGs. The performance of the demodulation module is tested by a temperature experiment. Spectrum resolution of 1pm is realized with precision of 2.5pm while the environmental temperature of TFF changes 9.3°C.

Universal scheme for finite-probability perfect transfer of arbitrary multispin states through spin chains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Man, Zhong-Xiao, E-mail: zxman@mail.qfnu.edu.cn; An, Nguyen Ba, E-mail: nban@iop.vast.ac.vn; Xia, Yun-Jie, E-mail: yjxia@mail.qfnu.edu.cn

In combination with the theories of open system and quantum recovering measurement, we propose a quantum state transfer scheme using spin chains by performing two sequential operations: a projective measurement on the spins of ‘environment’ followed by suitably designed quantum recovering measurements on the spins of interest. The scheme allows perfect transfer of arbitrary multispin states through multiple parallel spin chains with finite probability. Our scheme is universal in the sense that it is state-independent and applicable to any model possessing spin–spin interactions. We also present possible methods to implement the required measurements taking into account the current experimental technologies.more » As applications, we consider two typical models for which the probabilities of perfect state transfer are found to be reasonably high at optimally chosen moments during the time evolution. - Highlights: • Scheme that can achieve perfect quantum state transfer is devised. • The scheme is state-independent and applicable to any spin-interaction models. • The scheme allows perfect transfer of arbitrary multispin states. • Applications to two typical models are considered in detail.« less

Engineered SOI slot waveguide ring resonator V-shape resonance combs for refraction index sensing up to 1300nm/RIU (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhang, Weiwei; Serna, Samuel; Le Roux, Xavier; Vivien, Laurent; Cassan, Eric

2016-05-01

Bio-detection based on CMOS technology boosts the miniaturization of detection systems and the success on highly efficient, robust, accurate, and low coast Lab-on-Chip detection schemes. Such on chip detection technologies have covered healthy related harmful gases, bio-chemical analytes, genetic micro RNA, etc. Their monitoring accuracy is mainly qualified in terms of sensitivity and limit of the detection (LOD) of the detection system. In this context, recently developed silicon on insulator (SOI) optical devices have displayed highly performant detection abilities that LOD could go beyond 10-8RIU and sensitivity could exceeds 103nm/RIU. The SOI integrated optical sensing devices include strip/slotted waveguide consisting in structures like Mach-Zehnder interferometers (MZI), ring resonators (RR), nano cavities, etc. Typically, hollow core RR and nano-cavities could exhibit higher sensitivity due to their optical mode confinement properties with a partial localization of the electric field in low index sensing regions than devices based on evanescent field tails outside of the optical cores. Furthermore, they also provide larger sensing areas for surface functionalization to reach higher sensitivities and lower LODs. The state of art of hollow core devices, either based on Bragg gratings formed from a slot waveguide cavity or photonic crystal slot cavities, show sensitivities (S) up to 400nm/RIU and Figure of Merit (FOM) around 3,000 in water environment, FOM being defined as the inverse of LOD and precisely as FOM=SQ/λ, with λ the resonance wavelength and Q the quality factor of the considered resonator. Such high achieved FOMs in nano cavities are mainly due to their large Q factors around 15,000. While for mostly used RR, which do not require particular design strategies, relatively low Q factors around 1800 in water are met and moderate sensitivities about 300nm/RIU are found. In this work, we present here a novel slot ring resonator design to make breakthrough of the performance of slot ring resonator sensing ability. Different from the normal sensing regime by monitoring one specific resonance (λres) peak shift, the proposed approach stems from the sensitivity of the RR critical coupling. The critical coupling peak is auto-selected out by matching the following condition: the ring resonator's round trip attenuation coefficient a(λ) being equal to the coupler self-coupling coefficient k(λ), thus resulting in the deepest extinction ratio (ER) among the spectrum RR comb. The obtained sensing comb, based on a V-shape spectrum envelop, is engineered by controlling a(λ) and k(λ) with opposite monotonicities. Both a(λ)and k(λ) are tuned to have a large dispersion along the wavelength, which means that |a(λ)-k(λ)| keeps rapidly increasing as λres is far away from λc, eliminating the resonance ER quickly down to 0. Experimentally, slot waveguide ring resonators with a radius of 50µm have been fabricated on a standard silicon platform with a Si thickness of 220nm, loaded by racetrack couplers with a straight coupling length of 20µm. Sensing experiments have been carried out by changing the top cladding material from a series of Cargille optical liquids with refraction index values ranging from 1.3 to 1.5. The Q factors of critical coupling resonances was monitored from 2,000 to 6,000, and measured wavelength shifts of this peak are from 1.41µm to 1.56µm. The maximum sensitivity of 1300nm/RIU is observed in the cladding index range 1.30-1.35. To conclude, a new sensing regime by tracking the critical coupling resonance λc of slot waveguide ring resonators is demonstrated. The reported sensitivity is up 1300nm/RIU around the water RI of 1.33, and the monitored sensing FOM is about 2300, which is very close to the FOM values achieved from nanobeam cavities. This work can thus contribute to future integrated optical sensing schemes based on slot RRs.

Stabilized linear semi-implicit schemes for the nonlocal Cahn-Hilliard equation

NASA Astrophysics Data System (ADS)

Du, Qiang; Ju, Lili; Li, Xiao; Qiao, Zhonghua

2018-06-01

Comparing with the well-known classic Cahn-Hilliard equation, the nonlocal Cahn-Hilliard equation is equipped with a nonlocal diffusion operator and can describe more practical phenomena for modeling phase transitions of microstructures in materials. On the other hand, it evidently brings more computational costs in numerical simulations, thus efficient and accurate time integration schemes are highly desired. In this paper, we propose two energy-stable linear semi-implicit methods with first and second order temporal accuracies respectively for solving the nonlocal Cahn-Hilliard equation. The temporal discretization is done by using the stabilization technique with the nonlocal diffusion term treated implicitly, while the spatial discretization is carried out by the Fourier collocation method with FFT-based fast implementations. The energy stabilities are rigorously established for both methods in the fully discrete sense. Numerical experiments are conducted for a typical case involving Gaussian kernels. We test the temporal convergence rates of the proposed schemes and make a comparison of the nonlocal phase transition process with the corresponding local one. In addition, long-time simulations of the coarsening dynamics are also performed to predict the power law of the energy decay.

Photon Shot Noise Limited Radio Frequency Electric Field Sensing Using Rydberg Atoms in Vapor Cells

NASA Astrophysics Data System (ADS)

Kumar, Santosh; Jahangiri, Akbar J.; Fan, Haoquan; Kuebler, Harald; Shaffer, James P.

2017-04-01

We report Rydberg atom-based radio frequency (RF) electrometry measurements at a sensitivity limited by probe laser photon shot noise. By utilizing the phenomena of electromagnetically induced transparency (EIT) in room temperature atomic vapor cells, Rydberg atoms can be used for absolute electric field measurements that significantly surpass conventional methods in utility, sensitivity and accuracy. We show that by using a Mach-Zehnder interferometer with homodyne detection or using frequency modulation spectroscopy with active control of residual amplitude modulation we can achieve a RF electric field detection sensitivity of 3 μVcm-1Hz/2. The sensitivity is limited by photon shot noise on the detector used to readout the probe laser of the EIT scheme. We suggest a new multi-photon scheme that can mitigate the effect of photon shot noise. The multi-photon approach allows an increase in probe laser power without decreasing atomic coherence times that result from collisions caused by an increase in Rydberg atom excitation. The multi-photon scheme also reduces Residual Doppler broadening enabling more accurate measurements to be carried out. This work is supported by DARPA, and NRO.

Rotation Rate Sensing via Magnetostatic Surface Wave Propagation on a Thick Yig Ring.

DTIC Science & Technology

1979-12-03

Introduction . . . . . . . . . . . 1 Background . . . . . . . . I Statement of the Problem. o o . 4 Plan of Attack. o. . o o o • 4 Sequence of...crystal growth process. It was subsequently suggested that the thin film disfiguration problem could be avoided by ma- chining the desired ring...sensor provide any practical advantages that would make it a better choice over current rate sensing schemes? Plan of Attack This thesis concerns itself

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

NASA Astrophysics Data System (ADS)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

Total ozone column derived from GOME and SCIAMACHY using KNMI retrieval algorithms: Validation against Brewer measurements at the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Antón, M.; Kroon, M.; López, M.; Vilaplana, J. M.; Bañón, M.; van der A, R.; Veefkind, J. P.; Stammes, P.; Alados-Arboledas, L.

2011-11-01

This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.

Precision Sensing by Two Opposing Gradient Sensors: How Does Escherichia coli Find its Preferred pH Level?

PubMed Central

Hu, Bo; Tu, Yuhai

2013-01-01

It is essential for bacteria to find optimal conditions for their growth and survival. The optimal levels of certain environmental factors (such as pH and temperature) often correspond to some intermediate points of the respective gradients. This requires the ability of bacteria to navigate from both directions toward the optimum location and is distinct from the conventional unidirectional chemotactic strategy. Remarkably, Escherichia coli cells can perform such a precision sensing task in pH taxis by using the same chemotaxis machinery, but with opposite pH responses from two different chemoreceptors (Tar and Tsr). To understand bacterial pH sensing, we developed an Ising-type model for a mixed cluster of opposing receptors based on the push-pull mechanism. Our model can quantitatively explain experimental observations in pH taxis for various mutants and wild-type cells. We show how the preferred pH level depends on the relative abundance of the competing sensors and how the sensory activity regulates the behavioral response. Our model allows us to make quantitative predictions on signal integration of pH and chemoattractant stimuli. Our study reveals two general conditions and a robust push-pull scheme for precision sensing, which should be applicable in other adaptive sensory systems with opposing gradient sensors. PMID:23823247

Multiplexed EFPI sensors with ultra-high resolution

NASA Astrophysics Data System (ADS)

Ushakov, Nikolai; Liokumovich, Leonid

2014-05-01

An investigation of performance of multiplexed displacement sensors based on extrinsic Fabry-Perot interferometers has been carried out. We have considered serial and parallel configurations and analyzed the issues and advantages of the both. We have also extended the previously developed baseline demodulation algorithm for the case of a system of multiplexed sensors. Serial and parallel multiplexing schemes have been experimentally implemented with 3 and 4 sensing elements, respectively. For both configurations the achieved baseline standard deviations were between 30 and 200 pm, which is, to the best of our knowledge, more than an order less than any other multiplexed EFPI resolution ever reported.

Robotic situational awareness of actions in human teaming

NASA Astrophysics Data System (ADS)

Tahmoush, Dave

2015-06-01

When robots can sense and interpret the activities of the people they are working with, they become more of a team member and less of just a piece of equipment. This has motivated work on recognizing human actions using existing robotic sensors like short-range ladar imagers. These produce three-dimensional point cloud movies which can be analyzed for structure and motion information. We skeletonize the human point cloud and apply a physics-based velocity correlation scheme to the resulting joint motions. The twenty actions are then recognized using a nearest-neighbors classifier that achieves good accuracy.

Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping

2018-03-01

This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.

Estimation of Transmittance of Solar Radiation in the Visible Domain Based on Remote Sensing: Evaluation of Models Using In Situ Data

NASA Astrophysics Data System (ADS)

Zoffoli, M. Laura; Lee, Zhongping; Ondrusek, Michael; Lin, Junfang; Kovach, Charles; Wei, Jianwei; Lewis, Marlon

2017-11-01

The transmittance of solar radiation in the oceanic water column plays an important role in heat transfer and photosynthesis, with implications for the global carbon cycle, global circulation, and climate. Globally, the transmittance of solar radiation in the visible domain (˜400-700 nm) (TRVIS) through the water column, which determines the vertical distribution of visible light, has to be based on remote sensing products. There are models centered on chlorophyll-a (Chl) concentration or Inherent Optical Properties (IOPs) as both can be derived from ocean color measurements. We present evaluations of both schemes with field data from clear oceanic and from coastal waters. Here five models were evaluated: (1) Morel and Antoine (1994) (MA94), (2) Ohlmann and Siegel (2000) (OS00), (3) Murtugudde et al. (2002) (MU02), (4) Manizza et al. (2005) (MA05), and (5) Lee et al. ([Lee, Z., 2005]) (IOPs05), where the first four are Chl-based and the last one is IOPs-based, with all inputs derived from remote sensing reflectance. It is found that the best performing model is the IOPs05, with Unbiased Absolute Percent Difference (UAPD) ˜23%, while Chl-based models show higher uncertainties (UAPD for MA94: ˜54%, OS00: ˜133%, MU02: ˜56%, and MA05: ˜39%). The IOPs-based model was insensitive to the type of water, allowing it to be applied in most marine environments; whereas some of the Chl-based models (MU02 and MA05) show much higher sensitivities in coastal turbid waters (higher Chl waters). These results highlight the applicablity of using IOPs products for such applications.

Radio/FADS/IMU integrated navigation for Mars entry

NASA Astrophysics Data System (ADS)

Jiang, Xiuqiang; Li, Shuang; Huang, Xiangyu

2018-03-01

Supposing future orbiting and landing collaborative exploration mission as the potential project background, this paper addresses the issue of Mars entry integrated navigation using radio beacon, flush air data sensing system (FADS), and inertial measurement unit (IMU). The range and Doppler information sensed from an orbiting radio beacon, the dynamic pressure and heating data sensed from flush air data sensing system, and acceleration and attitude angular rate outputs from an inertial measurement unit are integrated in an unscented Kalman filter to perform state estimation and suppress the system and measurement noise. Computer simulations show that the proposed integrated navigation scheme can enhance the navigation accuracy, which enables precise entry guidance for the given Mars orbiting and landing collaborative exploration mission.

High-performance compression and double cryptography based on compressive ghost imaging with the fast Fourier transform

NASA Astrophysics Data System (ADS)

Leihong, Zhang; Zilan, Pan; Luying, Wu; Xiuhua, Ma

2016-11-01

To solve the problem that large images can hardly be retrieved for stringent hardware restrictions and the security level is low, a method based on compressive ghost imaging (CGI) with Fast Fourier Transform (FFT) is proposed, named FFT-CGI. Initially, the information is encrypted by the sender with FFT, and the FFT-coded image is encrypted by the system of CGI with a secret key. Then the receiver decrypts the image with the aid of compressive sensing (CS) and FFT. Simulation results are given to verify the feasibility, security, and compression of the proposed encryption scheme. The experiment suggests the method can improve the quality of large images compared with conventional ghost imaging and achieve the imaging for large-sized images, further the amount of data transmitted largely reduced because of the combination of compressive sensing and FFT, and improve the security level of ghost images through ciphertext-only attack (COA), chosen-plaintext attack (CPA), and noise attack. This technique can be immediately applied to encryption and data storage with the advantages of high security, fast transmission, and high quality of reconstructed information.

Securing health sensing using integrated circuit metric.

PubMed

Tahir, Ruhma; Tahir, Hasan; McDonald-Maier, Klaus

2015-10-20

Convergence of technologies from several domains of computing and healthcare have aided in the creation of devices that can help health professionals in monitoring their patients remotely. An increase in networked healthcare devices has resulted in incidents related to data theft, medical identity theft and insurance fraud. In this paper, we discuss the design and implementation of a secure lightweight wearable health sensing system. The proposed system is based on an emerging security technology called Integrated Circuit Metric (ICMetric) that extracts the inherent features of a device to generate a unique device identification. In this paper, we provide details of how the physical characteristics of a health sensor can be used for the generation of hardware "fingerprints". The obtained fingerprints are used to deliver security services like authentication, confidentiality, secure admission and symmetric key generation. The generated symmetric key is used to securely communicate the health records and data of the patient. Based on experimental results and the security analysis of the proposed scheme, it is apparent that the proposed system enables high levels of security for health monitoring in resource optimized manner.

Securing Health Sensing Using Integrated Circuit Metric

PubMed Central

Tahir, Ruhma; Tahir, Hasan; McDonald-Maier, Klaus

2015-01-01

Convergence of technologies from several domains of computing and healthcare have aided in the creation of devices that can help health professionals in monitoring their patients remotely. An increase in networked healthcare devices has resulted in incidents related to data theft, medical identity theft and insurance fraud. In this paper, we discuss the design and implementation of a secure lightweight wearable health sensing system. The proposed system is based on an emerging security technology called Integrated Circuit Metric (ICMetric) that extracts the inherent features of a device to generate a unique device identification. In this paper, we provide details of how the physical characteristics of a health sensor can be used for the generation of hardware “fingerprints”. The obtained fingerprints are used to deliver security services like authentication, confidentiality, secure admission and symmetric key generation. The generated symmetric key is used to securely communicate the health records and data of the patient. Based on experimental results and the security analysis of the proposed scheme, it is apparent that the proposed system enables high levels of security for health monitoring in resource optimized manner. PMID:26492250

Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network

PubMed Central

Paek, Jeongyeup; Hicks, John; Coe, Sharon; Govindan, Ramesh

2014-01-01

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet's built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions. PMID:25171121

Image-based environmental monitoring sensor application using an embedded wireless sensor network.

PubMed

Paek, Jeongyeup; Hicks, John; Coe, Sharon; Govindan, Ramesh

2014-08-28

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet's built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Cannot Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions.

In-line optofluidic refractive index sensing in a side-channel photonic crystal fiber.

PubMed

Zhang, Nan; Humbert, Georges; Wu, Zhifang; Li, Kaiwei; Shum, Perry Ping; Zhang, Nancy Meng Ying; Cui, Ying; Auguste, Jean-Louis; Dinh, Xuan Quyen; Wei, Lei

2016-11-28

An in-line optofluidic refractive index (RI) sensing platform is constructed by splicing a side-channel photonic crystal fiber (SC-PCF) with side-polished single mode fibers. A long-period grating (LPG) combined with an intermodal interference between LP₀₁ and LP₁₁ core modes is used for sensing the RI of the liquid in the side channel. The resonant dip shows a nonlinear wavelength shift with increasing RI over the measured range from 1.3330 to 1.3961. The RI response of this sensing platform for a low RI range of 1.3330-1.3780 is approximately linear, and exhibits a sensitivity of 1145 nm/RIU. Besides, the detection limit of our sensing scheme is improved by around one order of magnitude by introducing the intermodal interference.

A megahertz-frequency tunable piecewise-linear electromechanical resonator realized via nonlinear feedback

NASA Astrophysics Data System (ADS)

Bajaj, Nikhil; Chiu, George T.-C.; Rhoads, Jeffrey F.

2018-07-01

Vibration-based sensing modalities traditionally have relied upon monitoring small shifts in natural frequency in order to detect structural changes (such as those in mass or stiffness). In contrast, bifurcation-based sensing schemes rely on the detection of a qualitative change in the behavior of a system as a parameter is varied. This can produce easy-to-detect changes in response amplitude with high sensitivity to structural change, but requires resonant devices with specific dynamic behavior which is not always easily reproduced. Desirable behavior for such devices can be produced reliably via nonlinear feedback circuitry, but has in past efforts been largely limited to sub-MHz operation, partially due to the time delay limitations present in certain nonlinear feedback circuits, such as multipliers. This work demonstrates the design and implementation of a piecewise-linear resonator realized via diode- and integrated circuit-based feedback electronics and a quartz crystal resonator. The proposed system is fabricated and characterized, and the creation and selective placement of the bifurcation points of the overall electromechanical system is demonstrated by tuning the circuit gains. The demonstrated circuit operates at 16 MHz. Preliminary modeling and analysis is presented that qualitatively agrees with the experimentally-observed behavior.

Real Traceable Signatures

NASA Astrophysics Data System (ADS)

Chow, Sherman S. M.

Traceable signature scheme extends a group signature scheme with an enhanced anonymity management mechanism. The group manager can compute a tracing trapdoor which enables anyone to test if a signature is signed by a given misbehaving user, while the only way to do so for group signatures requires revealing the signer of all signatures. Nevertheless, it is not tracing in a strict sense. For all existing schemes, T tracing agents need to recollect all N' signatures ever produced and perform RN' “checks” for R revoked users. This involves a high volume of transfer and computations. Increasing T increases the degree of parallelism for tracing but also the probability of “missing” some signatures in case some of the agents are dishonest.

Cognitive fiber Bragg grating sensors system based on fiber Fabry-Perot tunable filter technology

NASA Astrophysics Data System (ADS)

Zhang, Hongtao; Wang, Pengfei; Zou, Jilin; Xie, Jing; Cui, Hong-Liang

2011-05-01

The wavelength demodulation based on a Fiber Fabry-Pérot Tunable Filter (FFP-TF) is a common method for multiplexing Fiber Bragg Grating (FBG) sensors. But this method cannot be used to detect high frequency signals due to the limitation by the highest scanning rate that the FFP-TF can achieve. To overcome this disadvantage, in this paper we present a scheme of cognitive sensors network based on FFP-TF technology. By perceiving the sensing environment, system can automatically switch into monitoring signals in two modes to obtain better measurement results: multi measurement points, low frequency (<1 KHz) signal, and few measurement points but high frequency (~50 KHz) signals. This cognitive sensors network can be realized in current technology and satisfy current most industrial requirements.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

NASA Technical Reports Server (NTRS)

Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

2013-01-01

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

A sparse reconstruction method for the estimation of multiresolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2014-08-20

We present a sparse reconstruction scheme that can also be used to ensure non-negativity when fitting wavelet-based random field models to limited observations in non-rectangular geometries. The method is relevant when multiresolution fields are estimated using linear inverse problems. Examples include the estimation of emission fields for many anthropogenic pollutants using atmospheric inversion or hydraulic conductivity in aquifers from flow measurements. The scheme is based on three new developments. Firstly, we extend an existing sparse reconstruction method, Stagewise Orthogonal Matching Pursuit (StOMP), to incorporate prior information on the target field. Secondly, we develop an iterative method that uses StOMP tomore » impose non-negativity on the estimated field. Finally, we devise a method, based on compressive sensing, to limit the estimated field within an irregularly shaped domain. We demonstrate the method on the estimation of fossil-fuel CO 2 (ffCO 2) emissions in the lower 48 states of the US. The application uses a recently developed multiresolution random field model and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of two. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Optical registration of spaceborne low light remote sensing camera

NASA Astrophysics Data System (ADS)

Li, Chong-yang; Hao, Yan-hui; Xu, Peng-mei; Wang, Dong-jie; Ma, Li-na; Zhao, Ying-long

2018-02-01

For the high precision requirement of spaceborne low light remote sensing camera optical registration, optical registration of dual channel for CCD and EMCCD is achieved by the high magnification optical registration system. System integration optical registration and accuracy of optical registration scheme for spaceborne low light remote sensing camera with short focal depth and wide field of view is proposed in this paper. It also includes analysis of parallel misalignment of CCD and accuracy of optical registration. Actual registration results show that imaging clearly, MTF and accuracy of optical registration meet requirements, it provide important guarantee to get high quality image data in orbit.

Polarimetric Glucose Sensing Using Brewster Reflection off of Eye Lens: Theoretical Analysis

NASA Technical Reports Server (NTRS)

Boeckle, Stefan; Rovati, Luigi; Ansari, Rafat R.

2002-01-01

An important task of in vivo polarimetric glucose sensing is to find an appropriate way to optically access the aqueous humor of the human eye. In this paper two different approaches are analyzed theoretically and applied to the eye model of Le Grand. First approach is the tangential path of Cote, et al. (G.L. Cot6, M.D. Fox, and R.B. Northrop: Noninvasive Optical Polarimetric Glucose Sensing Using a True Phase Measurement Technique. IEEE Transactions on Biomedical Engineering, vol. 39, no. 7, pp. 752-756, 1992.) and the second is a new scheme of this paper of applying Brewster reflection off the eye lens.

Effectiveness of compressed sensing and transmission in wireless sensor networks for structural health monitoring

NASA Astrophysics Data System (ADS)

Fujiwara, Takahiro; Uchiito, Haruki; Tokairin, Tomoya; Kawai, Hiroyuki

2017-04-01

Regarding Structural Health Monitoring (SHM) for seismic acceleration, Wireless Sensor Networks (WSN) is a promising tool for low-cost monitoring. Compressed sensing and transmission schemes have been drawing attention to achieve effective data collection in WSN. Especially, SHM systems installing massive nodes of WSN require efficient data transmission due to restricted communications capability. The dominant frequency band of seismic acceleration is occupied within 100 Hz or less. In addition, the response motions on upper floors of a structure are activated at a natural frequency, resulting in induced shaking at the specified narrow band. Focusing on the vibration characteristics of structures, we introduce data compression techniques for seismic acceleration monitoring in order to reduce the amount of transmission data. We carry out a compressed sensing and transmission scheme by band pass filtering for seismic acceleration data. The algorithm executes the discrete Fourier transform for the frequency domain and band path filtering for the compressed transmission. Assuming that the compressed data is transmitted through computer networks, restoration of the data is performed by the inverse Fourier transform in the receiving node. This paper discusses the evaluation of the compressed sensing for seismic acceleration by way of an average error. The results present the average error was 0.06 or less for the horizontal acceleration, in conditions where the acceleration was compressed into 1/32. Especially, the average error on the 4th floor achieved a small error of 0.02. Those results indicate that compressed sensing and transmission technique is effective to reduce the amount of data with maintaining the small average error.

Design and Control of a Mechatronic Tracheostomy Tube for Automated Tracheal Suctioning.

PubMed

Do, Thanh Nho; Seah, Tian En Timothy; Phee, Soo Jay

2016-06-01

Mechanical ventilation is required to aid patients with breathing difficulty to breathe more comfortably. A tracheostomy tube inserted through an opening in the patient neck into the trachea is connected to a ventilator for suctioning. Currently, nurses spend millions of person-hours yearly to perform this task. To save significant person-hours, an automated mechatronic tracheostomy system is needed. This system allows for relieving nurses and other carers from the millions of person-hours spent yearly on tracheal suctioning. In addition, it will result in huge healthcare cost savings. We introduce a novel mechatronic tracheostomy system including the development of a long suction catheter, automatic suctioning mechanisms, and relevant control approaches to perform tracheal suctioning automatically. To stop the catheter at a desired position, two approaches are introduced: 1) Based on the known travel length of the catheter tip; 2) Based on a new sensing device integrated at the catheter tip. It is known that backlash nonlinearity between the suction catheter and its conduit as well as in the gear system of the actuator are unavoidable. They cause difficulties to control the exact position of the catheter tip. For the former case, we develop an approximate model of backlash and a direct inverse scheme to enhance the system performances. The scheme does not require any complex inversions of the backlash model and allows easy implementations. For the latter case, a new sensing device integrated into the suction catheter tip is developed and backlash compensation controls are avoided. Automated suctioning validations are successfully carried out on the proposed experimental system. Comparisons and discussions are also introduced. The results demonstrate a significant contribution and potential benefits to the mechanical ventilation areas.

Are health workers motivated by income? Job motivation of Cambodian primary health workers implementing performance-based financing.

PubMed

Khim, Keovathanak

2016-01-01

Financial incentives are widely used in performance-based financing (PBF) schemes, but their contribution to health workers' incomes and job motivation is poorly understood. Cambodia undertook health sector reform from the middle of 2009 and PBF was employed as a part of the reform process. This study examines job motivation for primary health workers (PHWs) under PBF reform in Cambodia and assesses the relationship between job motivation and income. A cross-sectional self-administered survey was conducted on 266 PHWs, from 54 health centers in the 15 districts involved in the reform. The health workers were asked to report all sources of income from public sector jobs and provide answers to 20 items related to job motivation. Factor analysis was conducted to identify the latent variables of job motivation. Factors associated with motivation were identified through multivariable regression. PHWs reported multiple sources of income and an average total income of US$190 per month. Financial incentives under the PBF scheme account for 42% of the average total income. PHWs had an index motivation score of 4.9 (on a scale from one to six), suggesting they had generally high job motivation that was related to a sense of community service, respect, and job benefits. Regression analysis indicated that income and the perception of a fair distribution of incentives were both statistically significant in association with higher job motivation scores. Financial incentives used in the reform formed a significant part of health workers' income and influenced their job motivation. Improving job motivation requires fixing payment mechanisms and increasing the size of incentives. PBF is more likely to succeed when income, training needs, and the desire for a sense of community service are addressed and institutionalized within the health system.

GPU-accelerated compressed-sensing (CS) image reconstruction in chest digital tomosynthesis (CDT) using CUDA programming

NASA Astrophysics Data System (ADS)

Choi, Sunghoon; Lee, Haenghwa; Lee, Donghoon; Choi, Seungyeon; Shin, Jungwook; Jang, Woojin; Seo, Chang-Woo; Kim, Hee-Joung

2017-03-01

A compressed-sensing (CS) technique has been rapidly applied in medical imaging field for retrieving volumetric data from highly under-sampled projections. Among many variant forms, CS technique based on a total-variation (TV) regularization strategy shows fairly reasonable results in cone-beam geometry. In this study, we implemented the TV-based CS image reconstruction strategy in our prototype chest digital tomosynthesis (CDT) R/F system. Due to the iterative nature of time consuming processes in solving a cost function, we took advantage of parallel computing using graphics processing units (GPU) by the compute unified device architecture (CUDA) programming to accelerate our algorithm. In order to compare the algorithmic performance of our proposed CS algorithm, conventional filtered back-projection (FBP) and simultaneous algebraic reconstruction technique (SART) reconstruction schemes were also studied. The results indicated that the CS produced better contrast-to-noise ratios (CNRs) in the physical phantom images (Teflon region-of-interest) by factors of 3.91 and 1.93 than FBP and SART images, respectively. The resulted human chest phantom images including lung nodules with different diameters also showed better visual appearance in the CS images. Our proposed GPU-accelerated CS reconstruction scheme could produce volumetric data up to 80 times than CPU programming. Total elapsed time for producing 50 coronal planes with 1024×1024 image matrix using 41 projection views were 216.74 seconds for proposed CS algorithms on our GPU programming, which could match the clinically feasible time ( 3 min). Consequently, our results demonstrated that the proposed CS method showed a potential of additional dose reduction in digital tomosynthesis with reasonable image quality in a fast time.

Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

NASA Astrophysics Data System (ADS)

Tsai, F.; Lai, J. S.; Chiang, S. H.

2015-12-01

Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results demonstrate that the accuracies of landslide susceptibility analysis in all sequential predictions have been improved significantly after eliminating landslide depositions.

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Interfacing whispering-gallery microresonators and free space light with cavity enhanced Rayleigh scattering

PubMed Central

Zhu, Jiangang; Özdemir, Şahin K.; Yilmaz, Huzeyfe; Peng, Bo; Dong, Mark; Tomes, Matthew; Carmon, Tal; Yang, Lan

2014-01-01

Whispering gallery mode resonators (WGMRs) take advantage of strong light confinement and long photon lifetime for applications in sensing, optomechanics, microlasers and quantum optics. However, their rotational symmetry and low radiation loss impede energy exchange between WGMs and the surrounding. As a result, free-space coupling of light into and from WGMRs is very challenging. In previous schemes, resonators are intentionally deformed to break circular symmetry to enable free-space coupling of carefully aligned focused light, which comes with bulky size and alignment issues that hinder the realization of compact WGMR applications. Here, we report a new class of nanocouplers based on cavity enhanced Rayleigh scattering from nano-scatterer(s) on resonator surface, and demonstrate whispering gallery microlaser by free-space optical pumping of an Ytterbium doped silica microtoroid via the scatterers. This new scheme will not only expand the range of applications enabled by WGMRs, but also provide a possible route to integrate them into solar powered green photonics. PMID:25227918

Nitrogen dioxide sensing using a novel gas correlation detector

NASA Astrophysics Data System (ADS)

Kebabian, Paul L.; Annen, Kurt D.; Berkoff, Timothy A.; Freedman, Andrew

2000-05-01

A nitrogen dioxide point sensor, based on a novel nondispersive gas filter spectroscopic scheme, is described. The detection scheme relies on the fact that the absorption spectrum of nitrogen dioxide in the 400-550 nm region consists of a complicated line structure superimposed on an average broadband absorption. A compensating filter is used to remove the effect of the broadband absorption, making the sensor insensitive both to small particles in the optical path and to potentially interfering gases with broadband absorption features in the relevant wavelength region. Measurements are obtained using a remote optical absorption cell that is linked via multimode fibre optics to the source and detection optics. The incorporation of blue light emitting diodes which spectrally match the nitrogen dioxide absorption allows the employment of electronic (instead of mechanical) switching between optical paths. A sensitivity of better than 1.0 ppm m column density (1 s integration time) has been observed; improvements in electronics and thermal stabilization should increase this sensitivity.

Aerodynamic influence coefficient method using singularity splines

NASA Technical Reports Server (NTRS)

Mercer, J. E.; Weber, J. A.; Lesferd, E. P.

1974-01-01

A numerical lifting surface formulation, including computed results for planar wing cases is presented. This formulation, referred to as the vortex spline scheme, combines the adaptability to complex shapes offered by paneling schemes with the smoothness and accuracy of loading function methods. The formulation employes a continuous distribution of singularity strength over a set of panels on a paneled wing. The basic distributions are independent, and each satisfied all the continuity conditions required of the final solution. These distributions are overlapped both spanwise and chordwise. Boundary conditions are satisfied in a least square error sense over the surface using a finite summing technique to approximate the integral. The current formulation uses the elementary horseshoe vortex as the basic singularity and is therefore restricted to linearized potential flow. As part of the study, a non planar development was considered, but the numerical evaluation of the lifting surface concept was restricted to planar configurations. Also, a second order sideslip analysis based on an asymptotic expansion was investigated using the singularity spline formulation.

Interfacing whispering-gallery microresonators and free space light with cavity enhanced Rayleigh scattering.

PubMed

Zhu, Jiangang; Özdemir, Sahin K; Yilmaz, Huzeyfe; Peng, Bo; Dong, Mark; Tomes, Matthew; Carmon, Tal; Yang, Lan

2014-09-17

Whispering gallery mode resonators (WGMRs) take advantage of strong light confinement and long photon lifetime for applications in sensing, optomechanics, microlasers and quantum optics. However, their rotational symmetry and low radiation loss impede energy exchange between WGMs and the surrounding. As a result, free-space coupling of light into and from WGMRs is very challenging. In previous schemes, resonators are intentionally deformed to break circular symmetry to enable free-space coupling of carefully aligned focused light, which comes with bulky size and alignment issues that hinder the realization of compact WGMR applications. Here, we report a new class of nanocouplers based on cavity enhanced Rayleigh scattering from nano-scatterer(s) on resonator surface, and demonstrate whispering gallery microlaser by free-space optical pumping of an Ytterbium doped silica microtoroid via the scatterers. This new scheme will not only expand the range of applications enabled by WGMRs, but also provide a possible route to integrate them into solar powered green photonics.

Generation of spectral clusters in a mixture of noble and Raman-active gases.

PubMed

Hosseini, Pooria; Abdolvand, Amir; St J Russell, Philip

2016-12-01

We report a novel scheme for the generation of dense clusters of Raman sidebands. The scheme uses a broadband-guiding hollow-core photonic crystal fiber (HC-PCF) filled with a mixture of H₂, D₂, and Xe for efficient interaction between the gas mixture and a green laser pump pulse (532 nm, 1 ns) of only 5 μJ of energy. This results in the generation from noise of more than 135 rovibrational Raman sidebands covering the visible spectral region with an average spacing of only 2.2 THz. Such a spectrally dense and compact fiber-based source is ideal for applications where closely spaced narrow-band laser lines with high spectral power density are required, such as in spectroscopy and sensing. When the HC-PCF is filled with a H₂-D₂ mixture, the Raman comb spans the spectral region from the deep UV (280 nm) to the near infrared (1000 nm).

Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.

1996-01-01

An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.

An all-at-once reduced Hessian SQP scheme for aerodynamic design optimization

NASA Technical Reports Server (NTRS)

Feng, Dan; Pulliam, Thomas H.

1995-01-01

This paper introduces a computational scheme for solving a class of aerodynamic design problems that can be posed as nonlinear equality constrained optimizations. The scheme treats the flow and design variables as independent variables, and solves the constrained optimization problem via reduced Hessian successive quadratic programming. It updates the design and flow variables simultaneously at each iteration and allows flow variables to be infeasible before convergence. The solution of an adjoint flow equation is never needed. In addition, a range space basis is chosen so that in a certain sense the 'cross term' ignored in reduced Hessian SQP methods is minimized. Numerical results for a nozzle design using the quasi-one-dimensional Euler equations show that this scheme is computationally efficient and robust. The computational cost of a typical nozzle design is only a fraction more than that of the corresponding analysis flow calculation. Superlinear convergence is also observed, which agrees with the theoretical properties of this scheme. All optimal solutions are obtained by starting far away from the final solution.

Global biodiversity monitoring: from data sources to essential biodiversity variables

USGS Publications Warehouse

Proenca, Vania; Martin, Laura J.; Pereira, Henrique M.; Fernandez, Miguel; McRae, Louise; Belnap, Jayne; Böhm, Monika; Brummitt, Neil; Garcia-Moreno, Jaime; Gregory, Richard D.; Honrado, Joao P; Jürgens, Norbert; Opige, Michael; Schmeller, Dirk S.; Tiago, Patricia; van Sway, Chris A

2016-01-01

Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps.

Computational flow field in energy efficient engine (EEE)

NASA Astrophysics Data System (ADS)

Miki, Kenji; Moder, Jeff; Liou, Meng-Sing

2016-11-01

In this paper, preliminary results for the recently-updated Open National Combustor Code (Open NCC) as applied to the EEE are presented. The comparison between two different numerical schemes, the standard Jameson-Schmidt-Turkel (JST) scheme and the advection upstream splitting method (AUSM), is performed for the cold flow and the reacting flow calculations using the RANS. In the cold flow calculation, the AUSM scheme predicts a much stronger reverse flow in the central recirculation zone. In the reacting flow calculation, we test two cases: gaseous fuel injection and liquid spray injection. In the gaseous fuel injection case, the overall flame structures of the two schemes are similar to one another, in the sense that the flame is attached to the main nozzle, but is detached from the pilot nozzle. However, in the exit temperature profile, the AUSM scheme shows a more uniform profile than that of the JST scheme, which is close to the experimental data. In the liquid spray injection case, we expect different flame structures in this scenario. We will give a brief discussion on how two numerical schemes predict the flame structures inside the Eusing different ways to introduce the fuel injection. Supported by NASA's Transformational Tools and Technologies project.

Computational Flow Field in Energy Efficient Engine (EEE)

NASA Technical Reports Server (NTRS)

Miki, Kenji; Moder, Jeff; Liou, Meng-Sing

2016-01-01

In this paper, preliminary results for the recently-updated Open National Combustion Code (Open NCC) as applied to the EEE are presented. The comparison between two different numerical schemes, the standard Jameson-Schmidt-Turkel (JST) scheme and the advection upstream splitting method (AUSM), is performed for the cold flow and the reacting flow calculations using the RANS. In the cold flow calculation, the AUSM scheme predicts a much stronger reverse flow in the central recirculation zone. In the reacting flow calculation, we test two cases: gaseous fuel injection and liquid spray injection. In the gaseous fuel injection case, the overall flame structures of the two schemes are similar to one another, in the sense that the flame is attached to the main nozzle, but is detached from the pilot nozzle. However, in the exit temperature profile, the AUSM scheme shows a more uniform profile than that of the JST scheme, which is close to the experimental data. In the liquid spray injection case, we expect different flame structures in this scenario. We will give a brief discussion on how two numerical schemes predict the flame structures inside the EEE using different ways to introduce the fuel injection.

Estimation CODMN in Guangzhou Section of Pearl River Based on GF-1 Images

NASA Astrophysics Data System (ADS)

Feng, Y. B.; He, Y. Q.; Fu, Q. H.; Liu, C. Q.; Pan, H. Z.; Yin, B.

2018-04-01

Due to the way that remote sensing works, it has natural advantage to detect optical constituents in waters. And many kinds of inversion models were constructed based on the three main optical constituents, namely chlorophyll-a (Chl-a), suspended particulate matter (SPM), colored dissolved organic matter (CDOM). Except Chl-a used as an indicator of eutrophication, however, the public generally cares less about other two parameters and is more familiar with Grade I V scheme for utilization and protection purposes. Notice the three main optical constituents are also organic-related to some extent. It offers a possible way to estimate CODMn via remote sensing. According to field measurement conducted along the Guangzhou section of Pearl River (GPR for short), the spatial variation of CODMn in GPR shows some kinds of geographical feature, so does the correlation between CODMn and water color constituents. It indicated the complicated contribution of CODMn in GPR or some other urban rivers. Based on the band setting of GF-1 satellite, two kinds of inversion model of CODMn in GPR were finally constructed. One directly achieved CODMn from regression models of which predictors were different band combinations in different channels of GPR. To make the study more practical, the other one first provided empirical models of the three optical constituents, and then estimated CODMn of GPR based on its relationship with optical constituents. After all, Chl-a, SPM and CDOM could be distinguished optically, and remote sensing models of these three constituents in other studies may also be available.

Quantitative detection of the respective concentrations of chiral compounds with weak measurements

NASA Astrophysics Data System (ADS)

Xie, Linguo; Qiu, Xiaodong; Luo, Lan; Liu, Xiong; Li, Zhaoxue; Zhang, Zhiyou; Du, Jinglei; Wang, Deqiang

2017-11-01

In this letter, we determine the respective concentrations of glucose and fructose in the mixed chiral solution by simultaneously measuring the optical rotation angle (ORA) and the refractive index change (RIC) with weak measurements. The photonic spin Hall effect (PSHE) serves as a probe in our scheme. The measurement of ORA is based on the high sensitivity of the amplification factor to the polarization state in weak measurements. The measurement of RIC is based on the rapid variation of spin splitting of the PSHE. The measurement precision of the respective concentrations can be achieved to be 0.02 mg/ml. This method can detect traces of enantiomeric impurities and has a potential application in chiral sensing.

High-sensitivity fiber optic acoustic sensors

NASA Astrophysics Data System (ADS)

Lu, Ping; Liu, Deming; Liao, Hao

2016-11-01

Due to the overwhelming advantages compared with traditional electronicsensors, fiber-optic acoustic sensors have arisen enormous interest in multiple disciplines. In this paper we present the recent research achievements of our group on fiber-optic acoustic sensors. The main point of our research is high sensitivity interferometric acoustic sensors, including Michelson, Sagnac, and Fabry-Pérot interferometers. In addition, some advanced technologies have been proposed for acoustic or acoustic pressure sensing such as single-mode/multimode fiber coupler, dual FBGs and multi-longitudinal mode fiber laser based acoustic sensors. Moreover, our attention we have also been paid on signal demodulation schemes. The intensity-based quadrature point (Q-point) demodulation, two-wavelength quadrature demodulation and symmetric 3×3 coupler methodare discussed and compared in this paper.

Robust Algorithms for on Minor-Free Graphs Based on the Sherali-Adams Hierarchy

NASA Astrophysics Data System (ADS)

Magen, Avner; Moharrami, Mohammad

This work provides a Linear Programming-based Polynomial Time Approximation Scheme (PTAS) for two classical NP-hard problems on graphs when the input graph is guaranteed to be planar, or more generally Minor Free. The algorithm applies a sufficiently large number (some function of when approximation is required) of rounds of the so-called Sherali-Adams Lift-and-Project system. needed to obtain a -approximation, where f is some function that depends only on the graph that should be avoided as a minor. The problem we discuss are the well-studied problems, the and problems. An curious fact we expose is that in the world of minor-free graph, the is harder in some sense than the.

Detection of Single Molecules Illuminated by a Light-Emitting Diode

PubMed Central

Gerhardt, Ilja; Mai, Lijian; Lamas-Linares, Antía; Kurtsiefer, Christian

2011-01-01

Optical detection and spectroscopy of single molecules has become an indispensable tool in biological imaging and sensing. Its success is based on fluorescence of organic dye molecules under carefully engineered laser illumination. In this paper we demonstrate optical detection of single molecules on a wide-field microscope with an illumination based on a commercially available, green light-emitting diode. The results are directly compared with laser illumination in the same experimental configuration. The setup and the limiting factors, such as light transfer to the sample, spectral filtering and the resulting signal-to-noise ratio are discussed. A theoretical and an experimental approach to estimate these parameters are presented. The results can be adapted to other single emitter and illumination schemes. PMID:22346610

Super-cooled liquid water topped sub-arctic clouds and precipitation - investigation based on combination of ground-based in-situ and remote-sensing observations

NASA Astrophysics Data System (ADS)

Hirsikko, Anne; Brus, David; O'Connor, Ewan J.; Filioglou, Maria; Komppula, Mika; Romakkaniemi, Sami

2017-04-01

In the high and mid latitudes super-cooled liquid water layers are frequently observed on top of clouds. These layers are difficult to forecast with numerical weather prediction models, even though, they have strong influence on atmospheric radiative properties, cloud microphysical properties, and subsequently, precipitation. This work investigates properties of super-cooled liquid water layer topped sub-arctic clouds and precipitation observed with ground-based in-situ (cloud probes) and remote-sensing (a cloud radar, Doppler and multi-wavelength lidars) instrumentation during two-month long Pallas Cloud Experiment (PaCE 2015) in autumn 2015. Analysis is based on standard Cloudnet scheme supplemented with new retrieval products of the specific clouds and their properties. Combination of two scales of observation provides new information on properties of clouds and precipitation in the sub-arctic Pallas region. Current status of results will be presented during the conference. The authors acknowledge financial support by the Academy of Finland (Centre of Excellence Programme, grant no 272041; and ICINA project, grant no 285068), the ACTRIS2 - European Union's Horizon 2020 research and innovation programme under grant agreement No 654109, the KONE foundation, and the EU FP7 project BACCHUS (grant no 603445).

Accelerated self-gated UTE MRI of the murine heart

NASA Astrophysics Data System (ADS)

Motaal, Abdallah G.; Noorman, Nils; De Graaf, Wolter L.; Florack, Luc J.; Nicolay, Klaas; Strijkers, Gustav J.

2014-03-01

We introduce a new protocol to obtain radial Ultra-Short TE (UTE) MRI Cine of the beating mouse heart within reasonable measurement time. The method is based on a self-gated UTE with golden angle radial acquisition and compressed sensing reconstruction. The stochastic nature of the retrospective triggering acquisition scheme produces an under-sampled and random kt-space filling that allows for compressed sensing reconstruction, hence reducing scan time. As a standard, an intragate multislice FLASH sequence with an acquisition time of 4.5 min per slice was used to produce standard Cine movies of 4 mice hearts with 15 frames per cardiac cycle. The proposed self-gated sequence is used to produce Cine movies with short echo time. The total scan time was 11 min per slice. 6 slices were planned to cover the heart from the base to the apex. 2X, 4X and 6X under-sampled k-spaces cine movies were produced from 2, 1 and 0.7 min data acquisitions for each slice. The accelerated cine movies of the mouse hearts were successfully reconstructed with a compressed sensing algorithm. Compared to the FLASH cine images, the UTE images showed much less flow artifacts due to the short echo time. Besides, the accelerated movies had high image quality and the undersampling artifacts were effectively removed. Left ventricular functional parameters derived from the standard and the accelerated cine movies were nearly identical.

Sensitivity Enhancement of Transition Metal Dichalcogenides/Silicon Nanostructure-based Surface Plasmon Resonance Biosensor

PubMed Central

Ouyang, Qingling; Zeng, Shuwen; Jiang, Li; Hong, Liying; Xu, Gaixia; Dinh, Xuan-Quyen; Qian, Jun; He, Sailing; Qu, Junle; Coquet, Philippe; Yong, Ken-Tye

2016-01-01

In this work, we designed a sensitivity-enhanced surface plasmon resonance biosensor structure based on silicon nanosheet and two-dimensional transition metal dichalcogenides. This configuration contains six components: SF10 triangular prism, gold thin film, silicon nanosheet, two-dimensional MoS2/MoSe2/WS2/WSe2 (defined as MX2) layers, biomolecular analyte layer and sensing medium. The minimum reflectivity, sensitivity as well as the Full Width at Half Maximum of SPR curve are systematically examined by using Fresnel equations and the transfer matrix method in the visible and near infrared wavelength range (600 nm to 1024 nm). The variation of the minimum reflectivity and the change in resonance angle as the function of the number of MX2 layers are presented respectively. The results show that silicon nanosheet and MX2 layers can be served as effective light absorption medium. Under resonance conditions, the electrons in these additional dielectric layers can be transferred to the surface of gold thin film. All silicon-MX2 enhanced sensing models show much better performance than that of the conventional sensing scheme where pure Au thin film is used, the highest sensitivity can be achieved by employing 600 nm excitation light wavelength with 35 nm gold thin film and 7 nm thickness silicon nanosheet coated with monolayer WS2. PMID:27305974

Quantum noise in bright soliton matterwave interferometry

NASA Astrophysics Data System (ADS)

Haine, Simon A.

2018-03-01

There has been considerable recent interest in matterwave interferometry with bright solitons in quantum gases with attractive interactions, for applications such as rotation sensing. We model the quantum dynamics of these systems and find that the attractive interactions required for the presence of bright solitons causes quantum phase-diffusion, which severely impairs the sensitivity. We propose a scheme that partially restores the sensitivity, but find that in the case of rotation sensing, it is still better to work in a regime with minimal interactions if possible.

Bio-Inspired Sensing and Imaging of Polarization Information in Nature

DTIC Science & Technology

2008-05-04

polarization imaging,” Appl. Opt. 36, 150–155 (1997). 5. L. B. Wolff, “Polarization camera for computer vision with a beam splitter ,” J. Opt. Soc. Am. A...vision with a beam splitter ,” J. Opt. Soc. Am. A 11, 2935–2945 (1994). 2. L. B. Wolff and A. G. Andreou, “Polarization camera sensors,” Image Vis. Comput...group we have been developing various man-made, non -invasive imaging methodologies, sensing schemes, camera systems, and visualization and display

A review of visible, near-IR, and mid-IR transitions in rare-earth doped glass waveguides for remote sensing and LIDAR

NASA Astrophysics Data System (ADS)

Jha, Animesh

2006-12-01

In the review article we explain the recent investigations on rare-earth doped glass and optical fibres for designing lasers which may be suitable for remote sensing and LIDAR applications. The paper explains the importance of engineering efficient lasing transitions in visible (480-650 nm) for generating UV lasers via one-stage harmonic generation. Besides visible transitions, we also demonstrate the transitions in near- and mid-IR via near-IR pumping scheme.

Entanglement-Based dc Magnetometry with Separated Ions*

NASA Astrophysics Data System (ADS)

Ruster, T.; Kaufmann, H.; Luda, M. A.; Kaushal, V.; Schmiegelow, C. T.; Schmidt-Kaler, F.; Poschinger, U. G.

2017-07-01

We demonstrate sensing of inhomogeneous dc magnetic fields by employing entangled trapped ions, which are shuttled in a segmented Paul trap. As sensor states, we use Bell states of the type |↑↓ ⟩ +ei φ|↓↑ ⟩ encoded in two 40Ca+ ions stored at different locations. The linear Zeeman effect leads to the accumulation of a relative phase φ , which serves for measuring the magnetic-field difference between the constituent locations. Common-mode magnetic-field fluctuations are rejected by the entangled sensor state, which gives rise to excellent sensitivity without employing dynamical decoupling and therefore enables accurate dc sensing. Consecutive measurements on sensor states encoded in the S1 /2 ground state and in the D5 /2 metastable state are used to separate an ac Zeeman shift from the linear dc Zeeman effect. We measure magnetic-field differences over distances of up to 6.2 mm, with accuracies down to 300 fT and sensitivities down to 12 pT /√{Hz }. Our sensing scheme features spatial resolutions in the 20-nm range. For optimizing the information gain while maintaining a high dynamic range, we implement an algorithm for Bayesian frequency estimation.

Automated training site selection for large-area remote-sensing image analysis

NASA Astrophysics Data System (ADS)

McCaffrey, Thomas M.; Franklin, Steven E.

1993-11-01

A computer program is presented to select training sites automatically from remotely sensed digital imagery. The basic ideas are to guide the image analyst through the process of selecting typical and representative areas for large-area image classifications by minimizing bias, and to provide an initial list of potential classes for which training sites are required to develop a classification scheme or to verify classification accuracy. Reducing subjectivity in training site selection is achieved by using a purely statistical selection of homogeneous sites which then can be compared to field knowledge, aerial photography, or other remote-sensing imagery and ancillary data to arrive at a final selection of sites to be used to train the classification decision rules. The selection of the homogeneous sites uses simple tests based on the coefficient of variance, the F-statistic, and the Student's i-statistic. Comparisons of site means are conducted with a linear growing list of previously located homogeneous pixels. The program supports a common pixel-interleaved digital image format and has been tested on aerial and satellite optical imagery. The program is coded efficiently in the C programming language and was developed under AIX-Unix on an IBM RISC 6000 24-bit color workstation.

A hybrid single-end-access MZI and Φ-OTDR vibration sensing system with high frequency response

NASA Astrophysics Data System (ADS)

Zhang, Yixin; Xia, Lan; Cao, Chunqi; Sun, Zhenhong; Li, Yanting; Zhang, Xuping

2017-01-01

A hybrid single-end-access Mach-Zehnder interferometer (MZI) and phase sensitive OTDR (Φ-OTDR) vibration sensing system is proposed and demonstrated experimentally. In our system, the narrow optical pulses and the continuous wave are injected into the fiber through the front end of the fiber at the same time. And at the rear end of the fiber, a frequency-shift-mirror (FSM) is designed to back propagate the continuous wave modulated by the external vibration. Thus the Rayleigh backscattering signals (RBS) and the back propagated continuous wave interfere with the reference light at the same end of the sensing fiber and a single-end-access configuration is achieved. The RBS can be successfully separated from the interference signal (IS) through digital signal process due to their different intermediate frequency based on frequency division multiplexing technique. There is no influence between these two schemes. The experimental results show 10 m spatial resolution and up to 1.2 MHz frequency response along a 6.35 km long fiber. This newly designed single-end-access setup can achieve vibration events locating and high frequency events response, which can be widely used in health monitoring for civil infrastructures and transportation.

Internet of Things (IoT) Based Design of a Secure and Lightweight Body Area Network (BAN) Healthcare System.

PubMed

Deng, Yong-Yuan; Chen, Chin-Ling; Tsaur, Woei-Jiunn; Tang, Yung-Wen; Chen, Jung-Hsuan

2017-12-15

As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients' personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack.

Optimal rotated staggered-grid finite-difference schemes for elastic wave modeling in TTI media

NASA Astrophysics Data System (ADS)

Yang, Lei; Yan, Hongyong; Liu, Hong

2015-11-01

The rotated staggered-grid finite-difference (RSFD) is an effective approach for numerical modeling to study the wavefield characteristics in tilted transversely isotropic (TTI) media. But it surfaces from serious numerical dispersion, which directly affects the modeling accuracy. In this paper, we propose two different optimal RSFD schemes based on the sampling approximation (SA) method and the least-squares (LS) method respectively to overcome this problem. We first briefly introduce the RSFD theory, based on which we respectively derive the SA-based RSFD scheme and the LS-based RSFD scheme. Then different forms of analysis are used to compare the SA-based RSFD scheme and the LS-based RSFD scheme with the conventional RSFD scheme, which is based on the Taylor-series expansion (TE) method. The contrast in numerical accuracy analysis verifies the greater accuracy of the two proposed optimal schemes, and indicates that these schemes can effectively widen the wavenumber range with great accuracy compared with the TE-based RSFD scheme. Further comparisons between these two optimal schemes show that at small wavenumbers, the SA-based RSFD scheme performs better, while at large wavenumbers, the LS-based RSFD scheme leads to a smaller error. Finally, the modeling results demonstrate that for the same operator length, the SA-based RSFD scheme and the LS-based RSFD scheme can achieve greater accuracy than the TE-based RSFD scheme, while for the same accuracy, the optimal schemes can adopt shorter difference operators to save computing time.

Designing a Bio-responsive Robot from DNA Origami

PubMed Central

Ben-Ishay, Eldad; Abu-Horowitz, Almogit; Bachelet, Ido

2013-01-01

Nucleic acids are astonishingly versatile. In addition to their natural role as storage medium for biological information1, they can be utilized in parallel computing2,3 , recognize and bind molecular or cellular targets4,5 , catalyze chemical reactions6,7 , and generate calculated responses in a biological system8,9. Importantly, nucleic acids can be programmed to self-assemble into 2D and 3D structures10-12, enabling the integration of all these remarkable features in a single robot linking the sensing of biological cues to a preset response in order to exert a desired effect. Creating shapes from nucleic acids was first proposed by Seeman13, and several variations on this theme have since been realized using various techniques11,12,14,15 . However, the most significant is perhaps the one proposed by Rothemund, termed scaffolded DNA origami16. In this technique, the folding of a long (>7,000 bases) single-stranded DNA 'scaffold' is directed to a desired shape by hundreds of short complementary strands termed 'staples'. Folding is carried out by temperature annealing ramp. This technique was successfully demonstrated in the creation of a diverse array of 2D shapes with remarkable precision and robustness. DNA origami was later extended to 3D as well17,18 . The current paper will focus on the caDNAno 2.0 software19 developed by Douglas and colleagues. caDNAno is a robust, user-friendly CAD tool enabling the design of 2D and 3D DNA origami shapes with versatile features. The design process relies on a systematic and accurate abstraction scheme for DNA structures, making it relatively straightforward and efficient. In this paper we demonstrate the design of a DNA origami nanorobot that has been recently described20. This robot is 'robotic' in the sense that it links sensing to actuation, in order to perform a task. We explain how various sensing schemes can be integrated into the structure, and how this can be relayed to a desired effect. Finally we use Cando21 to simulate the mechanical properties of the designed shape. The concept we discuss can be adapted to multiple tasks and settings. PMID:23893007

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

Angstrom-Resolution Magnetic Resonance Imaging of Single Molecules via Wave-Function Fingerprints of Nuclear Spins

NASA Astrophysics Data System (ADS)

Ma, Wen-Long; Liu, Ren-Bao

2016-08-01

Single-molecule sensitivity of nuclear magnetic resonance (NMR) and angstrom resolution of magnetic resonance imaging (MRI) are the highest challenges in magnetic microscopy. Recent development in dynamical-decoupling- (DD) enhanced diamond quantum sensing has enabled single-nucleus NMR and nanoscale NMR. Similar to conventional NMR and MRI, current DD-based quantum sensing utilizes the "frequency fingerprints" of target nuclear spins. The frequency fingerprints by their nature cannot resolve different nuclear spins that have the same noise frequency or differentiate different types of correlations in nuclear-spin clusters, which limit the resolution of single-molecule MRI. Here we show that this limitation can be overcome by using "wave-function fingerprints" of target nuclear spins, which is much more sensitive than the frequency fingerprints to the weak hyperfine interaction between the targets and a sensor under resonant DD control. We demonstrate a scheme of angstrom-resolution MRI that is capable of counting and individually localizing single nuclear spins of the same frequency and characterizing the correlations in nuclear-spin clusters. A nitrogen-vacancy-center spin sensor near a diamond surface, provided that the coherence time is improved by surface engineering in the near future, may be employed to determine with angstrom resolution the positions and conformation of single molecules that are isotope labeled. The scheme in this work offers an approach to breaking the resolution limit set by the "frequency gradients" in conventional MRI and to reaching the angstrom-scale resolution.

Wideband optical sensing using pulse interferometry.

PubMed

Rosenthal, Amir; Razansky, Daniel; Ntziachristos, Vasilis

2012-08-13

Advances in fabrication of high-finesse optical resonators hold promise for the development of miniaturized, ultra-sensitive, wide-band optical sensors, based on resonance-shift detection. Many potential applications are foreseen for such sensors, among them highly sensitive detection in ultrasound and optoacoustic imaging. Traditionally, sensor interrogation is performed by tuning a narrow linewidth laser to the resonance wavelength. Despite the ubiquity of this method, its use has been mostly limited to lab conditions due to its vulnerability to environmental factors and the difficulty of multiplexing - a key factor in imaging applications. In this paper, we develop a new optical-resonator interrogation scheme based on wideband pulse interferometry, potentially capable of achieving high stability against environmental conditions without compromising sensitivity. Additionally, the method can enable multiplexing several sensors. The unique properties of the pulse-interferometry interrogation approach are studied theoretically and experimentally. Methods for noise reduction in the proposed scheme are presented and experimentally demonstrated, while the overall performance is validated for broadband optical detection of ultrasonic fields. The achieved sensitivity is equivalent to the theoretical limit of a 6 MHz narrow-line width laser, which is 40 times higher than what can be usually achieved by incoherent interferometry for the same optical resonator.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

PubMed Central

Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-01-01

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems. PMID:29439442

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems.

PubMed

Ma, Xingpo; Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-02-10

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Recognition of three dimensional obstacles by an edge detection scheme. [for Mars roving vehicle using laser range finder

NASA Technical Reports Server (NTRS)

Reed, M. A.

1974-01-01

The need for an obstacle detection system on the Mars roving vehicle was assumed, and a practical scheme was investigated and simulated. The principal sensing device on this vehicle was taken to be a laser range finder. Both existing and original algorithms, ending with thresholding operations, were used to obtain the outlines of obstacles from the raw data of this laser scan. A theoretical analysis was carried out to show how proper value of threshold may be chosen. Computer simulations considered various mid-range boulders, for which the scheme was quite successful. The extension to other types of obstacles, such as craters, was considered. The special problems of bottom edge detection and scanning procedure are discussed.

Reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning.

PubMed

Song, Ying; Zhu, Zhen; Lu, Yang; Liu, Qiegen; Zhao, Jun

2014-03-01

To improve the magnetic resonance imaging (MRI) data acquisition speed while maintaining the reconstruction quality, a novel method is proposed for multislice MRI reconstruction from undersampled k-space data based on compressed-sensing theory using dictionary learning. There are two aspects to improve the reconstruction quality. One is that spatial correlation among slices is used by extending the atoms in dictionary learning from patches to blocks. The other is that the dictionary-learning scheme is used at two resolution levels; i.e., a low-resolution dictionary is used for sparse coding and a high-resolution dictionary is used for image updating. Numerical experiments are carried out on in vivo 3D MR images of brains and abdomens with a variety of undersampling schemes and ratios. The proposed method (dual-DLMRI) achieves better reconstruction quality than conventional reconstruction methods, with the peak signal-to-noise ratio being 7 dB higher. The advantages of the dual dictionaries are obvious compared with the single dictionary. Parameter variations ranging from 50% to 200% only bias the image quality within 15% in terms of the peak signal-to-noise ratio. Dual-DLMRI effectively uses the a priori information in the dual-dictionary scheme and provides dramatically improved reconstruction quality. Copyright © 2013 Wiley Periodicals, Inc.

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Laser-ablative engineering of phase singularities in plasmonic metamaterial arrays for biosensing applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aristov, Andrey I.; Kabashin, Andrei V., E-mail: kabashin@lp3.univ-mrs.fr; Zywietz, Urs

2014-02-17

By using methods of laser-induced transfer combined with nanoparticle lithography, we design and fabricate large-area gold nanoparticle-based metamaterial arrays exhibiting extreme Heaviside-like phase jumps in reflected light due to a strong diffractive coupling of localized plasmons. When employed in sensing schemes, these phase singularities provide the sensitivity of 5 × 10{sup 4} deg. of phase shift per refractive index unit change that is comparable with best values reported for plasmonic biosensors. The implementation of sensor platforms on the basis of such metamaterial arrays promises a drastic improvement of sensitivity and cost efficiency of plasmonic biosensing devices.

Self-Assembled InAs Nanowires as Optical Reflectors

PubMed Central

Floris, Francesco; Fornasari, Lucia; Marini, Andrea; Roddaro, Stefano; Beltram, Fabio; Cecchini, Marco; Sorba, Lucia; Rossella, Francesco

2017-01-01

Subwavelength nanostructured surfaces are realized with self-assembled vertically-aligned InAs nanowires, and their functionalities as optical reflectors are investigated. In our system, polarization-resolved specular reflectance displays strong modulations as a function of incident photon energy and angle. An effective-medium model allows one to rationalize the experimental findings in the long wavelength regime, whereas numerical simulations fully reproduce the experimental outcomes in the entire frequency range. The impact of the refractive index of the medium surrounding the nanostructure assembly on the reflectance was estimated. In view of the present results, sensing schemes compatible with microfluidic technologies and routes to innovative nanowire-based optical elements are discussed. PMID:29160860

Cavity enhanced atomic magnetometry

PubMed Central

Crepaz, Herbert; Ley, Li Yuan; Dumke, Rainer

2015-01-01

Atom sensing based on Faraday rotation is an indispensable method for precision measurements, universally suitable for both hot and cold atomic systems. Here we demonstrate an all-optical magnetometer where the optical cell for Faraday rotation spectroscopy is augmented with a low finesse cavity. Unlike in previous experiments, where specifically designed multipass cells had been employed, our scheme allows to use conventional, spherical vapour cells. Spherical shaped cells have the advantage that they can be effectively coated inside with a spin relaxation suppressing layer providing long spin coherence times without addition of a buffer gas. Cavity enhancement shows in an increase in optical polarization rotation and sensitivity compared to single-pass configurations. PMID:26481853

Research on robot mobile obstacle avoidance control based on visual information

NASA Astrophysics Data System (ADS)

Jin, Jiang

2018-03-01

Robots to detect obstacles and control robots to avoid obstacles has been a key research topic of robot control. In this paper, a scheme of visual information acquisition is proposed. By judging visual information, the visual information is transformed into the information source of path processing. In accordance with the established route, in the process of encountering obstacles, the algorithm real-time adjustment trajectory to meet the purpose of intelligent control of mobile robots. Simulation results show that, through the integration of visual sensing information, the obstacle information is fully obtained, while the real-time and accuracy of the robot movement control is guaranteed.

Classifying and Tracking Dust Plumes from Passive Remote Sensing

NASA Astrophysics Data System (ADS)

Bachl, Fabian E.; Garbe, Christoph S.

2012-03-01

Recent studies emphasize the role mineral dust aerosols play in terms of the earth's climate system, its radiation budget and microbial nutrition cycles. In order to gain further insight into the genesis and long term characteristics of dust events, processing setellite imagery is inevitable. We propose a fully Bayesian multispectral classification method that significantly facilitates this task. Using MSG-SEVIRI imagery we show that our technique allows to extract dust activity well enough to pave the way for a tracking scheme. Based on this procedure we derive an approach to identify regions that are likely to be the origin of emerging dust plumes.

Maximally Informative Statistics for Localization and Mapping

NASA Technical Reports Server (NTRS)

Deans, Matthew C.

2001-01-01

This paper presents an algorithm for localization and mapping for a mobile robot using monocular vision and odometry as its means of sensing. The approach uses the Variable State Dimension filtering (VSDF) framework to combine aspects of Extended Kalman filtering and nonlinear batch optimization. This paper describes two primary improvements to the VSDF. The first is to use an interpolation scheme based on Gaussian quadrature to linearize measurements rather than relying on analytic Jacobians. The second is to replace the inverse covariance matrix in the VSDF with its Cholesky factor to improve the computational complexity. Results of applying the filter to the problem of localization and mapping with omnidirectional vision are presented.

A Z-Axis Quartz Cross-Fork Micromachined Gyroscope Based on Shear Stress Detection

PubMed Central

Xie, Liqiang; Wu, Xuezhong; Li, Shengyi; Wang, Haoxu; Su, Jianbin; Dong, Peitao

2010-01-01

Here we propose a novel quartz micromachined gyroscope. The sensor has a simple cross-fork structure in the x-y plane of quartz crystal. Shear stress rather than normal stress is utilized to sense Coriolis’ force generated by the input angular rate signal. Compared to traditional quartz gyroscopes, which have two separate sense electrodes on each sidewall, there is only one electrode on each sidewall of the sense beam. As a result, the fabrication of the electrodes is simplified and the structure can be easily miniaturized. In order to increase sensitivity, a pair of proof masses is attached to the ends of the drive beam, and the sense beam has a tapered design. The structure is etched from a z-cut quartz wafer and the electrodes are realized by direct evaporation using the aperture mask method. The drive mode frequency of the prototype is 13.38 kHz, and the quality factor is approximately 1,000 in air. Therefore, the gyroscope can work properly without a vacuum package. The measurement ability of the shear stress detection design scheme is validated by the Coriolis’ force test. The performance of the sensor is characterized on a precision rate table using a specially designed readout circuit. The experimentally obtained scale factor is 1.45 mV/°/s and the nonlinearity is 3.6% in range of ±200 °/s. PMID:22294887

Precision sensing by two opposing gradient sensors: how does Escherichia coli find its preferred pH level?

PubMed

Hu, Bo; Tu, Yuhai

2013-07-02

It is essential for bacteria to find optimal conditions for their growth and survival. The optimal levels of certain environmental factors (such as pH and temperature) often correspond to some intermediate points of the respective gradients. This requires the ability of bacteria to navigate from both directions toward the optimum location and is distinct from the conventional unidirectional chemotactic strategy. Remarkably, Escherichia coli cells can perform such a precision sensing task in pH taxis by using the same chemotaxis machinery, but with opposite pH responses from two different chemoreceptors (Tar and Tsr). To understand bacterial pH sensing, we developed an Ising-type model for a mixed cluster of opposing receptors based on the push-pull mechanism. Our model can quantitatively explain experimental observations in pH taxis for various mutants and wild-type cells. We show how the preferred pH level depends on the relative abundance of the competing sensors and how the sensory activity regulates the behavioral response. Our model allows us to make quantitative predictions on signal integration of pH and chemoattractant stimuli. Our study reveals two general conditions and a robust push-pull scheme for precision sensing, which should be applicable in other adaptive sensory systems with opposing gradient sensors. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A Mutual Authentication Framework for Wireless Medical Sensor Networks.

PubMed

Srinivas, Jangirala; Mishra, Dheerendra; Mukhopadhyay, Sourav

2017-05-01

Wireless medical sensor networks (WMSN) comprise of distributed sensors, which can sense human physiological signs and monitor the health condition of the patient. It is observed that providing privacy to the patient's data is an important issue and can be challenging. The information passing is done via the public channel in WMSN. Thus, the patient, sensitive information can be obtained by eavesdropping or by unauthorized use of handheld devices which the health professionals use in monitoring the patient. Therefore, there is an essential need of restricting the unauthorized access to the patient's medical information. Hence, the efficient authentication scheme for the healthcare applications is needed to preserve the privacy of the patients' vital signs. To ensure secure and authorized communication in WMSN, we design a symmetric key based authentication protocol for WMSN environment. The proposed protocol uses only computationally efficient operations to achieve lightweight attribute. We analyze the security of the proposed protocol. We use a formal security proof algorithm to show the scheme security against known attacks. We also use the Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator to show protocol secure against man-in-the-middle attack and replay attack. Additionally, we adopt an informal analysis to discuss the key attributes of the proposed scheme. From the formal proof of security, we can see that an attacker has a negligible probability of breaking the protocol security. AVISPA simulator also demonstrates the proposed scheme security against active attacks, namely, man-in-the-middle attack and replay attack. Additionally, through the comparison of computational efficiency and security attributes with several recent results, proposed scheme seems to be battered.

Shoreline dynamics of the active Yellow River delta since the implementation of Water-Sediment Regulation Scheme: A remote-sensing and statistics-based approach

NASA Astrophysics Data System (ADS)

Fan, Yaoshen; Chen, Shenliang; Zhao, Bo; Pan, Shunqi; Jiang, Chao; Ji, Hongyu

2018-01-01

The Active Yellow River (Huanghe) Delta (AYRD) is a complex landform in which rapid deposition takes place due to its geologic formation and evolution. Continuous monitoring of shoreline dynamics at high-temporal frequency is crucial for understanding the processes and the driving factors behind this rapidly changing coast. Great efforts have been devoted to map the changing shoreline of the Yellow River delta and explain such changes through remote sensing data. However, the temporal frequency of shoreline in the obtained datasets are generally not fine enough to reflect the detailed or subtly variable processes of shoreline retreat and advance. To overcome these limitations, we continuously monitored the dynamics of this shoreline using time series of Landsat data based on tidal-level calibration model and orthogonal-transect method. The Abrupt Change Value (ACV) results indicated that the retreat-advance patterns had a significant impact regardless of season or year. The Water-Sediment Regulation Scheme (WSRS) plays a dominant role in delivering river sediment discharge to the sea and has an impact on the annual average maximum ACV, especially at the mouth of the river. The positive relationship among the average ACV, runoff and sediment load are relatively obvious; however, we found that the Relative Exposure Index (REI) that measures wave energy was able to explain only approximately 20% of the variation in the data. Based on the abrupt change at the shoreline of the AYRD, river flow and time, we developed a binary regression model to calculate the critical sediment load and water discharge for maintaining the equilibrium of the active delta from 2002 to 2015. These values were approximately 0.48 × 108 t/yr and 144.37 × 108 m3/yr. If the current water and sediment proportions released from the Xiaolangdi Reservoir during the WSRS remain stable, the erosion-accretion patterns of the active delta will shift from rapid accretion to a dynamic balance.