Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure

PubMed Central

Tang, Yongsheng; Wu, Zhishen

2016-01-01

Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures. PMID:26927110

Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure.

PubMed

Tang, Yongsheng; Wu, Zhishen

2016-02-25

Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures.

Extraordinary improvement of gas-sensing performances in SnO2 nanofibers due to creation of local p-n heterojunctions by loading reduced graphene oxide nanosheets.

PubMed

Lee, Jae-Hyoung; Katoch, Akash; Choi, Sun-Woo; Kim, Jae-Hun; Kim, Hyoun Woo; Kim, Sang Sub

2015-02-11

We propose a novel approach to improve the gas-sensing properties of n-type nanofibers (NFs) that involves creation of local p-n heterojunctions with p-type reduced graphene oxide (RGO) nanosheets (NSs). This work investigates the sensing behaviors of n-SnO2 NFs loaded with p-RGO NSs as a model system. n-SnO2 NFs demonstrated greatly improved gas-sensing performances when loaded with an optimized amount of p-RGO NSs. Loading an optimized amount of RGOs resulted in a 20-fold higher sensor response than that of pristine SnO2 NFs. The sensing mechanism of monolithic SnO2 NFs is based on the joint effects of modulation of the potential barrier at nanograin boundaries and radial modulation of the electron-depletion layer. In addition to the sensing mechanisms described above, enhanced sensing was obtained for p-RGO NS-loaded SnO2 NFs due to creation of local p-n heterojunctions, which not only provided a potential barrier, but also functioned as a local electron absorption reservoir. These mechanisms markedly increased the resistance of SnO2 NFs, and were the origin of intensified resistance modulation during interaction of analyte gases with preadsorbed oxygen species or with the surfaces and grain boundaries of NFs. The approach used in this work can be used to fabricate sensitive gas sensors based on n-type NFs.

Effects of stick dynamics on helicopter flying qualities

NASA Technical Reports Server (NTRS)

Watson, Douglas C.; Schroeder, Jeffery A.

1990-01-01

An experiment that investigated the influence of typical helicopter force-feel system dynamics on roll-axis handling qualities was conducted in concurrent ground and inflight simulations. Variations in lateral control natural frequency and damping ratio, effected by changes in inertia and damping, were evaluated in a disturbance-rejection task. Pilot ratings indicated a preference for low-inertia feel systems, although measured performance was relatively constant over the range of stick characteristics. Force-sensing was compared with position sensing as the input to the control system. Force-sensing improved performance but did not improve pilot ratings. Overall, the results indicated that control-stick dynamics, at least within a reasonable range, did not have a significant effect on pilot-vehicle performance. However, the physical effort required to maintain a desired pilot/manipulator bandwidth became objectionable as the stick inertia increased beyond 5-7 lbm, which was reflected in the pilot ratings and comments.

Optimization of strand displacement amplification-sensitized G-quadruplex DNAzyme-based sensing system and its application in activity detection of uracil-DNA glycosylase.

PubMed

Du, Yi-Chen; Jiang, Hong-Xin; Huo, Yan-Fang; Han, Gui-Mei; Kong, De-Ming

2016-03-15

As an isothermal nucleic acid amplification technique, strand displacement amplification (SDA) reaction has been introduced in G-quadruplex DNAzyme-based sensing system to improve the sensing performance. To further provide useful information for the design of SDA-amplified G-quadruplex DNAzyme-based sensors, the effects of nicking site number in SDA template DNA were investigated. With the increase of the nicking site number from 1 to 2, enrichment of G-quadruplex DNAzyme by SDA is changed from a linear amplification to an exponential amplification, thus greatly increasing the amplification efficiency and subsequently improving the sensing performance of corresponding sensing system. The nicking site number cannot be further increased because more nicking sites might result in high background signals. However, we demonstrated that G-quadruplex DNAzyme enrichment efficiency could be further improved by introducing a cross-triggered SDA strategy, in which two templates each has two nicking sites are used. To validate the proposed cross-triggered SDA strategy, we used it to develop a sensing platform for the detection of uracil-DNA glycosylase (UDG) activity. The sensor enables sensitive detection of UDG activity in the range of 1 × 10(-4)-1 U/mL with a detection limit of 1 × 10(-4)U/mL. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrated Remote Sensing Modalities for Classification at a Legacy Test Site

NASA Astrophysics Data System (ADS)

Lee, D. J.; Anderson, D.; Craven, J.

2016-12-01

Detecting, locating, and characterizing suspected underground nuclear test sites is of interest to the worldwide nonproliferation monitoring community. Remote sensing provides both cultural and surface geological information over a large search area in a non-intrusive manner. We have characterized a legacy nuclear test site at the Nevada National Security Site (NNSS) using an aerial system based on RGB imagery, light detection and ranging, and hyperspectral imaging. We integrate these different remote sensing modalities to perform pattern recognition and classification tasks on the test site. These tasks include detecting cultural artifacts and exotic materials. We evaluate if the integration of different remote sensing modalities improves classification performance.

Plasmonic Enhanced Infrared Detection with a Dynamic Hyper-Spectral Tuning

DTIC Science & Technology

2013-09-19

performance operation and use expensive optics for sensing color information in the infrared. The integration of metallic arrays with these detectors is...technology while significantly improving performance. surface plasmons, infrared detectors , quantum dots, multi-spectral sensing Unclassified...Research Laboratory (AFRL), Albuquerque NM, for theoretical and strategic support and University of New Mexico, NM for growth of the detector

Number sense across the lifespan as revealed by a massive Internet-based sample

PubMed Central

Halberda, Justin; Ly, Ryan; Wilmer, Jeremy B.; Naiman, Daniel Q.; Germine, Laura

2012-01-01

It has been difficult to determine how cognitive systems change over the grand time scale of an entire life, as few cognitive systems are well enough understood; observable in infants, adolescents, and adults; and simple enough to measure to empower comparisons across vastly different ages. Here we address this challenge with data from more than 10,000 participants ranging from 11 to 85 years of age and investigate the precision of basic numerical intuitions and their relation to students’ performance in school mathematics across the lifespan. We all share a foundational number sense that has been observed in adults, infants, and nonhuman animals, and that, in humans, is generated by neurons in the intraparietal sulcus. Individual differences in the precision of this evolutionarily ancient number sense may impact school mathematics performance in children; however, we know little of its role beyond childhood. Here we find that population trends suggest that the precision of one’s number sense improves throughout the school-age years, peaking quite late at ∼30 y. Despite this gradual developmental improvement, we find very large individual differences in number sense precision among people of the same age, and these differences relate to school mathematical performance throughout adolescence and the adult years. The large individual differences and prolonged development of number sense, paired with its consistent and specific link to mathematics ability across the age span, hold promise for the impact of educational interventions that target the number sense. PMID:22733748

Complex-Difference Constrained Compressed Sensing Reconstruction for Accelerated PRF Thermometry with Application to MRI Induced RF Heating

PubMed Central

Cao, Zhipeng; Oh, Sukhoon; Otazo, Ricardo; Sica, Christopher T.; Griswold, Mark A.; Collins, Christopher M.

2014-01-01

Purpose Introduce a novel compressed sensing reconstruction method to accelerate proton resonance frequency (PRF) shift temperature imaging for MRI induced radiofrequency (RF) heating evaluation. Methods A compressed sensing approach that exploits sparsity of the complex difference between post-heating and baseline images is proposed to accelerate PRF temperature mapping. The method exploits the intra- and inter-image correlations to promote sparsity and remove shared aliasing artifacts. Validations were performed on simulations and retrospectively undersampled data acquired in ex-vivo and in-vivo studies by comparing performance with previously proposed techniques. Results The proposed complex difference constrained compressed sensing reconstruction method improved the reconstruction of smooth and local PRF temperature change images compared to various available reconstruction methods in a simulation study, a retrospective study with heating of a human forearm in vivo, and a retrospective study with heating of a sample of beef ex vivo . Conclusion Complex difference based compressed sensing with utilization of a fully-sampled baseline image improves the reconstruction accuracy for accelerated PRF thermometry. It can be used to improve the volumetric coverage and temporal resolution in evaluation of RF heating due to MRI, and may help facilitate and validate temperature-based methods for safety assurance. PMID:24753099

Architecture effects of glucose oxidase/Au nanoparticle composite Langmuir-Blodgett films on glucose sensing performance

NASA Astrophysics Data System (ADS)

Wang, Ke-Hsuan; Wu, Jau-Yann; Chen, Liang-Huei; Lee, Yuh-Lang

2016-03-01

The Langmuir-Blodgett (LB) deposition technique is employed to prepare nano-composite films consisting of glucose oxidase (GOx) and gold nanoparticles (AuNPs) for glucose sensing applications. The GOx and AuNPs are co-adsorbed from an aqueous solution onto an air/liquid interface in the presence of an octadecylamine (ODA) template monolayer, forming a mixed (GOx-AuNP) monolayer. Alternatively, a composite film with a cascade architecture (AuNP/GOx) is also prepared by sequentially depositing monolayers of AuNPs and GOx. The architecture effects of the composite LB films on the glucose sensing are studied. The results show that the presence of AuNPs in the co-adsorption system does not affect the adsorption amount and preferred conformation (α-helix) of GOx. Furthermore, the incorporation of AuNPs in both composite films can significantly improve the sensing performance. However, the enhancement effects of the AuNPs in the two architectures are distinct. The major effect of the AuNPs is on the facilitation of charge-transfer in the (GOx-AuNP) film, but on the increase of catalytic activity in the (AuNP/GOx) one. Therefore, the sensing performance can be greatly improved by utilizing a film combining both architectures (AuNP/GOx-AuNP).

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

Efficient cooperative compressive spectrum sensing by identifying multi-candidate and exploiting deterministic matrix

NASA Astrophysics Data System (ADS)

Li, Jia; Wang, Qiang; Yan, Wenjie; Shen, Yi

2015-12-01

Cooperative spectrum sensing exploits the spatial diversity to improve the detection of occupied channels in cognitive radio networks (CRNs). Cooperative compressive spectrum sensing (CCSS) utilizing the sparsity of channel occupancy further improves the efficiency by reducing the number of reports without degrading detection performance. In this paper, we firstly and mainly propose the referred multi-candidate orthogonal matrix matching pursuit (MOMMP) algorithms to efficiently and effectively detect occupied channels at fusion center (FC), where multi-candidate identification and orthogonal projection are utilized to respectively reduce the number of required iterations and improve the probability of exact identification. Secondly, two common but different approaches based on threshold and Gaussian distribution are introduced to realize the multi-candidate identification. Moreover, to improve the detection accuracy and energy efficiency, we propose the matrix construction based on shrinkage and gradient descent (MCSGD) algorithm to provide a deterministic filter coefficient matrix of low t-average coherence. Finally, several numerical simulations validate that our proposals provide satisfactory performance with higher probability of detection, lower probability of false alarm and less detection time.

Observability-Based Guidance and Sensor Placement

NASA Astrophysics Data System (ADS)

Hinson, Brian T.

Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.

3D Architectured Graphene/Metal Oxide Hybrids for Gas Sensors: A Review

PubMed Central

Xia, Yi; Li, Ran; Chen, Ruosong; Wang, Jing; Xiang, Lan

2018-01-01

Graphene/metal oxide-based materials have been demonstrated as promising candidates for gas sensing applications due to the enhanced sensing performance and synergetic effects of the two components. Plenty of metal oxides such as SnO2, ZnO, WO3, etc. have been hybridized with graphene to improve the gas sensing properties. However, graphene/metal oxide nanohybrid- based gas sensors still have several limitations in practical application such as the insufficient sensitivity and response rate, and long recovery time in some cases. To achieve higher sensing performances of graphene/metal oxides nanocomposites, many recent efforts have been devoted to the controllable synthesis of 3D graphene/metal oxides architectures owing to their large surface area and well-organized structure for the enhanced gas adsorption/diffusion on sensing films. This review summarizes recent advances in the synthesis, assembly, and applications of 3D architectured graphene/metal oxide hybrids for gas sensing. PMID:29735951

Gas Sensing Properties of p-Co₃O₄/n-TiO₂ Nanotube Heterostructures.

PubMed

Alev, Onur; Kılıç, Alp; Çakırlar, Çiğdem; Büyükköse, Serkan; Öztürk, Zafer Ziya

2018-03-23

In this paper, we fabricated p-Co₃O₄/n-TiO₂ heterostructures and investigated their gas sensing properties. The structural and morphological characterization were performed by scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy analysis (XPS). The electrical properties of the heterostructure were studied within the temperature range from 293 K to 423 K. Changes in electrical properties and sensing behavior against reducing and oxidizing gases were attributed to the formation of p-n heterojunctions at the Co₃O₄ and TiO₂ interface. In comparison with sensing performed with pristine TiO₂ nanotubes (NTs), a significant improvement in H₂ sensing at 200 °C was observed, while the sensing response against NO₂ decreased for the heterostructures. Additionally, a response against toluene gas, in contrast to pristine TiO₂ NTs, appeared in the Co₃O₄/TiO₂ heterostructure samples.

Characterization and cysteine sensing performance of nanocomposites based on up-conversion excitation host and rhodamine-derived probes

NASA Astrophysics Data System (ADS)

Yuqing, Zhao; Yi, Xing; Lihua, Li; Juanjuan, Ma

2018-02-01

Optical sensing for cysteine (Cys) recognition is an interesting topic due to Cys biological participation. In this paper, two rhodamine-based chemosensors were designed for Cys optical sensing. For chemosensor photostability improvement, up-conversion nanocrystals were synthesized and used as excitation host. These nanocrystals were modified with a phase transfer reagent α-cyclodextrin (α-CD) to improve their compatibility with chemosensors. An efficient energy transfer from these nanocrystals to chemosensors under 980 nm radiation was observed and confirmed by spectral match analysis, energy transfer radius calculation and emission decay lifetime comparison. A direct bonding mechanism between Cys and chemosensors with bonding stoichiometry of 1:1 was established by Job's plot experiment. Given the presence of Cys, chemosensor emission was increased, showing emission turn on effect. These two chemosensors showed good selectivity, improved photostability and linear sensing response towards Cys.

TiO2-Based Nanoheterostructures for Promoting Gas Sensitivity Performance: Designs, Developments, and Prospects

PubMed Central

Wang, Yuan; Wu, Tao; Zhou, Yun; Meng, Chuanmin; Zhu, Wenjun; Liu, Lixin

2017-01-01

Gas sensors based on titanium dioxide (TiO2) have attracted much public attention during the past decades due to their excellent potential for applications in environmental pollution remediation, transportation industries, personal safety, biology, and medicine. Numerous efforts have therefore been devoted to improving the sensing performance of TiO2. In those effects, the construct of nanoheterostructures is a promising tactic in gas sensing modification, which shows superior sensing performance to that of the single component-based sensors. In this review, we briefly summarize and highlight the development of TiO2-based heterostructure gas sensing materials with diverse models, including semiconductor/semiconductor nanoheterostructures, noble metal/semiconductor nanoheterostructures, carbon-group-materials/semiconductor nano- heterostructures, and organic/inorganic nanoheterostructures, which have been investigated for effective enhancement of gas sensing properties through the increase of sensitivity, selectivity, and stability, decrease of optimal work temperature and response/recovery time, and minimization of detectable levels. PMID:28846621

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification.

Advanced materials for improving biosensing performances of propagating and localized plasmonic transducers

NASA Astrophysics Data System (ADS)

Manera, M. G.; Colombelli, A.; Convertino, A.; Rella, S.; De Lorenzis, E.; Taurino, A.; Malitesta, C.; Rella, R.

2015-05-01

Among all transduction methodologies reported in the field of solid state optical chemical sensors, the attention has been focused onto the optical sensing characterization by using propagating and localized surface plasmon resonance (SPR) techniques. The research in this field is always oriented in the improvement of the sensing features in terms of sensitivity and limits of detection. To this purpose different strategies have been proposed to realize advanced materials for high sensitive plasmonic devices. In this work nanostructured silica nanowires decorated by gold nanoparticles and active magneto-plasmonic transductors are considered as new biosensing transductors useful to increase the performance of sensitive devices.

Land use/cover classification in the Brazilian Amazon using satellite images.

PubMed

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira

2012-09-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Land use/cover classification in the Brazilian Amazon using satellite images

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant’Anna, Sidnei João Siqueira

2013-01-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data. PMID:24353353

Role of the heterojunctions in In2O3-composite SnO2 nanorod sensors and their remarkable gas-sensing performance for NOx at room temperature

NASA Astrophysics Data System (ADS)

Xu, Shuang; Gao, Jun; Wang, Linlin; Kan, Kan; Xie, Yu; Shen, Peikang; Li, Li; Shi, Keying

2015-08-01

Establishing heterostructures, as a good strategy to improve gas sensing performance, has been studied extensively. In this research, In2O3-composite SnO2 nanorod (ICTOs) heterostructures have been prepared via electrospinning, followed by calcination. It is found that In2O3 can improve the carrier density and oxygen deficiency of SnO2. In particular, the 3ICTO (Sn : In atom ratio of 25 : 0.3) nanorods with special particle distributions show an excellent sensing response towards different concentrations of NOx at room temperature. The highest sensing response is up to 8.98 for 100 ppm NOx with a fast response time of 4.67 s, which is over 11 times higher than that of pristine SnO2 nanorods at room temperature and the lowest detection limit is down to 0.1 ppm. More significantly, it presents good stability after 30 days for NOx of low concentration (0.1 ppm and 0.5 ppm). In addition, the rational band structure model combined with the surface depletion model which describe the NOx gas sensing mechanism of 3ICTO are presented. The 3ICTO nanorods may be promising in the application of gas sensors.Establishing heterostructures, as a good strategy to improve gas sensing performance, has been studied extensively. In this research, In2O3-composite SnO2 nanorod (ICTOs) heterostructures have been prepared via electrospinning, followed by calcination. It is found that In2O3 can improve the carrier density and oxygen deficiency of SnO2. In particular, the 3ICTO (Sn : In atom ratio of 25 : 0.3) nanorods with special particle distributions show an excellent sensing response towards different concentrations of NOx at room temperature. The highest sensing response is up to 8.98 for 100 ppm NOx with a fast response time of 4.67 s, which is over 11 times higher than that of pristine SnO2 nanorods at room temperature and the lowest detection limit is down to 0.1 ppm. More significantly, it presents good stability after 30 days for NOx of low concentration (0.1 ppm and 0.5 ppm). In addition, the rational band structure model combined with the surface depletion model which describe the NOx gas sensing mechanism of 3ICTO are presented. The 3ICTO nanorods may be promising in the application of gas sensors. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03796d

ARGOS wavefront sensing: from detection to correction

NASA Astrophysics Data System (ADS)

Orban de Xivry, Gilles; Bonaglia, M.; Borelli, J.; Busoni, L.; Connot, C.; Esposito, S.; Gaessler, W.; Kulas, M.; Mazzoni, T.; Puglisi, A.; Rabien, S.; Storm, J.; Ziegleder, J.

2014-08-01

Argos is the ground-layer adaptive optics system for the Large Binocular Telescope. In order to perform its wide-field correction, Argos uses three laser guide stars which sample the atmospheric turbulence. To perform the correction, Argos has at disposal three different wavefront sensing measurements : its three laser guide stars, a NGS tip-tilt, and a third wavefront sensor. We present the wavefront sensing architecture and its individual components, in particular: the finalized Argos pnCCD camera detecting the 3 laser guide stars at 1kHz, high quantum efficiency and 4e- noise; the Argos tip-tilt sensor based on a quad-cell avalanche photo-diodes; and the Argos wavefront computer. Being in the middle of the commissioning, we present the first wavefront sensing configurations and operations performed at LBT, and discuss further improvements in the measurements of the 3 laser guide star slopes as detected by the pnCCD.

Performance improvement of IPMC flow sensors with a biologically-inspired cupula structure

NASA Astrophysics Data System (ADS)

Lei, Hong; Sharif, Montassar Aidi; Paley, Derek A.; McHenry, Matthew J.; Tan, Xiaobo

2016-04-01

Ionic polymer-metal composites (IPMCs) have inherent underwater sensing and actuation properties. They can be used as sensors to collect flow information. Inspired by the hair-cell mediated receptor in the lateral line system of fish, the impact of a flexible, cupula-like structure on the performance of IPMC flow sensors is experimentally explored. The fabrication method to create a silicone-capped IPMC sensor is reported. Experiments are conducted to compare the sensing performance of the IPMC flow sensor before and after the PDMS coating under the periodic flow stimulus generated by a dipole source in still water and the laminar flow stimulus generated in a flow tank. Experimental results show that the performance of IPMC flow sensors is significantly improved under the stimulus of both periodic flow and laminar flow by the proposed silicone-capping.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Application of distributed optical fiber sensing technologies to the monitoring of leakage and abnormal disturbance of oil pipeline

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Zhu, Xiaofei; Deng, Chi; Li, Junyi; Liu, Cheng; Yu, Wenpeng; Luo, Hui

2017-10-01

To improve the level of management and monitoring of leakage and abnormal disturbance of long distance oil pipeline, the distributed optical fiber temperature and vibration sensing system is employed to test the feasibility for the healthy monitoring of a domestic oil pipeline. The simulating leakage and abnormal disturbance affairs of oil pipeline are performed in the experiment. It is demonstrated that the leakage and abnormal disturbance affairs of oil pipeline can be monitored and located accurately with the distributed optical fiber sensing system, which exhibits good performance in the sensitivity, reliability, operation and maintenance etc., and shows good market application prospect.

User-centric incentive design for participatory mobile phone sensing

NASA Astrophysics Data System (ADS)

Gao, Wei; Lu, Haoyang

2014-05-01

Mobile phone sensing is a critical underpinning of pervasive mobile computing, and is one of the key factors for improving people's quality of life in modern society via collective utilization of the on-board sensing capabilities of people's smartphones. The increasing demands for sensing services and ambient awareness in mobile environments highlight the necessity of active participation of individual mobile users in sensing tasks. User incentives for such participation have been continuously offered from an application-centric perspective, i.e., as payments from the sensing server, to compensate users' sensing costs. These payments, however, are manipulated to maximize the benefits of the sensing server, ignoring the runtime flexibility and benefits of participating users. This paper presents a novel framework of user-centric incentive design, and develops a universal sensing platform which translates heterogenous sensing tasks to a generic sensing plan specifying the task-independent requirements of sensing performance. We use this sensing plan as input to reduce three categories of sensing costs, which together cover the possible sources hindering users' participation in sensing.

Pressure sensing element based on the BN-graphene-BN heterostructure

NASA Astrophysics Data System (ADS)

Li, Mengwei; Wu, Chenggen; Zhao, Shiliang; Deng, Tao; Wang, Junqiang; Liu, Zewen; Wang, Li; Wang, Gao

2018-04-01

In this letter, we report a pressure sensing element based on the graphene-boron nitride (BN) heterostructure. The heterostructure consists of monolayer graphene sandwiched between two layers of vertically stacked dielectric BN nanofilms. The BN layers were used to protect the graphene layer from oxidation and pollution. Pressure tests were performed to investigate the characteristics of the BN-graphene-BN pressure sensing element. A sensitivity of 24.85 μV/V/mmHg is achieved in the pressure range of 130-180 kPa. After exposing the BN-graphene-BN pressure sensing element to the ambient environment for 7 days, the relative resistance change in the pressure sensing element is only 3.1%, while that of the reference open-faced graphene device without the BN protection layers is 15.7%. Thus, this strategy is promising for fabricating practical graphene pressure sensors with improved performance and stability.

Enhanced acoustic sensing through wave compression and pressure amplification in anisotropic metamaterials.

PubMed

Chen, Yongyao; Liu, Haijun; Reilly, Michael; Bae, Hyungdae; Yu, Miao

2014-10-15

Acoustic sensors play an important role in many areas, such as homeland security, navigation, communication, health care and industry. However, the fundamental pressure detection limit hinders the performance of current acoustic sensing technologies. Here, through analytical, numerical and experimental studies, we show that anisotropic acoustic metamaterials can be designed to have strong wave compression effect that renders direct amplification of pressure fields in metamaterials. This enables a sensing mechanism that can help overcome the detection limit of conventional acoustic sensing systems. We further demonstrate a metamaterial-enhanced acoustic sensing system that achieves more than 20 dB signal-to-noise enhancement (over an order of magnitude enhancement in detection limit). With this system, weak acoustic pulse signals overwhelmed by the noise are successfully recovered. This work opens up new vistas for the development of metamaterial-based acoustic sensors with improved performance and functionalities that are highly desirable for many applications.

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

PubMed

Wang, Xinhao; Chang, Te-Wei; Lin, Guohong; Gartia, Manas Ranjan; Liu, Gang Logan

2017-01-03

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Wang, Wenkai; Li, Husheng; Sun, Yan(Lindsay); Han, Zhu

2009-12-01

Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks, collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes, secondary users are usually assumed to report their sensing information honestly. However, compromised nodes can send false sensing information to mislead the system. In this paper, we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories. We calculate the suspicious level of all nodes based on their reports. The reports from nodes with high suspicious levels will be excluded in decision-making. Compared with existing defense methods, the proposed scheme can effectively differentiate malicious nodes and honest nodes. As a result, it can significantly improve the performance of collaborative sensing. For example, when there are 10 secondary users, with the primary user detection rate being equal to 0.99, one malicious user can make the false alarm rate [InlineEquation not available: see fulltext.] increase to 72%. The proposed scheme can reduce it to 5%. Two malicious users can make [InlineEquation not available: see fulltext.] increase to 85% and the proposed scheme reduces it to 8%.

Sensing Methods for Detecting Analog Television Signals

NASA Astrophysics Data System (ADS)

Rahman, Mohammad Azizur; Song, Chunyi; Harada, Hiroshi

This paper introduces a unified method of spectrum sensing for all existing analog television (TV) signals including NTSC, PAL and SECAM. We propose a correlation based method (CBM) with a single reference signal for sensing any analog TV signals. In addition we also propose an improved energy detection method. The CBM approach has been implemented in a hardware prototype specially designed for participating in Singapore TV white space (WS) test trial conducted by Infocomm Development Authority (IDA) of the Singapore government. Analytical and simulation results of the CBM method will be presented in the paper, as well as hardware testing results for sensing various analog TV signals. Both AWGN and fading channels will be considered. It is shown that the theoretical results closely match with those from simulations. Sensing performance of the hardware prototype will also be presented in fading environment by using a fading simulator. We present performance of the proposed techniques in terms of probability of false alarm, probability of detection, sensing time etc. We also present a comparative study of the various techniques.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Wuhan Ionospheric Oblique Backscattering Sounding System and Its Applications—A Review

PubMed Central

Shi, Shuzhu; Yang, Guobin; Jiang, Chunhua; Zhang, Yuannong; Zhao, Zhengyu

2017-01-01

For decades, high-frequency (HF) radar has played an important role in sensing the Earth’s environment. Advances in radar technology are providing opportunities to significantly improve the performance of HF radar, and to introduce more applications. This paper presents a low-power, small-size, and multifunctional HF radar developed by the Ionospheric Laboratory of Wuhan University, referred to as the Wuhan Ionospheric Oblique Backscattering Sounding System (WIOBSS). Progress in the development of this radar is described in detail, including the basic principles of operation, the system configuration, the sounding waveforms, and the signal and data processing methods. Furthermore, its various remote sensing applications are briefly reviewed to show the good performance of this radar. Finally, some suggested solutions are given for further improvement of its performance. PMID:28629157

CeO₂ Enhanced Ethanol Sensing Performance in a CdS Gas Sensor.

PubMed

Li, Meishan; Ren, Wei; Wu, Rong; Zhang, Min

2017-07-05

CdS nanowires (NWs) were fabricated through a facile low-temperature solvothermal method, following which CeO₂ nanoparticles were modified on the NWs. The ethanol sensing characteristics of pure CdS and decorated ones with different CeO₂ content were studied. It was found that the sensing performance of CdS was significantly improved after CeO₂ decoration. In particular, the 5 at% CeO₂/CdS composite exhibited a much higher response to 100 ppm ethanol (about 52), which was 2.6 times larger than that of pure CdS. A fast response and recovery time (less than 12 s and 3 s, respectively) were obtained as well as an excellent selectivity. These results make the CeO₂-decorated CdS NWs good candidates for ethanol sensing applications.

Metal nanostructures for non-enzymatic glucose sensing.

PubMed

Tee, Si Yin; Teng, Choon Peng; Ye, Enyi

2017-01-01

This review covers the recent development of metal nanostructures in electrochemical non-enzymatic glucose sensing. It highlights a variety of nanostructured materials including noble metals, other transition metals, bimetallic systems, and their hybrid with carbon-based nanomaterials. Particularly, attention is devoted to numerous approaches that have been implemented for improving the sensors performance by tailoring size, shape, composition, effective surface area, adsorption capability and electron-transfer properties. The correlation of the metal nanostructures to the glucose sensing performance is addressed with respect to the linear concentration range, sensitivity and detection limit. In overall, this review provides important clues from the recent scientific achievements of glucose sensor nanomaterials which will be essentially useful in designing better and more effective electrocatalysts for future electrochemical sensing industry. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Experimental results for correlation-based wavefront sensing

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

Poyneer, L A; Palmer, D W; LaFortune, K N

2005-07-01

Correlation wave-front sensing can improve Adaptive Optics (AO) system performance in two keys areas. For point-source-based AO systems, Correlation is more accurate, more robust to changing conditions and provides lower noise than a centroiding algorithm. Experimental results from the Lick AO system and the SSHCL laser AO system confirm this. For remote imaging, Correlation enables the use of extended objects for wave-front sensing. Results from short horizontal-path experiments will show algorithm properties and requirements.

Analysis of Employee Engagement to Improve the Performance of Retail Risk Group PT Bank Mandiri

ERIC Educational Resources Information Center

Wiseto, Artody; Hubeis, Aida Vitayala; Sukandar, Dadang

2016-01-01

Nowadays, every company requires their employees have a bound sense to their company. It's called engagement. Also have that expectation, PT Bank Mandiri (Persero) Tbk, Bank with the largest assets in Indonesia. PT Bank Mandiri (Persero) Tbk expect which employee engagement can improve the performance such as financial, service, and production…

Making Sense of School Turnarounds

ERIC Educational Resources Information Center

Hess, Frederick M.

2012-01-01

Today, in a sector flooded with $3.5 billion in School Improvement Grant funds and the resulting improvement plans, there's great faith that "turnaround" strategies are a promising way to tackle stubborn problems with persistently low-performing schools. Unlike traditional reform efforts, with their emphasis on incremental improvement, turnarounds…

Effects of mindfulness meditation on three individuals with aphasia.

PubMed

Orenstein, Ellen; Basilakos, Alexandra; Marshall, Rebecca Shisler

2012-01-01

There is evidence to suggest that people with aphasia (PWA) may have deficits in attention stemming from the inefficient allocation of resources. The inaccurate perception of task demand, or sense of effort, may underlie the misallocation of the available attention resources. Given the lack of treatment options for improving attention in aphasia, Mindfulness Meditation, shown to improve attention in neurologically intact individuals, may prove effective in increasing attention in PWA. The purpose of the present study was to determine if Mindfulness Meditation improves divided attention or language in PWA and if it affects the overall sense of effort. A multiple baseline single-subject design was used to determine the effects of Mindfulness Meditation on divided attention for three PWA. Divided attention was measured using a non-linguistic divided attention task. Visual inspection of the data was used to determine changes in performance (sense of effort, reaction time and accuracy, language) over time. High performance observed on the attention measures suggests that PWA have varying degrees of attentional impairment that may surface when certain demands are presented. There were no observable changes in the performance on the sense of effort or language measures; however, measures of reaction time may indicate Mindfulness Meditation improved efficiency of task completion. All three participants reported that Mindfulness Meditation was easy to learn and carry out on a daily basis, and reported feeling more 'relaxed' and 'peaceful' after Mindfulness Meditation training than before. With the knowledge that PWA can learn meditative practices, and with such successful findings in neurologically intact individuals, it is important to continue evaluating the benefits of Mindfulness Meditation in PWA. © 2012 Royal College of Speech and Language Therapists.

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: part II--Optimization of structural sensor placement.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-04-01

The work proposed an optimization approach for structural sensor placement to improve the performance of vibro-acoustic virtual sensor for active noise control applications. The vibro-acoustic virtual sensor was designed to estimate the interior sound pressure of an acoustic-structural coupled enclosure using structural sensors. A spectral-spatial performance metric was proposed, which was used to quantify the averaged structural sensor output energy of a vibro-acoustic system excited by a spatially varying point source. It was shown that (i) the overall virtual sensing error energy was contributed additively by the modal virtual sensing error and the measurement noise energy; (ii) each of the modal virtual sensing error system was contributed by both the modal observability levels for the structural sensing and the target acoustic virtual sensing; and further (iii) the strength of each modal observability level was influenced by the modal coupling and resonance frequencies of the associated uncoupled structural/cavity modes. An optimal design of structural sensor placement was proposed to achieve sufficiently high modal observability levels for certain important panel- and cavity-controlled modes. Numerical analysis on a panel-cavity system demonstrated the importance of structural sensor placement on virtual sensing and active noise control performance, particularly for cavity-controlled modes.

Synthesis, Fabrication and Characterization of ZnO-Based Thin Films Prepared by Sol-Gel Process and H2 Gas Sensing Performance

NASA Astrophysics Data System (ADS)

Dey, Anup; Roy, Subhashis; Sarkar, Subir Kumar

2018-03-01

In this paper, an attempt is made to deposit ZnO thin films using sol-gel process followed by dip-coating method on p-silicon (100) substrates for intended application as a hydrogen gas sensor owing to the low toxic nature and thermal stability of ZnO. The thin films are annealed under annealing temperatures of 350, 450 and 550 °C for 25 min. The crystalline quality of the fabricated thin films is then analyzed by field-emission scanning electron microscopy and transmission electron microscope. The gas sensing performance analysis of ZnO thin films is demonstrated at different annealing temperatures and hydrogen gas concentrations ranging from 100 to 3000 ppm. Results obtained show that the sensitivity is significantly improved as annealing temperature increases with maximum sensitivity being achieved at 550 °C annealing temperature and operating temperature of 150 °C. Hence, the modified ZnO thin films can be applicable as H2 gas sensing device showing to the improved performance in comparison with unmodified thin-film sensor.

A Localized Surface Plasmon Resonance Sensor Using Double-Metal-Complex Nanostructures and a Review of Recent Approaches

PubMed Central

Ahn, Heesang; Song, Hyerin; Kim, Kyujung

2017-01-01

From active developments and applications of various devices to acquire outside and inside information and to operate based on feedback from that information, the sensor market is growing rapidly. In accordance to this trend, the surface plasmon resonance (SPR) sensor, an optical sensor, has been actively developed for high-sensitivity real-time detection. In this study, the fundamentals of SPR sensors and recent approaches for enhancing sensing performance are reported. In the section on the fundamentals of SPR sensors, a brief description of surface plasmon phenomena, SPR, SPR-based sensing applications, and several configuration types of SPR sensors are introduced. In addition, advanced nanotechnology- and nanofabrication-based techniques for improving the sensing performance of SPR sensors are proposed: (1) localized SPR (LSPR) using nanostructures or nanoparticles; (2) long-range SPR (LRSPR); and (3) double-metal-layer SPR sensors for additional performance improvements. Consequently, a high-sensitivity, high-biocompatibility SPR sensor method is suggested. Moreover, we briefly describe issues (miniaturization and communication technology integration) for future SPR sensors. PMID:29301238

Carbon nanotube-embedded advanced aerospace composites for early-stage damage sensing

NASA Astrophysics Data System (ADS)

Nataraj, Latha; Coatney, Michael; Cain, Jason; Hall, Asha

2018-03-01

Fiber reinforced polymer (FRP) composites featuring outstanding fatigue performance, high specific stiffness and strength, and low density have evolved as critical structural materials in aerospace applications. Microscale damage such as fiber breakage, matrix cracking, and delamination could occur in layered composites compromising structural integrity, emphasizing the critical need to monitor structural health. Early damage detection would lead to enhanced reliability, lifetime, and performance while minimizing maintenance time, leading to enormous scientific and technical interest in realizing physically stable, quick responding, and cost effective strain sensing materials, devices, and techniques with high sensitivity over a broad range of the practical strain spectrum. Today's most commonly used strain sensing techniques are metal foil strain gauges and optical fiber sensors. Metal foil gauges offer high stability and cost-effectiveness but can only be surface-mounted and have a low gauge factor. Optical fibers require expensive instrumentation, are mostly insensitive to cracks parallel to the fiber orientation and may lead to crack initiation as the diameter is larger than that of the reinforcement fibers. Carbon nanotubes (CNTs) have attracted much attention due to high aspect ratio and superior electrical, thermal, and mechanical properties. CNTs embedded in layered composites have improved performance. A variety of CNT architectures and configurations have shown improved piezoresistive behavior and stability for sensing applications. However, scaling up and commercialization remain serious challenges. The current study investigates a simple, cost effective and repeatable technique for highly sensitive, stable, linear and repeatable strain sensing for damage detection by integrating CNT laminates into composites.

High Surface Area MoS 2/Graphene Hybrid Aerogel for Ultrasensitive NO 2 Detection

DOE PAGES

Long, Hu; Harley-Trochimczyk, Anna; Pham, Thang; ...

2016-05-23

A MoS 2/graphene hybrid aerogel synthesized with two-dimensional MoS 2 sheets coating a high surface area graphene aerogel scaffold is characterized and used for ultrasensitive NO 2 detection. The combination of graphene and MoS 2 leads to improved sensing properties with the graphene scaffold providing high specific surface area and high electrical and thermal conductivity and the single to few-layer MoS2 sheets providing high sensitivity and selectivity to NO 2. The hybrid aerogel is integrated onto a low-power microheater platform to probe the gas sensing performance. At room temperature, the sensor exhibits an ultralow detection limit of 50 ppb NOmore » 2. By heating the material to 200 °C, the response and recovery times to reach 90% of the final signal decrease to <1 min, while retaining the low detection limit. The MoS 2/graphene hybrid also shows good selectivity for NO 2 against H 2 and CO, especially when compared to bare graphene aerogel. The unique structure of the hybrid aerogel is responsible for the ultrasensitive, selective, and fast NO 2 sensing. The improved sensing performance of this hybrid aerogel also suggests the possibility of other 2D material combinations for further sensing applications.« less

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy.

PubMed

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Fiber-optic Sensor Demonstrator (FSD) integration with PROBA-2

NASA Astrophysics Data System (ADS)

Reutlinger, Arnd; Glier, Markus; Zuknik, Karl-Heinz; Hoffmann, Lars; Müller, Mathias; Rapp, Stephan; Kurvin, Charles; Ernst, Thomas; McKenzie, Iain; Karafolas, Nikos

2017-11-01

Modern telecommunication satellites can benefit from the features of fiber optic sensing wrt to mass savings, improved performance and lower costs. Within the course of a technology study, launched by the European Space Agency, a fiber optic sensing system has been designed and is to be tested on representative mockups of satellite sectors and environment.

Will algorithms modified with soil and weather information improve in-field reflectance-sensing corn nitrogen applications?

USDA-ARS?s Scientific Manuscript database

Nitrogen (N) needs to support corn (Zea mays L.) production can be highly variable within fields. Canopy reflectance sensing for assessing crop N health has been implemented on many farmers’ fields to side-dress or top-dress variable-rate N application, but at times farmers report the performance of...

Study on additional carrier sensing for IEEE 802.15.4 wireless sensor networks.

PubMed

Lee, Bih-Hwang; Lai, Ruei-Lung; Wu, Huai-Kuei; Wong, Chi-Ming

2010-01-01

Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the guise of low-rate and short-distance wireless personal area networks (WPANs). The slotted carrier sense multiple access with collision avoidance (CSMA/CA) is used for contention mechanism. Sensor nodes perform a backoff process as soon as the clear channel assessment (CCA) detects a busy channel. In doing so they may neglect the implicit information of the failed CCA detection and further cause the redundant sensing. The blind backoff process in the slotted CSMA/CA will cause lower channel utilization. This paper proposes an additional carrier sensing (ACS) algorithm based on IEEE 802.15.4 to enhance the carrier sensing mechanism for the original slotted CSMA/CA. An analytical Markov chain model is developed to evaluate the performance of the ACS algorithm. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which in turn significantly improves throughput, average medium access control (MAC) delay and power consumption of CCA detection.

Long-term neuromuscular training and ankle joint position sense.

PubMed

Kynsburg, A; Pánics, G; Halasi, T

2010-06-01

Preventive effect of proprioceptive training is proven by decreasing injury incidence, but its proprioceptive mechanism is not. Major hypothesis: the training has a positive long-term effect on ankle joint position sense in athletes of a high-risk sport (handball). Ten elite-level female handball-players represented the intervention group (training-group), 10 healthy athletes of other sports formed the control-group. Proprioceptive training was incorporated into the regular training regimen of the training-group. Ankle joint position sense function was measured with the "slope-box" test, first described by Robbins et al. Testing was performed one day before the intervention and 20 months later. Mean absolute estimate errors were processed for statistical analysis. Proprioceptive sensory function improved regarding all four directions with a high significance (p<0.0001; avg. mean estimate error improvement: 1.77 degrees). This was also highly significant (p< or =0.0002) in each single directions, with avg. mean estimate error improvement between 1.59 degrees (posterior) and 2.03 degrees (anterior). Mean absolute estimate errors at follow-up (2.24 degrees +/-0.88 degrees) were significantly lower than in uninjured controls (3.29 degrees +/-1.15 degrees) (p<0.0001). Long-term neuromuscular training has improved ankle joint position sense function in the investigated athletes. This joint position sense improvement can be one of the explanations for injury rate reduction effect of neuromuscular training.

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

NASA Astrophysics Data System (ADS)

Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez-Suarez, Juan Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali M.; Hain, Christopher R.; Sharifi, Amirreza

2018-01-01

As the global demands for the use of freshwater resources continues to rise, it has become increasingly important to insure the sustainability of this resources. This is accomplished through the use of management strategies that often utilize monitoring and the use of hydrological models. However, monitoring at large scales is not feasible and therefore model applications are becoming challenging, especially when spatially distributed datasets, such as evapotranspiration, are needed to understand the model performances. Due to these limitations, most of the hydrological models are only calibrated for data obtained from site/point observations, such as streamflow. Therefore, the main focus of this paper is to examine whether the incorporation of remotely sensed and spatially distributed datasets can improve the overall performance of the model. In this study, actual evapotranspiration (ETa) data was obtained from the two different sets of satellite based remote sensing data. One dataset estimates ETa based on the Simplified Surface Energy Balance (SSEBop) model while the other one estimates ETa based on the Atmosphere-Land Exchange Inverse (ALEXI) model. The hydrological model used in this study is the Soil and Water Assessment Tool (SWAT), which was calibrated against spatially distributed ETa and single point streamflow records for the Honeyoey Creek-Pine Creek Watershed, located in Michigan, USA. Two different techniques, multi-variable and genetic algorithm, were used to calibrate the SWAT model. Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73-0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error - observations standard deviation ratio (RSR) values <0.7 (0.39-0.52). However, the genetic algorithm technique was more effective with the ETa calibration while significantly reducing the model performance for estimating the streamflow (NSE: 0.32-0.52, PBIAS: ±32.73%, and RSR: 0.63-0.82). Meanwhile, using the multi-variable technique, the model performance for estimating the streamflow was maintained with a high level of accuracy (NSE: 0.59-0.61, PBIAS: ±13.70%, and RSR: 0.63-0.64) while the evapotranspiration estimations were improved. Results from this assessment shows that incorporation of remotely sensed and spatially distributed data can improve the hydrological model performance if it is coupled with a right calibration technique.

Rhodamine spirolactam sensors operated by sulfur-cooperated metal complexation

NASA Astrophysics Data System (ADS)

Heo, Gisuk; Lee, Dahye; Kim, Chi Gwan; Do, Jung Yun

2018-01-01

New rhodamine Schiff base sensors were developed to improve selective sensing by introducing sulfide, ester, and dithiocarbonate groups, as well as using ketones coupled to rhodamine-hydrazine. Metal sensing proceeded through the 1:1 complexation of the metal ion for most sensors in the presence of Cu2 + and Hg2 +. A sensor carrying a dithiocarbonate group responded selectively to Hg2 + showing a strong colorimetric change and intense fluorescence. The association constants of the sensors were determined from a linear plot performed at micro-molar concentrations to afford values in the range of 104. Sensing was interrupted at the initial time of Hg2 + exposure due to the isomerization of imine and preferential metal bonding of two dithiocarbonate groups regardless of the main structure of rhodamine. The sensors exhibited the reversible and reproducible performance for Hg2 + sensing.

Feasibility of an Orthogonal Redundant Sensor incorporating Optical plus Redundant Electrochemical Glucose Sensing.

PubMed

McAuley, Sybil A; Dang, Tri T; Horsburgh, Jodie C; Bansal, Anubhuti; Ward, Glenn M; Aroyan, Sarkis; Jenkins, Alicia J; MacIsaac, Richard J; Shah, Rajiv V; O'Neal, David N

2016-05-01

Orthogonal redundancy for glucose sensing (multiple sensing elements utilizing distinct methodologies) may enhance performance compared to nonredundant sensors, and to sensors with multiple elements utilizing the same technology (simple redundancy). We compared the performance of a prototype orthogonal redundant sensor (ORS) combining optical fluorescence and redundant electrochemical sensing via a single insertion platform to an electrochemical simple redundant sensor (SRS). Twenty-one adults with type 1 diabetes wore an ORS and an SRS concurrently for 7 days. Following sensor insertion, and on Day 4 with a standardized meal, frequent venous samples were collected for reference glucose measurement (laboratory [YSI] and meter) over 3 and 4 hours, respectively. Between study visits reference capillary blood glucose testing was undertaken. Sensor data were processed prospectively. ORS mean absolute relative difference (MARD) was (mean ± SD) 10.5 ± 13.2% versus SRS 11.0 ± 10.4% (P = .34). ORS values in Clarke error grid zones A and A+B were 88.1% and 97.6%, respectively, versus SRS 86.4% and 97.8%, respectively (P = .23 and P = .84). ORS Day 1 MARD (10.7 ± 10.7%) was superior to SRS (16.5 ± 13.4%; P < .0001), and comparable to ORS MARD for the week. ORS sensor survival (time-averaged mean) was 92.1% versus SRS 74.4% (P = .10). ORS display time (96.0 ± 5.8%) was equivalent to SRS (95.6 ± 8.9%; P = .87). Combining simple and orthogonal sensor redundancy via a single insertion is feasible, with accuracy comparing favorably to current generation nonredundant sensors. Addition of an optical component potentially improves sensor reliability compared to electrochemical sensing alone. Further improvement in optical sensing performance is required prior to clinical application. © 2016 Diabetes Technology Society.

Effect of ordered mesoporous carbon contact layer on the sensing performance of sputtered RuO2 thin film pH sensor.

PubMed

Lonsdale, W; Maurya, D K; Wajrak, M; Alameh, K

2017-03-01

The effect of contact layer on the pH sensing performance of a sputtered RuO 2 thin film pH sensor is investigated. The response of pH sensors employing RuO 2 thin film electrodes on screen-printed Pt, carbon and ordered mesoporous carbon (OMC) contact layers are measured over a pH range from 4 to 10. Working electrodes with OMC contact layer are found to have Nernstian pH sensitivity (-58.4mV/pH), low short-term drift rate (5.0mV/h), low hysteresis values (1.13mV) and fast reaction times (30s), after only 1h of conditioning. A pH sensor constructed with OMC carbon contact layer displays improved sensing performance compared to Pt and carbon-based counterparts, making this electrode more attractive for applications requiring highly-accurate pH sensing with reduced conditioning time. Copyright © 2016 Elsevier B.V. All rights reserved.

Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation.

PubMed

Jimeno Yepes, Antonio

2017-09-01

Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation. Features extracted from the context of an ambiguous word are used to identify the proper sense of such a word. The type of features have an impact on machine learning methods, thus affect disambiguation performance. In this work, we have evaluated several types of features derived from the context of the ambiguous word and we have explored as well more global features derived from MEDLINE using word embeddings. Results show that word embeddings improve the performance of more traditional features and allow as well using recurrent neural network classifiers based on Long-Short Term Memory (LSTM) nodes. The combination of unigrams and word embeddings with an SVM sets a new state of the art performance with a macro accuracy of 95.97 in the MSH WSD data set. Copyright © 2017 Elsevier Inc. All rights reserved.

Cervical joint position sense in neck pain. Immediate effects of muscle vibration versus mental training interventions: a RCT.

PubMed

Beinert, K; Preiss, S; Huber, M; Taube, W

2015-12-01

Impaired cervical joint position sense is a feature of chronic neck pain and is commonly argued to rely on abnormal cervical input. If true, muscle vibration, altering afferent input, but not mental interventions, should have an effect on head repositioning acuity and neck pain perception. The aim of the present study was to determine the short-term effects of neck muscle vibration, motor imagery, and action observation on cervical joint position sense and pressure pain threshold in people with chronic neck pain. Forty-five blinded participants with neck pain received concealed allocation and were randomized in three treatment groups. A blinded assessor performed pre- and post-test measurement. Patients were recruited from secondary outpatient clinics in the southwest of Germany. Chronic, non specific neck pain patients without arm pain were recruited for this study. A single intervention session of 5 minutes was delivered to each blinded participant. Patients were either allocated to one of the following three interventions: (1) neck muscle vibration; (2) motor imagery; (3) action observation. Primary outcomes were cervical joint position sense acuity and pressure pain threshold. Repeated measures ANOVAs were used to evaluate differences between groups and subjects. Repositioning acuity displayed significant time effects for vibration, motor imagery, and action observation (all P<0.05), but revealed no time*group effect. Pressure pain threshold demonstrated a time*group effect (P=0.042) as only vibration significantly increased pressure pain threshold (P=0.01). Although motor imagery and action observation did not modulate proprioceptive, afferent input, they nevertheless improved cervical joint position sense acuity. This indicates that, against the common opinion, changes in proprioceptive input are not prerequisite to improve joint repositioning performance. However, the short-term applications of these cognitive treatments had no effect on pressure pain thresholds, whereas vibration reduced pressure pain thresholds. This implies different underlying mechanisms after vibration and mental training. Mental interventions were effective in improving cervical joint position sense and are easy to integrate in rehabilitation regimes. Neck muscle vibration is effective in improving cervical joint position sense and pressure pain thresholds within 5 minutes of application.

Position and speed control of brushless DC motors using sensorless techniques and application trends.

PubMed

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

A Survey on Gas Sensing Technology

PubMed Central

Liu, Xiao; Cheng, Sitian; Liu, Hong; Hu, Sha; Zhang, Daqiang; Ning, Huansheng

2012-01-01

Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches. PMID:23012563

Strategies for Improving the Performance of Sensors Based on Organic Field-Effect Transistors.

PubMed

Wu, Xiaohan; Mao, Shun; Chen, Junhong; Huang, Jia

2018-04-01

Organic semiconductors (OSCs) have been extensively studied as sensing channel materials in field-effect transistors due to their unique charge transport properties. Stimulation caused by its environmental conditions can readily change the charge-carrier density and mobility of OSCs. Organic field-effect transistors (OFETs) can act as both signal transducers and signal amplifiers, which greatly simplifies the device structure. Over the past decades, various sensors based on OFETs have been developed, including physical sensors, chemical sensors, biosensors, and integrated sensor arrays with advanced functionalities. However, the performance of OFET-based sensors still needs to be improved to meet the requirements from various practical applications, such as high sensitivity, high selectivity, and rapid response speed. Tailoring molecular structures and micro/nanofilm structures of OSCs is a vital strategy for achieving better sensing performance. Modification of the dielectric layer and the semiconductor/dielectric interface is another approach for improving the sensor performance. Moreover, advanced sensory functionalities have been achieved by developing integrated device arrays. Here, a brief review of strategies used for improving the performance of OFET sensors is presented, which is expected to inspire and provide guidance for the design of future OFET sensors for various specific and practical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

Effective application of optical sensing technology for sustainable liquid level sensing and rainfall measurement

NASA Astrophysics Data System (ADS)

Afzal, Muhammad Hassan Bin

2015-05-01

Rainfall measurement is performed on regular basis to facilitate effectively the weather stations and local inhabitants. Different types of rain gauges are available with different measuring principle for rainfall measurement. In this research work, a novel optical rain sensor is designed, which precisely calculate the rainfall level according to rainfall intensity. This proposed optical rain sensor model introduced in this paper, which is basically designed for remote sensing of rainfall and it designated as R-ORMS (Remote Optical Rainfall Measurement sensor). This sensor is combination of some improved method of tipping bucket rain gauge and most of the optical hydreon rain sensor's principle. This optical sensor can detect the starting time and ending time of rain, rain intensity and rainfall level. An infrared beam from Light Emitting Diode (LED) through powerful convex lens can accurately determines the diameter of each rain drops by total internal reflection principle. Calculations of these accumulative results determine the rain intensity and rainfall level. Accurate rainfall level is determined by internal optical LED based sensor which is embedded in bucket wall. This internal sensor is also following the total internal reflection (TIR) principle and the Fresnel's law. This is an entirely novel design of optical sensing principle based rain sensor and also suitable for remote sensing rainfall level. The performance of this proposed sensor has been comprehensively compared with other sensors with similar attributes and it showed better and sustainable result. Future related works have been proposed at the end of this paper, to provide improved and enhanced performance of proposed novel rain sensor.

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.

Childhood school segregation and later life sense of control and physical performance in the African American Health cohort.

PubMed

Wolinsky, Fredric D; Andresen, Elena M; Malmstrom, Theodore K; Miller, J Philip; Schootman, Mario; Miller, Douglas K

2012-09-27

The association between childhood school desegregation and later life sense of control and physical performance among African Americans is not clear. We hypothesized that childhood school desegregation adversely affected the sense of control of in later life, and that this reduced sense of control accounts in part for reduced physical performance. In-home follow-up assessments were completed in 2010 with 582 of the 58-74 year old men and women participating in the on-going African American Health cohort. We used these data to examine the relationship between (a) retrospective self-reports of attending segregated schools during one's 1st-to-12th grade education and one's current sense of control, as well as (b) the association between current sense of control and physical performance. Multiple linear regression analysis with propensity score re-weighting was used. Attending segregated schools for at least half of one's 1st-to-12th grade education was significantly associated with higher scores on the sense of control. Adjusting for all covariates and potential confounders, those receiving half or more of their 1st-to-12th grade education in segregated schools had sense of control scores that were .886 points higher (p ≤ .01; standardized effect size = .22). Sense of control scores were independently (all p < .01) associated with better systolic blood pressure, grip strength, peak expiratory flow, chair stands, balance tests, and the Short Portable Physical Battery even after adjusting for all covariates and potential confounders. Moreover, sense of control scores either partially or fully mediated the statistically significant beneficial associations between childhood school segregation and physical performance. Childhood school desegregation was adversely associated with the sense of control of African Americans in later life, and this reduced sense of control appears, in part, to account for their poorer physical performance. The etiologic mechanism through which childhood school segregation at the time that this cohort experienced it improved the sense of control in later life, which subsequently led to better physical performance, has not been identified. We suspect, however, that the pathway involves greater exposure to racial solidarity, same-race students as peer role models and same-race teachers and principals as authority role models, the reduced likelihood of exposure to race-based discrimination or antagonism during their formative early lives, and greater exposure to encouragement and support for academic and life success.

Childhood school segregation and later life sense of control and physical performance in the African American Health cohort

PubMed Central

2012-01-01

Background The association between childhood school desegregation and later life sense of control and physical performance among African Americans is not clear. We hypothesized that childhood school desegregation adversely affected the sense of control of in later life, and that this reduced sense of control accounts in part for reduced physical performance. Methods In-home follow-up assessments were completed in 2010 with 582 of the 58–74 year old men and women participating in the on-going African American Health cohort. We used these data to examine the relationship between (a) retrospective self-reports of attending segregated schools during one’s 1st-to-12th grade education and one’s current sense of control, as well as (b) the association between current sense of control and physical performance. Multiple linear regression analysis with propensity score re-weighting was used. Results Attending segregated schools for at least half of one’s 1st-to-12th grade education was significantly associated with higher scores on the sense of control. Adjusting for all covariates and potential confounders, those receiving half or more of their 1st-to-12th grade education in segregated schools had sense of control scores that were .886 points higher (p ≤ .01; standardized effect size = .22). Sense of control scores were independently (all p < .01) associated with better systolic blood pressure, grip strength, peak expiratory flow, chair stands, balance tests, and the Short Portable Physical Battery even after adjusting for all covariates and potential confounders. Moreover, sense of control scores either partially or fully mediated the statistically significant beneficial associations between childhood school segregation and physical performance. Conclusions Childhood school desegregation was adversely associated with the sense of control of African Americans in later life, and this reduced sense of control appears, in part, to account for their poorer physical performance. The etiologic mechanism through which childhood school segregation at the time that this cohort experienced it improved the sense of control in later life, which subsequently led to better physical performance, has not been identified. We suspect, however, that the pathway involves greater exposure to racial solidarity, same-race students as peer role models and same-race teachers and principals as authority role models, the reduced likelihood of exposure to race-based discrimination or antagonism during their formative early lives, and greater exposure to encouragement and support for academic and life success. PMID:23017218

Chemical and biological sensors based on defect-engineered graphene mesh field-effect transistors.

PubMed

Cho, Seunghee H; Kwon, Sun Sang; Yi, Jaeseok; Park, Won Il

2016-01-01

Graphene has been intensively studied for applications to high-performance sensors, but the sensing characteristics of graphene devices have varied from case to case, and the sensing mechanism has not been satisfactorily determined thus far. In this review, we describe recent progress in engineering of the defects in graphene grown by a silica-assisted chemical vapor deposition technique and elucidate the effect of the defects upon the electrical response of graphene sensors. This review provides guidelines for engineering and/or passivating defects to improve sensor performance and reliability.

Wavelet-Based Processing for Fiber Optic Sensing Systems

NASA Technical Reports Server (NTRS)

Hamory, Philip J. (Inventor); Parker, Allen R., Jr. (Inventor)

2016-01-01

The present invention is an improved method of processing conglomerate data. The method employs a Triband Wavelet Transform that decomposes and decimates the conglomerate signal to obtain a final result. The invention may be employed to improve performance of Optical Frequency Domain Reflectometry systems.

Hydrogen sensing properties of nanocomposite graphene oxide/Co-based metal organic frameworks (Co-MOFs@GO)

NASA Astrophysics Data System (ADS)

Fardindoost, Somayeh; Hatamie, Shadie; Iraji Zad, Azam; Razi Astaraei, Fatemeh

2018-01-01

This paper reports on hydrogen sensing based graphene oxide hybrid with Co-based metal organic frameworks (Co-MOFs@GO) prepared by the hydrothermal process. The texture and morphology of the hybrid were characterized by powder x-ray diffraction, scanning electron microscopy and Brunauer-Emmett-Teller analysis. Porous flower like structures assembled from Co-MOFs and GO flakes with sufficient specific surface area are obtained, which are ideal for gas molecules diffusion and interactions. Sensing performance of Co-MOFs@GO were tested and also improved by sputtering platinum (Pt) as a catalyst. The Pt-sputtered Co-MOFs@GO show outstanding hydrogen resistive-sensing with response and recovery times below 12 s at 15 °C. Also, they show stable, repeatable and selective responses to the target gas which make it suitable for the development of a high performance hydrogen sensor.

Enhancing intensity and refractive index sensing capability with infrared plasmonic perfect absorbers.

PubMed

Cheng, Fei; Yang, Xiaodong; Gao, Jie

2014-06-01

An infrared refractive index sensor based on plasmonic perfect absorbers for glucose concentration sensing is experimentally demonstrated. Utilizing substantial absorption contrast between a perfect absorber (∼98% at normal incidence) and a non-perfect absorber upon the refractive index change, a maximum value of figure of merit (FOM^*) about 55 and a bulk wavelength sensitivity about 590  nm/RIU are achieved. The demonstrated sensing platform provides great potential in improving the performance of plasmonic refractive index sensors and developing future surface enhanced infrared spectroscopy.

Re-defining one's occupational self 2 years after breast cancer: a case study.

PubMed

Newman, Robin M

2013-01-01

Margaret*, a 56 year-old Caucasian Stage III breast cancer survivor, participated in a 5 week occupational therapy pilot program, called Take Action. This program was designed for breast cancer survivors who self-reported changes in cognitive function following completion of chemotherapy. The goals of the program were to improve participants' knowledge and use of strategies to enhance occupational performance and to improve satisfaction and performance of meaningful daily activities or occupations. Through a client-centered and evidence-based approach, this case study highlights the importance of incorporating the survivors' sense of self into an occupation-based intervention. Occupational therapists play an important role in facilitating exploration of sense of self in the survivorship phase of care to support occupational performance in self care, productivity, work, leisure and social participation. This case study highlights the important work of redefining oneself in the survivorship phase of care. (*denotes name change).

Learning Unplugged: Using Mobile Technologies for Organizational Training and Performance Improvement.

ERIC Educational Resources Information Center

Gayeski, Diane

This book, which is written by a training consultant, is intended to help organizations determine whether specific readily available mobile technologies make sense for their particular learning and performance needs. Chapter 1 discusses the mobile revolution in learning and performance, with special attention to the new work and learning…

Short-term effects of kinesio tape on joint position sense, isokinetic measurements, and clinical parameters in patellofemoral pain syndrome

PubMed Central

Kurt, Emine Eda; Büyükturan, Öznur; Erdem, Hatice Rana; Tuncay, Figen; Sezgin, Hicabi

2016-01-01

[Purpose] To evaluate the short-term effects of kinesio tape on joint position sense, isokinetic measurements, kinesiophobia, symptoms, and functional limitations in patients with patellofemoral pain syndrome. [Subjects and Methods] A total of 90 patients (112 knees) with patellofemoral pain syndrome were randomized into a kinesio tape group (n=45) or placebo kinesio tape group (n=45). Baseline isokinetic quadriceps muscle tests and measurements of joint position sense were performed in both groups. Pain was measured with a Visual Analog Scale, kinesiophobia with the Tampa kinesiophobia scale, and symptoms and functional limitations with the Kujala pain scale. Measurements were repeated 2 days after kinesio tape application. [Results] No differences were found between baseline isokinetic muscle measurements and those taken 2 days after application. However, significant improvements were observed in the kinesio tape group, with regard to joint position sense, pain, kinesiophobia, symptoms, and functional limitations after treatment. Examination of the differences between pre- and post-treatment values in both groups revealed that the kinesio tape group demonstrated greater improvements compared to the placebo kinesio tape group. [Conclusion] Although short-term kinesio tape application did not increase hamstring muscle strength, it may have improved joint position sense, pain, kinesiophobia, symptoms, and daily limitations. PMID:27512259

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Quantitative assessment of joint position sense recovery in subacute stroke patients: a pilot study.

PubMed

Kattenstroth, Jan-Christoph; Kalisch, Tobias; Kowalewski, Rebecca; Tegenthoff, Martin; Dinse, Hubert R

2013-11-01

To assess joint position sense performance in subacute stroke patients using a novel quantitative assessment. Proof-of-principle pilot study with a group of subacute stroke patients. Assessment at baseline and after 2 weeks of intervention. Additional data for a healthy age-matched control group. Ten subacute stroke patients (aged 65.41 years (standard deviation 2.5), 4 females, 2.3 weeks (standard deviation 0.2)) post-stroke receiving in-patient standard rehabilitation and repetitive electrical stimulation of the affected hand. Joint position sense was assessed based on the ability of correctly perceiving the opening angles of the finger joints. Patients had to report size differences of polystyrene balls of various sizes, whilst the balls were enclosed simultaneously by the affected and the non-affected hands. A total of 21 pairwise size comparisons was used to quantify joint position performance. After 2 weeks of therapeutic intervention a significant improvement in joint position sense performance was observed; however, the performance level was still below that of a healthy control group. The results indicate high feasibility and sensitivity of the joint position test in subacute stroke patients. Testing allowed quantification of both the deficit and the rehabilitation outcome.

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

Going Green: Eco-Friendly Schools

ERIC Educational Resources Information Center

Whelan, Debra Lau

2007-01-01

A growing number of studies show that a school's physical condition--especially its lighting and indoor air quality--directly affect student performance. A 2005 Turner Construction survey of green buildings found that 70 percent of districts with sustainable schools reported improved student performance. It also makes perfect sense that…

The analysis of temperature effect and temperature compensation of MOEMS accelerometer based on a grating interferometric cavity

NASA Astrophysics Data System (ADS)

Han, Dandan; Bai, Jian; Lu, Qianbo; Lou, Shuqi; Jiao, Xufen; Yang, Guoguang

2016-08-01

There is a temperature drift of an accelerometer attributed to the temperature variation, which would adversely influence the output performance. In this paper, a quantitative analysis of the temperature effect and the temperature compensation of a MOEMS accelerometer, which is composed of a grating interferometric cavity and a micromachined sensing chip, are proposed. A finite-element-method (FEM) approach is applied in this work to simulate the deformation of the sensing chip of the MOEMS accelerometer at different temperature from -20°C to 70°C. The deformation results in the variation of the distance between the grating and the sensing chip of the MOEMS accelerometer, modulating the output intensities finally. A static temperature model is set up to describe the temperature characteristics of the accelerometer through the simulation results and the temperature compensation is put forward based on the temperature model, which can improve the output performance of the accelerometer. This model is permitted to estimate the temperature effect of this type accelerometer, which contains a micromachined sensing chip. Comparison of the output intensities with and without temperature compensation indicates that the temperature compensation can improve the stability of the output intensities of the MOEMS accelerometer based on a grating interferometric cavity.

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review

PubMed Central

Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-01-01

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on. PMID:29614024

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review.

PubMed

Ding, Zhenyang; Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-04-03

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Enhanced glucose biosensor properties of gold nanoparticle-decorated ZnO nanorods

NASA Astrophysics Data System (ADS)

Wang, Zi-Hao; Yang, Chih-Chiang; Su, Yan-Kuin; Ruand, Jian-Long

2017-04-01

As new materials have been reported and more knowledge on detailed mechanism of glucose oxidation has been unveiled, the non-enzymatic glucose sensor keeps coming closer to practical applications. Nanostructures with higher surface specific area has great potential applications in sensing devices ZnO nanoords were synthesized in a hydrothermal method using simply available laboratory chemicals. Results showed that as-synthesized Gold Nanoparticle-decorated ZnO Nanorods possessing higher specific surface area, significantly increased the non-enzyme efficiency which in turn improved the sensing performances. The electrode also demonstrated excellent performance in sensing glucose concentration with remarkable sensitivity (46.6 μA/mM-cm2) and good repeatability. This work is expected to open a new avenue to fabricate non-enzymatic electrochemical sensors of glucose involving co-mediating.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

NASA Astrophysics Data System (ADS)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

Surgical Reconstruction with the Remnant Ligament Improves Joint Position Sense as well as Functional Ankle Instability: A 1-Year Follow-Up Study

PubMed Central

Iwao, Kamizato; Masataka, Deie; Kohei, Fukuhara

2014-01-01

Introduction. Chronic functional instability—characterized by repeated ankle inversion sprains and a subjective sensation of instability—is one of the most common residual disabilities after an inversion sprain. However, whether surgical reconstruction improves sensorimotor control has not been reported to date. The purpose of this study was to assess functional improvement of chronic ankle instability after surgical reconstruction using the remnant ligament. Materials and Methods. We performed 10 cases in the intervention group and 20 healthy individuals as the control group. Before and after surgical reconstruction, we evaluated joint position sense and functional ankle instability by means of a questionnaire. Results and Discussion. There was a statistically significant difference between the control and intervention groups before surgical reconstruction. Three months after surgery in the intervention group, the joint position sense was significantly different from those found preoperatively. Before surgery, the mean score of functional ankle instability in the intervention group was almost twice as low. Three months after surgery, however, the score significantly increased. The results showed that surgical reconstruction using the remnant ligament was effective not only for improving mechanical retensioning but also for ameliorating joint position sense and functional ankle instability. PMID:25401146

A Powerful Molecular Engineering Tool Provided Efficient Chlamydomonas Mutants as Bio-Sensing Elements for Herbicides Detection

PubMed Central

Lambreva, Maya D.; Giardi, Maria Teresa; Rambaldi, Irene; Antonacci, Amina; Pastorelli, Sandro; Bertalan, Ivo; Husu, Ivan; Johanningmeier, Udo; Rea, Giuseppina

2013-01-01

This study was prompted by increasing concerns about ecological damage and human health threats derived by persistent contamination of water and soil with herbicides, and emerging of bio-sensing technology as powerful, fast and efficient tool for the identification of such hazards. This work is aimed at overcoming principal limitations negatively affecting the whole-cell-based biosensors performance due to inadequate stability and sensitivity of the bio-recognition element. The novel bio-sensing elements for the detection of herbicides were generated exploiting the power of molecular engineering in order to improve the performance of photosynthetic complexes. The new phenotypes were produced by an in vitro directed evolution strategy targeted at the photosystem II (PSII) D1 protein of Chlamydomonas reinhardtii, using exposures to radical-generating ionizing radiation as selection pressure. These tools proved successful to identify D1 mutations conferring enhanced stability, tolerance to free-radical-associated stress and competence for herbicide perception. Long-term stability tests of PSII performance revealed the mutants capability to deal with oxidative stress-related conditions. Furthermore, dose-response experiments indicated the strains having increased sensitivity or resistance to triazine and urea type herbicides with I50 values ranging from 6×10−8 M to 2×10−6 M. Besides stressing the relevance of several amino acids for PSII photochemistry and herbicide sensing, the possibility to improve the specificity of whole-cell-based biosensors, via coupling herbicide-sensitive with herbicide-resistant strains, was verified. PMID:23613953

Citrate-based fluorescent materials for low-cost chloride sensing in the diagnosis of Cystic Fibrosis.

PubMed

Kim, Jimin P; Xie, Zhiwei; Creer, Michael; Liu, Zhiwen; Yang, Jian

2017-01-01

Chloride is an essential electrolyte that maintains homeostasis within the body, where abnormal chloride levels in biological fluids may indicate various diseases such as Cystic Fibrosis. However, current analytical solutions for chloride detection fail to meet the clinical needs of both high performance and low material or labor costs, hindering translation into clinical settings. Here we present a new class of fluorescence chloride sensors derived from a facile citrate -based synthesis platform that utilize dynamic quenching mechanisms. Based on this low-cost platform, we demonstrate for the first time a selective sensing strategy that uses a single fluorophore to detect multiple halides simultaneously, promising both selectivity and automation to improve performance and reduce labor costs. We also demonstrate the clinical utility of citrate-based sensors as a new sweat chloride test method for the diagnosis of Cystic Fibrosis by performing analytical validation with sweat controls and clinical validation with sweat from individuals with or without Cystic Fibrosis. Lastly, molecular modeling studies reveal the structural mechanism behind chloride sensing, serving to expand this class of fluorescence sensors with improved chloride sensitivities. Thus citrate-based fluorescent materials may enable low-cost, automated multi-analysis systems for simpler, yet accurate, point-of-care diagnostics that can be readily translated into clinical settings. More broadly, a wide range of medical, industrial, and environmental applications can be achieved with such a facile synthesis platform, demonstrated in our citrate-based biodegradable polymers with intrinsic fluorescence sensing.

Optical Passive Sensor Calibration for Satellite Remote Sensing and the Legacy of NOAA and NIST Cooperation

PubMed Central

Datla, Raju; Weinreb, Michael; Rice, Joseph; Johnson, B. Carol; Shirley, Eric; Cao, Changyong

2014-01-01

This paper traces the cooperative efforts of scientists at the National Oceanic and Atmospheric Administration (NOAA) and the National Institute of Standards and Technology (NIST) to improve the calibration of operational satellite sensors for remote sensing of the Earth’s land, atmosphere and oceans. It gives a chronological perspective of the NOAA satellite program and the interactions between the two agencies’ scientists to address pre-launch calibration and issues of sensor performance on orbit. The drive to improve accuracy of measurements has had a new impetus in recent years because of the need for improved weather prediction and climate monitoring. The highlights of this cooperation and strategies to achieve SI-traceability and improve accuracy for optical satellite sensor data are summarized1. PMID:26601030

Optical Passive Sensor Calibration for Satellite Remote Sensing and the Legacy of NOAA and NIST Cooperation.

PubMed

Datla, Raju; Weinreb, Michael; Rice, Joseph; Johnson, B Carol; Shirley, Eric; Cao, Changyong

2014-01-01

This paper traces the cooperative efforts of scientists at the National Oceanic and Atmospheric Administration (NOAA) and the National Institute of Standards and Technology (NIST) to improve the calibration of operational satellite sensors for remote sensing of the Earth's land, atmosphere and oceans. It gives a chronological perspective of the NOAA satellite program and the interactions between the two agencies' scientists to address pre-launch calibration and issues of sensor performance on orbit. The drive to improve accuracy of measurements has had a new impetus in recent years because of the need for improved weather prediction and climate monitoring. The highlights of this cooperation and strategies to achieve SI-traceability and improve accuracy for optical satellite sensor data are summarized.

Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

PubMed Central

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks. PMID:22163582

Sensing performances of pure and hybridized carbon nanotubes-ZnO nanowire networks: A detailed study.

PubMed

Lupan, Oleg; Schütt, Fabian; Postica, Vasile; Smazna, Daria; Mishra, Yogendra Kumar; Adelung, Rainer

2017-11-07

In this work, the influence of carbon nanotube (CNT) hybridization on ultraviolet (UV) and gas sensing properties of individual and networked ZnO nanowires (NWs) is investigated in detail. The CNT concentration was varied to achieve optimal conditions for the hybrid with improved sensing properties. In case of CNT decorated ZnO nanonetworks, the influence of relative humidity (RH) and applied bias voltage on the UV sensing properties was thoroughly studied. By rising the CNT content to about 2.0 wt% (with respect to the entire ZnO network) the UV sensing response is considerably increased from 150 to 7300 (about 50 times). With respect to gas sensing, the ZnO-CNT networks demonstrate an excellent selectivity as well as a high gas response to NH 3 vapor. A response of 430 to 50 ppm at room temperature was obtained, with an estimated detection limit of about 0.4 ppm. Based on those results, several devices consisting of individual ZnO NWs covered with CNTs were fabricated using a FIB/SEM system. The highest sensing performance was obtained for the finest NW with diameter (D) of 100 nm,  with a response of about 4 to 10 ppm NH 3 vapor at room temperature.

A study on gaseous extinguishing agent sensing with a simple measurement method

NASA Astrophysics Data System (ADS)

Guan, Yu; Lu, Song; Yuan, Wei; Qian, Hanjie

2018-03-01

As research on the concentration distribution for evaluating the effectiveness of a gas fire extinguisher system is quite important, the proper sensing technology is necessary. Here, a simple method used for measuring the concentration of agent is introduced, and the manufacture of the sensing part is described clearly. The sensing unit is composed of a pressure reducing structure and pressure sensor element. The detection was achieved by sensing the change of pressure difference caused by gas flow. In order to verify the theory and characterize the sensing performance, two types of fire extinguishing agents, bromotrifluoromethane (CBrF3) and heptafluoropropane (C3HF7), were used in the experiments. The results showed a high sensitivity from 0 to 100%, good repeatability and fast response/recovery time. Furthermore, the effect of operating temperature, humidity and geometric structure on the response were investigated. Measurements showed, for CBrF3, that the temperature had a linear impact on the response and the influence of humidity in the sensor was negligible. Through the analysis of the geometry parameter, it was found that the sensing performance could be greatly improved through adjusting the geometry structure. This technique provides a low-cost and highly reliable sensor for the detection of gaseous extinguishing agent that can be easily fabricated.

The effects of end-of-day picture review and a sensor-based picture capture procedure on autobiographical memory using SenseCam.

PubMed

Finley, Jason R; Brewer, William F; Benjamin, Aaron S

2011-10-01

Emerging "life-logging" technologies have tremendous potential to augment human autobiographical memory by recording and processing vast amounts of information from an individual's experiences. In this experiment undergraduate participants wore a SenseCam, a small, sensor-equipped digital camera, as they went about their normal daily activities for five consecutive days. Pictures were captured either at fixed intervals or as triggered by SenseCam's sensors. On two of five nights, participants watched an end-of-day review of a random subset of pictures captured that day. Participants were tested with a variety of memory measures at intervals of 1, 3, and 8 weeks. The most fruitful of six measures were recognition rating (on a 1-7 scale) and picture-cued recall length. On these tests, end-of-day review enhanced performance relative to no review, while pictures triggered by SenseCam's sensors showed little difference in performance compared to those taken at fixed time intervals. We discuss the promise of SenseCam as a tool for research and for improving autobiographical memory.

A Latin-cross-shaped integrated resonant cantilever with second torsion-mode resonance for ultra-resoluble bio-mass sensing

NASA Astrophysics Data System (ADS)

Xia, Xiaoyuan; Zhang, Zhixiang; Li, Xinxin

2008-03-01

Second torsion-mode resonance is proposed for microcantilever biosensors for ultra-high mass-weighing sensitivity and resolution. By increasing both the resonant frequency and Q-factor, the higher mode torsional resonance is favorable for improving the mass-sensing performance. For the first time, a Latin-cross-shaped second-mode resonant cantilever is constructed and optimally designed for both signal-readout and resonance-exciting elements. The cantilever sensor is fabricated by using silicon micromachining techniques. The transverse piezoresistive sensing element and the specific-shaped resonance-exciting loop are successfully integrated in the cantilever. Alpha-fetoprotein (AFP) antibody-antigen specific binding is implemented for the sensing experiment. The proposed cantilever sensor is designed with significantly superior sensitivity to the previously reported first torsion-mode one. After analysis with an Allan variance algorithm, which can be easily embedded in the sensing system, the Latin-cross-shaped second torsion-mode resonant cantilever is evaluated with ultra-high mass resolution. Therefore, the high-performance integrated micro-sensor is promising for on-the-spot bio-molecule detection.

Passive Polarimetric Information Processing for Target Classification

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz; Sadjadi, Farzad

Polarimetric sensing is an area of active research in a variety of applications. In particular, the use of polarization diversity has been shown to improve performance in automatic target detection and recognition. Within the diverse scope of polarimetric sensing, the field of passive polarimetric sensing is of particular interest. This chapter presents several new methods for gathering in formation using such passive techniques. One method extracts three-dimensional (3D) information and surface properties using one or more sensors. Another method extracts scene-specific algebraic expressions that remain unchanged under polariza tion transformations (such as along the transmission path to the sensor).

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

NASA Astrophysics Data System (ADS)

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, P.; Williams, C.; Ardö, J.; Boucher, M.; Cappelaere, B.; de Grandcourt, A.; Nickless, A.; Nouvellon, Y.; Scholes, R.; Kutsch, W.

2013-03-01

Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

Flexible hemispheric microarrays of highly pressure-sensitive sensors based on breath figure method.

PubMed

Wang, Zhihui; Zhang, Ling; Liu, Jin; Jiang, Hao; Li, Chunzhong

2018-05-30

Recently, flexible pressure sensors featuring high sensitivity, broad sensing range and real-time detection have aroused great attention owing to their crucial role in the development of artificial intelligent devices and healthcare systems. Herein, highly sensitive pressure sensors based on hemisphere-microarray flexible substrates are fabricated via inversely templating honeycomb structures deriving from a facile and static breath figure process. The interlocked and subtle microstructures greatly improve the sensing characteristics and compressibility of the as-prepared pressure sensor, endowing it a sensitivity as high as 196 kPa-1 and a wide pressure sensing range (0-100 kPa), as well as other superior performance, including a lower detection limit of 0.5 Pa, fast response time (<26 ms) and high reversibility (>10 000 cycles). Based on the outstanding sensing performance, the potential capability of our pressure sensor in capturing physiological information and recognizing speech signals has been demonstrated, indicating promising application in wearable and intelligent electronics.

Dipole-modified graphene with ultrahigh gas sensibility

NASA Astrophysics Data System (ADS)

Jia, Ruokun; Xie, Peng; Feng, Yancong; Chen, Zhuo; Umar, Ahmad; Wang, Yao

2018-05-01

This study reports the supramolecular assembly of functional graphene-based materials with ultrahigh gas sensing performances which are induced by charge transfer enhancement. Two typical Donor-π-Accepter (D-π-A) structure molecules 4-aminoquinoline (4AQ, μ = 3.17 Debye) and 4-hydroxyquinoline (4HQ, μ = 1.98 Debye), with different charge transfer enhancing effects, were selected to modify reduce oxide graphene (rGO) via supramolecular assembly. Notably, compared to the 4HQ-rGO, the 4AQ-rGO exhibits more significant increase of gas response (Ra/Rg = 3.79) toward 10 ppm NO2, which is ascribed to the larger dipole moment (μ) of 4AQ and hence the more intensive enhancing effect of charge transfer on the interface of rGO. Meanwhile, 4AQ-rGO sensors also reveal superior comprehensive gas sensing performances, including excellent gas sensing selectivity, linearity, repeatability and stability. It is believed that the present work demonstrates an effective supramolecular approach of modifying rGO with strong dipoles to significantly improve gas sensing properties of graphene-based materials.

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

Biocompatible Pressure Sensing Skins for Minimally Invasive Surgical Instruments

PubMed Central

Arabagi, Veaceslav; Felfoul, Ouajdi; Gosline, Andrew H.; Wood, Robert J.; Dupont, Pierre E.

2016-01-01

This paper presents 800-μm thick, biocompatible sensing skins composed of arrays of pressure sensors. The arrays can be configured to conform to the surface of medical instruments so as to act as disposable sensing skins. In particular, the fabrication of cylindrical geometries is considered here for use on endoscopes. The sensing technology is based on polydimethylsiloxane synthetic silicone encapsulated microchannels filled with a biocompatible salt-saturated glycerol solution, functioning as the conductive medium. A multi-layer manufacturing approach is introduced that enables stacking sensing microchannels, mechanical stress concentration features, and electrical routing via flexcircuits in a thickness of less than 1 mm. The proposed approach is inexpensive and does not require clean room tools or techniques. The mechanical stress concentration features are implemented using a patterned copper layer that serves to improve sensing range and sensitivity. Sensor performance is demonstrated experimentally using a sensing skin mounted on a neuroendoscope insertion cannula and is shown to outperform previously developed non-biocompatible sensors. PMID:27642266

Ultrathin Tungsten Oxide Nanowires/Reduced Graphene Oxide Composites for Toluene Sensing

PubMed Central

Hassan, Muhammad; Wang, Zhi-Hua; Huang, Wei-Ran; Li, Min-Qiang; Chen, Jia-Fu

2017-01-01

Graphene-based composites have gained great attention in the field of gas sensor fabrication due to their higher surface area with additional functional groups. Decorating one-dimensional (1D) semiconductor nanomaterials on graphene also show potential benefits in gas sensing applications. Here we demonstrate the one-pot and low cost synthesis of W18O49 NWs/rGO composites with different amount of reduced graphene oxide (rGO) which show excellent gas-sensing properties towards toluene and strong dependence on their chemical composition. As compared to pure W18O49 NWs, an improved gas sensing response (2.8 times higher) was achieved in case of W18O49 NWs composite with 0.5 wt. % rGO. Promisingly, this strategy can be extended to prepare other nanowire based composites with excellent gas-sensing performance. PMID:28961178

Various on-chip sensors with microfluidics for biological applications.

PubMed

Lee, Hun; Xu, Linfeng; Koh, Domin; Nyayapathi, Nikhila; Oh, Kwang W

2014-09-12

In this paper, we review recent advances in on-chip sensors integrated with microfluidics for biological applications. Since the 1990s, much research has concentrated on developing a sensing system using optical phenomena such as surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS) to improve the sensitivity of the device. The sensing performance can be significantly enhanced with the use of microfluidic chips to provide effective liquid manipulation and greater flexibility. We describe an optical image sensor with a simpler platform for better performance over a larger field of view (FOV) and greater depth of field (DOF). As a new trend, we review consumer electronics such as smart phones, tablets, Google glasses, etc. which are being incorporated in point-of-care (POC) testing systems. In addition, we discuss in detail the current optical sensing system integrated with a microfluidic chip.

Achieving Efficient Spectrum Usage in Passive and Active Sensing

NASA Astrophysics Data System (ADS)

Wang, Huaiyi

Increasing demand for supporting more wireless services with higher performance and reliability within the frequency bands that are most conducive to operating cost-effective cellular and mobile broadband is aggravating current electromagnetic spectrum congestion. This situation motivates technology and management innovation to increase the efficiency of spectral use. If primary-secondary spectrum sharing can be shown possible without compromising (or while even improving) performance in an existing application, opportunities for efficiency may be realizable by making the freed spectrum available for commercial use. While both active and passive sensing systems are vitally important for many public good applications, opportunities for increasing the efficiency of spectrum use can be shown to exist for both systems. This dissertation explores methods and technologies for remote sensing systems that enhance spectral efficiency and enable dynamic spectrum access both within and outside traditionally allocated bands.

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

PubMed

Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability.

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes

PubMed Central

Yates, Katherine L.; Mellin, Camille; Caley, M. Julian; Radford, Ben T.; Meeuwig, Jessica J.

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability. PMID:27333202

Robot-Assisted Proprioceptive Training with Added Vibro-Tactile Feedback Enhances Somatosensory and Motor Performance.

PubMed

Cuppone, Anna Vera; Squeri, Valentina; Semprini, Marianna; Masia, Lorenzo; Konczak, Jürgen

2016-01-01

This study examined the trainability of the proprioceptive sense and explored the relationship between proprioception and motor learning. With vision blocked, human learners had to perform goal-directed wrist movements relying solely on proprioceptive/haptic cues to reach several haptically specified targets. One group received additional somatosensory movement error feedback in form of vibro-tactile cues applied to the skin of the forearm. We used a haptic robotic device for the wrist and implemented a 3-day training regimen that required learners to make spatially precise goal-directed wrist reaching movements without vision. We assessed whether training improved the acuity of the wrist joint position sense. In addition, we checked if sensory learning generalized to the motor domain and improved spatial precision of wrist tracking movements that were not trained. The main findings of the study are: First, proprioceptive acuity of the wrist joint position sense improved after training for the group that received the combined proprioceptive/haptic and vibro-tactile feedback (VTF). Second, training had no impact on the spatial accuracy of the untrained tracking task. However, learners who had received VTF significantly reduced their reliance on haptic guidance feedback when performing the untrained motor task. That is, concurrent VTF was highly salient movement feedback and obviated the need for haptic feedback. Third, VTF can be also provided by the limb not involved in the task. Learners who received VTF to the contralateral limb equally benefitted. In conclusion, somatosensory training can significantly enhance proprioceptive acuity within days when learning is coupled with vibro-tactile sensory cues that provide feedback about movement errors. The observable sensory improvements in proprioception facilitates motor learning and such learning may generalize to the sensorimotor control of the untrained motor tasks. The implications of these findings for neurorehabilitation are discussed.

The Sense of Agency during Continuous Action: Performance Is More Important than Action-Feedback Association

PubMed Central

Wen, Wen; Yamashita, Atsushi; Asama, Hajime

2015-01-01

The sense of agency refers to the feeling that one is controlling events through one’s own behavior. This study examined how task performance and the delay of events influence one’s sense of agency during continuous action accompanied by a goal. The participants were instructed to direct a moving dot into a square as quickly as possible by pressing the left and right keys on a keyboard to control the direction in which the dot traveled. The interval between the key press and response of the dot (i.e., direction change) was manipulated to vary task difficulty. Moreover, in the assisted condition, the computer ignored participants’ erroneous commands, resulting in improved task performance but a weaker association between the participants’ commands and actual movements of the dot relative to the condition in which all of the participants’ commands were executed (i.e., self-control condition). The results showed that participants’ sense of agency increased with better performance in the assisted condition relative to the self-control condition, even though a large proportion of their commands were not executed. We concluded that, when the action-feedback association was uncertain, cognitive inference was more dominant relative to the process of comparing predicted and perceived information in the judgment of agency. PMID:25893992

Effects of Warm-Up and Fatigue on Knee Joint Position Sense and Jump Performance.

PubMed

Romero-Franco, N; Jiménez-Reyes, P

2017-01-01

The purpose of this study was to evaluate the effects of a warm-up and fatigue protocol on the vertical jump and knee joint position sense of sprinters. Thirty-two sprinters were randomly allocated to either a control group (CONT) or a plyometric group (PLYO) that performed a warm-up, followed by a high-intensity plyometric protocol. Absolute (AAE), relative (RAE), and variable (VAE) angular errors and vertical jump were evaluated before and after the warm-up, as well as after the plyometric protocol and again 5 min later. After the warm-up, athletes improved RAE and jump performance. After the plyometric protocol, scores on the RAE, VAE, and the vertical jump performance worsened compared to the control group and to the values obtained after the warm-up. Five minutes later, RAE and vertical jump continued to be impaired. AAE did not show significant differences. The vertical jump is improved after the warm-up, although it is deteriorated after high-intensity plyometry. Regarding knee proprioception, the lack of impairments in the AAE make unclear the effects of the plyometric exercises on knee proprioception.

Multi-scale functional mapping of tidal marsh vegetation for restoration monitoring

NASA Astrophysics Data System (ADS)

Tuxen Bettman, Karin

2007-12-01

Nearly half of the world's natural wetlands have been destroyed or degraded, and in recent years, there have been significant endeavors to restore wetland habitat throughout the world. Detailed mapping of restoring wetlands can offer valuable information about changes in vegetation and geomorphology, which can inform the restoration process and ultimately help to improve chances of restoration success. I studied six tidal marshes in the San Francisco Estuary, CA, US, between 2003 and 2004 in order to develop techniques for mapping tidal marshes at multiple scales by incorporating specific restoration objectives for improved longer term monitoring. I explored a "pixel-based" remote sensing image analysis method for mapping vegetation in restored and natural tidal marshes, describing the benefits and limitations of this type of approach (Chapter 2). I also performed a multi-scale analysis of vegetation pattern metrics for a recently restored tidal marsh in order to target the metrics that are consistent across scales and will be robust measures of marsh vegetation change (Chapter 3). Finally, I performed an "object-based" image analysis using the same remotely sensed imagery, which maps vegetation type and specific wetland functions at multiple scales (Chapter 4). The combined results of my work highlight important trends and management implications for monitoring wetland restoration using remote sensing, and will better enable restoration ecologists to use remote sensing for tidal marsh monitoring. Several findings important for tidal marsh restoration monitoring were made. Overall results showed that pixel-based methods are effective at quantifying landscape changes in composition and diversity in recently restored marshes, but are limited in their use for quantifying smaller, more fine-scale changes. While pattern metrics can highlight small but important changes in vegetation composition and configuration across years, scientists should exercise caution when using metrics in their studies or to validate restoration management decisions, and multi-scale analyses should be performed before metrics are used in restoration science for important management decisions. Lastly, restoration objectives, ecosystem function, and scale can each be integrated into monitoring techniques using remote sensing for improved restoration monitoring.

Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach

PubMed Central

Li, Zhao-Liang

2018-01-01

Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty. PMID:29373548

Pt-decorated GaN nanowires with significant improvement in H2 gas-sensing performance at room temperature.

PubMed

Abdullah, Q N; Yam, F K; Hassan, Z; Bououdina, M

2015-12-15

Superior sensitivity towards H2 gas was successfully achieved with Pt-decorated GaN nanowires (NWs) gas sensor. GaN NWs were fabricated via chemical vapor deposition (CVD) route. Morphology (field emission scanning electron microscopy and transmission electron microscopy) and crystal structure (high resolution X-ray diffraction) characterizations of the as-synthesized nanostructures demonstrated the formation of GaN NWs having a wurtzite structure, zigzaged shape and an average diameter of 30-166nm. The Pt-decorated GaN NWs sensor shows a high response of 250-2650% upon exposure to H2 gas concentration from 7 to 1000ppm respectively at room temperature (RT), and then increases to about 650-4100% when increasing the operating temperature up to 75°C. The gas-sensing measurements indicated that the Pt-decorated GaN NWs based sensor exhibited efficient detection of H2 at low concentration with excellent sensitivity, repeatability, and free hysteresis phenomena over a period of time of 100min. The large surface-to-volume ratio of GaN NWs and the catalytic activity of Pt metal are the most influential factors leading to the enhancement of H2 gas-sensing performances through the improvement of the interaction between the target molecules (H2) and the sensing NWs surface. The attractive low-cost, low power consumption and high-performance of the resultant decorated GaN NWs gas sensor assure their uppermost potential for H2 gas sensor working at low operating temperature. Copyright © 2015 Elsevier Inc. All rights reserved.

Platinum decorated carbon nanotubes for highly sensitive amperometric glucose sensing

NASA Astrophysics Data System (ADS)

Xie, Jining; Wang, Shouyan; Aryasomayajula, L.; Varadan, V. K.

2007-02-01

Fine platinum nanoparticles (1-5 nm in diameter) were deposited on functionalized multi-walled carbon nanotubes (MWNTs) through a decoration technique. A novel type of enzymatic Pt/MWNTs paste-based mediated glucose sensor was fabricated. Electrochemical measurements revealed a significantly improved sensitivity (around 52.7 µA mM-1 cm-2) for glucose sensing without using any picoampere booster or Faraday cage. In addition, the calibration curve exhibited a good linearity in the range of 1-28 mM of glucose concentration. Transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy (XPS) were performed to investigate the nanoscale structure and the chemical bonding information of the Pt/MWNTs paste-based sensing material, respectively. The improved sensitivity of this novel glucose sensor could be ascribed to its higher electroactive surface area, enhanced electron transfer, efficient enzyme immobilization, unique interaction in nanoscale and a synergistic effect on the current signal from possible multi-redox reactions.

Silica Nanowires: Growth, Integration, and Sensing Applications

PubMed Central

Kaushik, Ajeet; Kumar, Rajesh; Huey, Eric; Bhansali, Shekhar; Nair, Narayana; Nanir, Madhavan

2014-01-01

This review (with 129 refs.) gives an overview on how the integration of silica nanowires (NWs) into micro-scale devices has resulted, in recent years, in simple yet robust nano-instrumentation with improved performance in targeted application areas such as sensing. This has been achieved by the use of appropriate techniques such as di-electrophoresis and direct vapor-liquid-growth phenomena, to restrict the growth of NWs to site-specific locations. This also has eliminated the need for post-growth processing and enables nanostructures to be placed on pre-patterned substrates. Various kinds of NWs have been investigated to determine how their physical and chemical properties can be tuned for integration into sensing structures. NWs integrated onto interdigitated micro-electrodes have been applied to the determination of gases and biomarkers. The technique of directly growing NWs eliminates the need for their physical transfer and thus preserves their structure and performance, and further reduces the costs of fabrication. The biocompatibility of NWs also has been studied with respect to possible biological applications. This review addresses the challenges in growth and integration of NWs to understand related mechanism on biological contact or gas exposure and sensing performance for personalized health and environmental monitoring. PMID:25382871

Au functionalized ZnO rose-like hierarchical structures and their enhanced NO2 sensing performance

NASA Astrophysics Data System (ADS)

Shingange, K.; Swart, H. C.; Mhlongo, G. H.

2018-04-01

Herein, we present ZnO rose-like hierarchical nanostructures employed as support to Au nanoparticles to produce Au functionalized three dimensional (3D) ZnO hierarchical nanostructures (Au/ZnO) for NO2 detection using a microwave-assisted method. Comparative analysis of NO2 sensing performance between the pristine ZnO and Au/ZnO rose-like structures at 300 °C revealed improved NO2 response and rapid response-recovery times with Au incorporation owing to a combination of high surface accessibility induced by hierarchical nanostructure design and catalytic activity of the small Au nanoparticles. Structural and optical analyses acquired from X-ray diffraction, scanning electron microscopy, transmission electron microscope and photoluminescence spectroscopy were also performed.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications.

PubMed

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-03-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications †

PubMed Central

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-01-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. PMID:28257067

Multifuctional integrated sensors (MFISES).

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

Homeijer, Brian D.; Roozeboom, Clifton

2015-10-01

Many emerging IoT applications require sensing of multiple physical and environmental parameters for: completeness of information, measurement validation, unexpected demands, improved performance. For example, a typical outdoor weather station measures temperature, humidity, barometric pressure, light intensity, rainfall, wind speed and direction. Existing sensor technologies do not directly address the demand for cost, size, and power reduction in multi-paramater sensing applications. Industry sensor manufacturers have developed integrated sensor systems for inertial measurements that combine accelerometers, gyroscopes, and magnetometers, but do not address environmental sensing functionality. In existing research literature, a technology gap exists between the functionality of MEMS sensors and themore » real world applications of the sensors systems.« less

Photonics: Technology project summary

NASA Technical Reports Server (NTRS)

Depaula, Ramon P.

1991-01-01

Photonics involves the use of light (photons) in conjunction with electronics for applications in communications, computing, control, and sensing. Components used in photonic systems include lasers, optical detectors, optical wave guide devices, fiber optics, and traditional electronic devices. The goal of this program is to develop hybrid optoelectronic devices and systems for sensing, information processing, communications, and control. It is hoped that these new devices will yield at least an order of magnitude improvement in performance over existing technology. The objective of the program is to conduct research and development in the following areas: (1) materials and devices; (2) networking and computing; (3) optical processing/advanced pattern recognition; and (4) sensing.

Multiscale deep features learning for land-use scene recognition

NASA Astrophysics Data System (ADS)

Yuan, Baohua; Li, Shijin; Li, Ning

2018-01-01

The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.

The Effects of End-of-Day Picture Review and a Sensor-based Picture Capture Procedure on Autobiographical Memory using SenseCam

PubMed Central

Finley, Jason R.; Brewer, William F.; Benjamin, Aaron S.

2011-01-01

Emerging “life-logging” technologies have tremendous potential to augment human autobiographical memory by recording and processing vast amounts of information from an individual’s experiences. In this experiment undergraduate participants wore a SenseCam, a small, sensor-equipped digital camera, as they went about their normal daily activities for five consecutive days. Pictures were captured either at fixed intervals or as triggered by SenseCam’s sensors. On two of five nights, participants watched an end-of-day review of a random subset of pictures captured that day. Participants were tested with a variety of memory measures at intervals of 1, 3, and 8 weeks. The most fruitful of six measures were recognition rating (on a 1–7 scale) and picture-cued recall length. On these tests, end-of-day review enhanced performance relative to no review, while pictures triggered by SenseCam’s sensors showed little difference in performance compared to those taken at fixed time intervals. We discuss the promise of SenseCam as a tool for research and for improving autobiographical memory. PMID:21229457

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.

Identification of two-phase flow regime based on electrical capacitance tomography and soft-sensing technique

NASA Astrophysics Data System (ADS)

Zhao, Ming-fu; Hu, Xin-Yu; Shao, Yun; Luo, Bin-bin; Wang, Xin

2008-10-01

This article analyses nowadays in common use of football robots in China, intended to improve the football robots' hardware platform system's capability, and designed a football robot which based on DSP core controller, and combined Fuzzy-PID control algorithm. The experiment showed, because of the advantages of DSP, such as quickly operation, various of interfaces, low power dissipation etc. It has great improvement on the football robot's performance of movement, controlling precision, real-time performance.

Ultrasensitive sensing with three-dimensional terahertz metamaterial absorber

NASA Astrophysics Data System (ADS)

Tan, Siyu; Yan, Fengping; Wang, Wei; Zhou, Hong; Hou, Yafei

2018-05-01

Planar metasurfaces and metamaterial absorbers have shown great promise for label-free sensing applications at microwaves, optical and terahertz frequencies. The realization of high-quality-factor resonance in these structures is of significant interest to enhance the sensing sensitivities to detect minute frequency shifts. We propose and demonstrate in this manuscript an ultrasensitive terahertz metamaterial absorber sensor based on a three-dimensional split ring resonator absorber with a high quality factor of 60.09. The sensing performance of the proposed absorber sensor was systematically investigated through detailed numerical calculations and a maximum refractive index sensitivity of 34.40% RIU‑1 was obtained. Furthermore, the absorber sensor can maintain a high sensitivity for a wide range of incidence angles up to 60° under TM polarization incidence. These findings would improve the design flexibility of the absorber sensors and further open up new avenues to achieve ultrasensitive sensing in the terahertz regime.

Sensing Performance Analysis on Quartz Tuning Fork-Probe at the High Order Vibration Mode for Multi-Frequency Scanning Probe Microscopy

PubMed Central

Gao, Fengli; Li, Xide

2018-01-01

Multi-frequency scanning near-field optical microscopy, based on a quartz tuning fork-probe (QTF-p) sensor using the first two orders of in-plane bending symmetrical vibration modes, has recently been developed. This method can simultaneously achieve positional feedback (based on the 1st in-plane mode called the low mode) and detect near-field optically induced forces (based on the 2nd in-plane mode called the high mode). Particularly, the high mode sensing performance of the QTF-p is an important issue for characterizing the tip-sample interactions and achieving higher resolution microscopic imaging but the related researches are insufficient. Here, we investigate the vibration performance of QTF-p at high mode based on the experiment and finite element method. The frequency spectrum characteristics are obtained by our homemade laser Doppler vibrometer system. The effects of the properties of the connecting glue layer and the probe features on the dynamic response of the QTF-p sensor at the high mode are investigated for optimization design. Finally, compared with the low mode, an obvious improvement of quality factor, of almost 50%, is obtained at the high mode. Meanwhile, the QTF-p sensor has a high force sensing sensitivity and a large sensing range at the high mode, indicating a broad application prospect for force sensing. PMID:29364847

Improved Object Detection Using a Robotic Sensing Antenna with Vibration Damping Control

PubMed Central

Feliu-Batlle, Vicente; Feliu-Talegon, Daniel; Castillo-Berrio, Claudia Fernanda

2017-01-01

Some insects or mammals use antennae or whiskers to detect by the sense of touch obstacles or recognize objects in environments in which other senses like vision cannot work. Artificial flexible antennae can be used in robotics to mimic this sense of touch in these recognition tasks. We have designed and built a two-degree of freedom (2DOF) flexible antenna sensor device to perform robot navigation tasks. This device is composed of a flexible beam, two servomotors that drive the beam and a load cell sensor that detects the contact of the beam with an object. It is found that the efficiency of such a device strongly depends on the speed and accuracy achieved by the antenna positioning system. These issues are severely impaired by the vibrations that appear in the antenna during its movement. However, these antennae are usually moved without taking care of these undesired vibrations. This article proposes a new closed-loop control schema that cancels vibrations and improves the free movements of the antenna. Moreover, algorithms to estimate the 3D beam position and the instant and point of contact with an object are proposed. Experiments are reported that illustrate the efficiency of these proposed algorithms and the improvements achieved in object detection tasks using a control system that cancels beam vibrations. PMID:28406449

Improved Object Detection Using a Robotic Sensing Antenna with Vibration Damping Control.

PubMed

Feliu-Batlle, Vicente; Feliu-Talegon, Daniel; Castillo-Berrio, Claudia Fernanda

2017-04-13

Some insects or mammals use antennae or whiskers to detect by the sense of touch obstacles or recognize objects in environments in which other senses like vision cannot work. Artificial flexible antennae can be used in robotics to mimic this sense of touch in these recognition tasks. We have designed and built a two-degree of freedom (2DOF) flexible antenna sensor device to perform robot navigation tasks. This device is composed of a flexible beam, two servomotors that drive the beam and a load cell sensor that detects the contact of the beam with an object. It is found that the efficiency of such a device strongly depends on the speed and accuracy achieved by the antenna positioning system. These issues are severely impaired by the vibrations that appear in the antenna during its movement. However, these antennae are usually moved without taking care of these undesired vibrations. This article proposes a new closed-loop control schema that cancels vibrations and improves the free movements of the antenna. Moreover, algorithms to estimate the 3D beam position and the instant and point of contact with an object are proposed. Experiments are reported that illustrate the efficiency of these proposed algorithms and the improvements achieved in object detection tasks using a control system that cancels beam vibrations.

Did I Do That? Expectancy Effects of Brain Stimulation on Error-related Negativity and Sense of Agency.

PubMed

Hoogeveen, Suzanne; Schjoedt, Uffe; van Elk, Michiel

2018-06-19

This study examines the effects of expected transcranial stimulation on the error(-related) negativity (Ne or ERN) and the sense of agency in participants who perform a cognitive control task. Placebo transcranial direct current stimulation was used to elicit expectations of transcranially induced cognitive improvement or impairment. The improvement/impairment manipulation affected both the Ne/ERN and the sense of agency (i.e., whether participants attributed errors to oneself or the brain stimulation device): Expected improvement increased the ERN in response to errors compared with both impairment and control conditions. Expected impairment made participants falsely attribute errors to the transcranial stimulation. This decrease in sense of agency was correlated with a reduced ERN amplitude. These results show that expectations about transcranial stimulation impact users' neural response to self-generated errors and the attribution of responsibility-especially when actions lead to negative outcomes. We discuss our findings in relation to predictive processing theory according to which the effect of prior expectations on the ERN reflects the brain's attempt to generate predictive models of incoming information. By demonstrating that induced expectations about transcranial stimulation can have effects at a neural level, that is, beyond mere demand characteristics, our findings highlight the potential for placebo brain stimulation as a promising tool for research.

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.

Various On-Chip Sensors with Microfluidics for Biological Applications

PubMed Central

Lee, Hun; Xu, Linfeng; Koh, Domin; Nyayapathi, Nikhila; Oh, Kwang W.

2014-01-01

In this paper, we review recent advances in on-chip sensors integrated with microfluidics for biological applications. Since the 1990s, much research has concentrated on developing a sensing system using optical phenomena such as surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS) to improve the sensitivity of the device. The sensing performance can be significantly enhanced with the use of microfluidic chips to provide effective liquid manipulation and greater flexibility. We describe an optical image sensor with a simpler platform for better performance over a larger field of view (FOV) and greater depth of field (DOF). As a new trend, we review consumer electronics such as smart phones, tablets, Google glasses, etc. which are being incorporated in point-of-care (POC) testing systems. In addition, we discuss in detail the current optical sensing system integrated with a microfluidic chip. PMID:25222033

Ranging Consistency Based on Ranging-Compensated Temperature-Sensing Sensor for Inter-Satellite Link of Navigation Constellation

PubMed Central

Meng, Zhijun; Yang, Jun; Guo, Xiye; Zhou, Yongbin

2017-01-01

Global Navigation Satellite System performance can be significantly enhanced by introducing inter-satellite links (ISLs) in navigation constellation. The improvement in position, velocity, and time accuracy as well as the realization of autonomous functions requires ISL distance measurement data as the original input. To build a high-performance ISL, the ranging consistency among navigation satellites is an urgent problem to be solved. In this study, we focus on the variation in the ranging delay caused by the sensitivity of the ISL payload equipment to the ambient temperature in space and propose a simple and low-power temperature-sensing ranging compensation sensor suitable for onboard equipment. The experimental results show that, after the temperature-sensing ranging compensation of the ISL payload equipment, the ranging consistency becomes less than 0.2 ns when the temperature change is 90 °C. PMID:28608809

Analysis and demonstration of vibration waveform reconstruction in distributed optical fiber vibration sensing system

NASA Astrophysics Data System (ADS)

Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-10-01

A method for reconstructing the vibration waveform from the optical time-domain backscattering pulses in the distributed optical fiber sensing system (DOFSS) is proposed, which allows for extracting and recovering the external vibration signal from the tested pulses by analog signal processing, so that can obtain vibration location and waveform simultaneously. We establish the response model of DOFSS to the external vibration and analyze the effects of system parameters on the operational performance. The main parts of the DOFSS are optimized, including delay fiber length and wavelength, to improve the sensitivity of the system. The experimental system is set up and the vibration amplitudes and reconstructed waveforms are fit well with the original driving signal. The experimental results demonstrate that the performance of vibration waveform reconstruction is good with SNR of 15 dB whenever the external vibrations with different intensities and frequencies exert on the sensing fiber.

Aligned hierarchical Ag/ZnO nano-heterostructure arrays via electrohydrodynamic nanowire template for enhanced gas-sensing properties.

PubMed

Yin, Zhouping; Wang, Xiaomei; Sun, Fazhe; Tong, Xiaohu; Zhu, Chen; Lv, Qiying; Ye, Dong; Wang, Shuai; Luo, Wei; Huang, YongAn

2017-09-22

Gas sensing performance can be improved significantly by the increase in both the effective gas exposure area and the surface reactivitiy of ZnO nanorods. Here, we propose aligned hierarchical Ag/ZnO nano-heterostructure arrays (h-Ag/ZnO-NAs) via electrohydrodynamic nanowire template, together with a subsequent hydrothermal synthesis and photoreduction reaction. The h-Ag/ZnO-NAs scatter at top for higher specific surface areas with the air, simultaneously contact at root for the electrical conduction. Besides, the ZnO nanorods are uniformly coated with dispersed Ag nanoparticles, resulting in a tremendous enhancement of the surface reactivity. Compared with pure ZnO, such h-Ag/ZnO-NAs exhibit lower electrical resistance and faster responses. Moreover, they demonstrate enhanced NO 2 gas sensing properties. Self-assembly via electrohydrodynamic nanowire template paves a new way for the preparation of high performance gas sensors.

Best Practices for the Application of Functional Near Infrared Spectroscopy to Operator State Sensing

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Hylton, Alan G.; Hearn, Tristan A.

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neuronal measurement technique with many advantages for application in operational and training contexts. Instrumentation and protocol improvements, however, are required to obtain useful signals and produce expeditiously self-applicable, comfortable and unobtrusive headgear. Approaches for improving the validity and reliability of fNIRS data for the purpose of sensing the mental state of commercial aircraft operators are identified, and an exemplary system design for attentional state monitoring is outlined. Intelligent flight decks of the future can be responsive to state changes to optimally support human performance. Thus, the identification of cognitive performance decrement, such as lapses in operator attention, may be used to predict and avoid error-prone states. We propose that attentional performance may be monitored with fNIRS through the quantification of hemodynamic activations in cortical regions which are part of functionally-connected attention and resting state networks. Activations in these regions have been shown to correlate with behavioral performance and task engagement. These regions lie beneath superficial tissue in head regions beyond the forehead. Headgear development is key to reliably and robustly accessing locations beyond the hair line to measure functionally-connected networks across the whole head. Human subject trials using both fNIRS and functional Magnetic Resonance Imaging (fMRI) will be used to test this system. Data processing employs Support Vector Machines for state classification based on the fNIRS signals. If accurate state classification is achieved based on sensed activation patterns, fNIRS will be shown to be useful for monitoring attentional performance.

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

NASA Astrophysics Data System (ADS)

Shao, Haidong; Jiang, Hongkai; Zhang, Haizhou; Duan, Wenjing; Liang, Tianchen; Wu, Shuaipeng

2018-02-01

The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.

Recent developments for the Large Binocular Telescope Guiding Control Subsystem

NASA Astrophysics Data System (ADS)

Golota, T.; De La Peña, M. D.; Biddick, C.; Lesser, M.; Leibold, T.; Miller, D.; Meeks, R.; Hahn, T.; Storm, J.; Sargent, T.; Summers, D.; Hill, J.; Kraus, J.; Hooper, S.; Fisher, D.

2014-07-01

The Large Binocular Telescope (LBT) has eight Acquisition, Guiding, and wavefront Sensing Units (AGw units). They provide guiding and wavefront sensing capability at eight different locations at both direct and bent Gregorian focal stations. Recent additions of focal stations for PEPSI and MODS instruments doubled the number of focal stations in use including respective motion, camera controller server computers, and software infrastructure communicating with Guiding Control Subsystem (GCS). This paper describes the improvements made to the LBT GCS and explains how these changes have led to better maintainability and contributed to increased reliability. This paper also discusses the current GCS status and reviews potential upgrades to further improve its performance.

Glass Fibers for Printed Circuit Boards

NASA Astrophysics Data System (ADS)

Longobardo, Anthony V.

Fiberglass imparts numerous positive benefits to modern printed circuit boards. Reinforced laminate composites have an excellent cost-performance relationship that makes sense for most applications. At the leading edge of the technology, new glass fibers with improved properties, in combination with the best resin systems available, are able to meet very challenging performance, cost, and regulatory demands while remaining manufacturable.

Practical Guide to Designing Comprehensive Principal Evaluation Systems: A Tool to Assist in the Development of Principal Evaluation Systems. Revised Edition

ERIC Educational Resources Information Center

Clifford, Matthew; Hansen, Ulcca Joshni; Wraight, Sara

2014-01-01

Across the country, states and districts are designing principal evaluation systems as a means of improving leadership, learning, and school performance. Principal evaluation systems hold potential for supporting leaders' learning and sense of accountability for instructional excellence and student performance. Principal evaluation also is an…

A Practical Guide to Designing Comprehensive Principal Evaluation Systems: A Tool to Assist in the Development of Principal Evaluation Systems

ERIC Educational Resources Information Center

Clifford, Matthew; Hansen, Ulcca Joshni; Wraight, Sara

2012-01-01

Across the country, states and districts are designing principal evaluation systems as a means of improving leadership, learning, and school performance. Principal evaluation systems hold potential for supporting leaders' learning and sense of accountability for instructional excellence and student performance. Principal evaluation is also an…

Enhancement of humidity sensitivity of graphene through functionalization with polyethylenimine

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

Ben Aziza, Zeineb; School of Electrical and Electronics Engineering, Nanyang Technological University, Block S1, 50 Nanyang Avenue, Singapore 639798; XLIM UMR 7252 Université de Limoges/CNRS, 123 Avenue Albert Thomas, 87060 Limoges

2015-09-28

In this work, we show that the sensing performance of graphene based humidity sensors can be largely improved through polymer functionalization. Chemical vapor deposited graphene is functionalized with amine rich polymer, leading to electron transfer from amine groups in the polymer to graphene. The functionalized graphene humidity sensor has demonstrated good sensitivity, recovery, and repeatability. Charge transfer between the functionalized graphene and water molecules and the sensing mechanism are studied systemically using field effect transistor geometry and scanning Kelvin probe microscopy.

Stellar tracking attitude reference system

NASA Technical Reports Server (NTRS)

Klestadt, B.

1974-01-01

A satellite precision attitude control system was designed, based on the use of STARS as the principal sensing system. The entire system was analyzed and simulated in detail, considering the nonideal properties of the control and sensing components and realistic spacecraft mass properties. Experimental results were used to improve the star tracker noise model. The results of the simulation indicate that STARS performs in general as predicted in a realistic application and should be a strong contender in most precision earth pointing applications.

The decoration of Nb-doped TiO2 microspheres by reduced graphene oxide for enhanced CO gas sensing

NASA Astrophysics Data System (ADS)

Liang, Feng; Chen, Shimin; Xie, Wei; Zou, Changwei

2018-03-01

Reduced graphene oxide (rGO) was used to improve the CO sensing properties of Nb-doped TiO2 (TiO2:Nb) microspheres by an improved ultrasonic spray pyrolysis deposition method. The responses of the sensor dramatically increased as the CO gas concentration increased from 100 to 1000 ppm, which indicated that rGO/TiO2:Nb-based sensor had a wide detection range for CO gas. Moreover, the conductivity of sensor based on the rGO/TiO2:Nb would be greatly improved than that of sensors without decoration by rGO. The enhanced gas sensing performance of the rGO/TiO2:Nb can be attributed to two reasons. Firstly, rGO could facilitate charge transport from TiO2 to graphene which provided a preferential pathway for the charge currents. Secondly, the decorated TiO2 by rGO could provide more active sites such as oxygen vacancy (VO) which could capture electrons from the conductance band and form a space-charge region.

Comparison of Effects of a Proprioceptive Exercise Program in Water and on Land the Balance of Chronic Stroke Patients

PubMed Central

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-01-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients. PMID:24259761

Comparison of effects of a proprioceptive exercise program in water and on land the balance of chronic stroke patients.

PubMed

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-10-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients.

Mapping Tamarix: New techniques for field measurements, spatial modeling and remote sensing

NASA Astrophysics Data System (ADS)

Evangelista, Paul H.

Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Ni doping effect on the electronic and sensing properties of 2D SnO2

NASA Astrophysics Data System (ADS)

Patel, Anjali; Roondhe, Basant; Jha, Prafulla K.

2018-05-01

In the present work using state of art first principles calculations under the frame work of density functional theory the effect of Nickel (Ni) doping on electronic as well as sensing properties of most stable two dimensional (2D) T-SnO2 phase towards ethanol (C2H5OH) has been observed. It has been found that Ni atom when dope on T-SnO2 causes prominent decrement in the band gap from 2.26 eV to 1.48 eV and improves the sensing phenomena of pristine T-SnO2 towards C2H5OH by increasing the binding energy from -0.18eV to -0.93eV. The comparative analysis of binding energy shows that Ni improves the binding of C2H5OH by 5.16 times the values for pristine T-SnO2. The doping of Ni into 2D T-SnO2 reduces the band gap through lowering of the conduction band minimum, thereby increasing the electron affinity which increases the sensing performance of T-SnO2. The variation in the electronic properties after and before the exposure of ethanol reinforced to use Ni:SnO2 nano structure for sensing applications. The results indicate that the Ni doped T-SnO2 can be utilized in improved optoelectronic as well as sensor devices in the future.

Study on the effect of carbon nanotube coating on the refractive index sensing sensitivity of fiber modal interferometer

NASA Astrophysics Data System (ADS)

Zhang, Ya-nan; Xie, Wen-ge; Wang, Jianzhang; Wang, Pengzhao

2018-01-01

Refractive index sensing of liquid is important in the domain of chemistry and biology. Fiber optical sensors provide an excellent way to measure the refractive index due to their feasible integration to other fiber optics components, high sensitivity, small size, and distributed sensing. However, conventional optical sensors have different shortages. To find a practical way to measure the refractive index of liquid, this paper intended to combine Carbon Nanotube (CNT) with non-core fiber (NCF) to prepare a kind of modal interferometer sensor and to explore the effect of CNT coating on refractive index sensing properties of the modal interferometer. Firstly, a structure of single mode non-core single mode (SNS) fiber with a CNT film coating was proposed and simulated. The simulation results showed that the CNT coating could improve the refractive index sensitivity of the interferometer sensor. Then in the experiment part, the CNT solution was fabricated and deposited onto the NCF, and a refractive index sensing system was built to examine the property of the CNT-coated SNS interferometer sensor. During the experiment, the influence factors of sensitivity were summarized by testing the sensing performance under different conditions, and it was demonstrated that the CNT coating could improve the contrast of the interference spectrum, and also had the possibility to increase the refractive index sensitivity of the interferometer sensor.

The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies

PubMed Central

Pestell, Nicholas; Cramphorn, Luke; Winstone, Benjamin; Giannaccini, Maria Elena; Rossiter, Jonathan; Lepora, Nathan F.

2018-01-01

Abstract Tactile sensing is an essential component in human–robot interaction and object manipulation. Soft sensors allow for safe interaction and improved gripping performance. Here we present the TacTip family of sensors: a range of soft optical tactile sensors with various morphologies fabricated through dual-material 3D printing. All of these sensors are inspired by the same biomimetic design principle: transducing deformation of the sensing surface via movement of pins analogous to the function of intermediate ridges within the human fingertip. The performance of the TacTip, TacTip-GR2, TacTip-M2, and TacCylinder sensors is here evaluated and shown to attain submillimeter accuracy on a rolling cylinder task, representing greater than 10-fold super-resolved acuity. A version of the TacTip sensor has also been open-sourced, enabling other laboratories to adopt it as a platform for tactile sensing and manipulation research. These sensors are suitable for real-world applications in tactile perception, exploration, and manipulation, and will enable further research and innovation in the field of soft tactile sensing. PMID:29297773

The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies.

PubMed

Ward-Cherrier, Benjamin; Pestell, Nicholas; Cramphorn, Luke; Winstone, Benjamin; Giannaccini, Maria Elena; Rossiter, Jonathan; Lepora, Nathan F

2018-04-01

Tactile sensing is an essential component in human-robot interaction and object manipulation. Soft sensors allow for safe interaction and improved gripping performance. Here we present the TacTip family of sensors: a range of soft optical tactile sensors with various morphologies fabricated through dual-material 3D printing. All of these sensors are inspired by the same biomimetic design principle: transducing deformation of the sensing surface via movement of pins analogous to the function of intermediate ridges within the human fingertip. The performance of the TacTip, TacTip-GR2, TacTip-M2, and TacCylinder sensors is here evaluated and shown to attain submillimeter accuracy on a rolling cylinder task, representing greater than 10-fold super-resolved acuity. A version of the TacTip sensor has also been open-sourced, enabling other laboratories to adopt it as a platform for tactile sensing and manipulation research. These sensors are suitable for real-world applications in tactile perception, exploration, and manipulation, and will enable further research and innovation in the field of soft tactile sensing.

Morphology and Gas-Sensing Properties of Tin Oxide Foams with Dual Pore Structure

NASA Astrophysics Data System (ADS)

Nam, Kyungju; Kim, Hyeong-Gwan; Choi, Hyelim; Park, Hyeji; Kang, Jin Soo; Sung, Yung-Eun; Lee, Hee Chul; Choe, Heeman

2017-06-01

Tin oxide is a commonly used gas-sensing material, which can be applied as an n- or p-type gas sensor. To improve the gas-sensing performance of tin oxide, we successfully synthesized tin oxide foam via an ice-templating or freeze-casting method. The tin oxide foam samples showed different morphological features depending on the major processing parameters, which include sintering temperature, sintering time, and the amount of added powder. Based on scanning electron microscopy images, we could identify dual pore structure of tin oxide foam containing `wall' pores ranging from 5.3 μm to 10.7 μm, as well as smaller secondary pores (a few micrometers in size) on the wall surfaces. Gas-sensing performance tests for the synthesized tin oxide foams reveal a sensitivity of 13.1, a response time of 192 s, and a recovery time of 160 s at an ethanol gas concentration of 60 ppm at 300°C. This is a remarkable result given that it showed p-type semiconductor behavior and was used without the addition of any catalyst.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

PubMed

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Vision technology/algorithms for space robotics applications

NASA Technical Reports Server (NTRS)

Krishen, Kumar; Defigueiredo, Rui J. P.

1987-01-01

The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed.

Occupational Therapy (For Parents)

MedlinePlus

... needs improve their cognitive, physical, sensory, and motor skills and enhance their self-esteem and sense of accomplishment. Some people may think that occupational therapy is only for adults; kids, after all, do not have ... kids' skills for playing, school performance, and daily activities and ...

Strategies for enhancing bioluminescent bacterial sensor performance by promoter region manipulation

PubMed Central

Bilic, Benny; Belkin, Shimshon

2010-01-01

Genetically engineered microbial reporter strains are based upon the fusion of an inducible sensing element upstream of a reporting element, so that the construct emits a dose-dependent signal when exposed to the inducing compound(s) or stress factor(s). In this communication1 we described several general approaches undertaken in order to enhance the sensing performance of such promoter::reporter fusions. Significant improvements in detection sensitivity, response kinetics and signal intensity were achieved by modi fication of the length of the promoter-containing DNA fragment, by random or site-directed mutagenesis and by promoter duplication. The general nature of these genetics manipulations makes them applicable to other types of promoter::reporter fusions. PMID:21326942

Time-domain multiplexed high resolution fiber optics strain sensor system based on temporal response of fiber Fabry-Perot interferometers.

PubMed

Chen, Jiageng; Liu, Qingwen; He, Zuyuan

2017-09-04

We developed a multiplexed strain sensor system with high resolution using fiber Fabry-Perot interferometers (FFPI) as sensing elements. The temporal responses of the FFPIs excited by rectangular laser pulses are used to obtain the strain applied on each FFPI. The FFPIs are connected by cascaded couplers and delay fiber rolls for the time-domain multiplexing. A compact optoelectronic system performing closed-loop cyclic interrogation is employed to improve the sensing resolution and the frequency response. In the demonstration experiment, 3-channel strain sensing with resolutions better than 0.1 nε and frequency response higher than 100 Hz is realized.

Integrated control and health monitoring capacitive displacement sensor development task. Orbit transfer rocket engine technology program

NASA Technical Reports Server (NTRS)

Collamore, Frank N.

1989-01-01

The development of a miniature multifunction turbomachinery shaft displacement sensor using state-of-the-art non-contract capacitive sensing technology is described. Axial displacement, radial displacement, and speed are sensed using a single probe within the envelope normally required for a single function. A survey of displacement sensing technology is summarized including inductive, capacitive, optical and ultrasonic techniques. The design and operation of an experimental triple function sensor is described. Test results are included showing calibration tests and simultaneous dynamic testing of multiple functions. Recommendations for design changes are made to improve low temperature performance, reliability, and for design of a flight type signal conditioning unit.

Auditory Force Feedback Substitution Improves Surgical Precision during Simulated Ophthalmic Surgery

PubMed Central

Cutler, Nathan; Balicki, Marcin; Finkelstein, Mark; Wang, Jiangxia; Gehlbach, Peter; McGready, John; Iordachita, Iulian; Taylor, Russell; Handa, James T.

2013-01-01

Purpose. To determine the extent that auditory force feedback (AFF) substitution improves performance during a simulated ophthalmic peeling procedure. Methods. A 25-gauge force-sensing microforceps was linked to two AFF modes. The “alarm” AFF mode sounded when the force reached 9 mN. The “warning” AFF mode made beeps with a frequency proportional to the generated force. Participants with different surgical experience levels were asked to peel a series of bandage strips off a platform as quickly as possible without exceeding 9 mN of force. In study arm A, participants peeled with alarm and warning AFF modes, the order randomized within the experience level. In study arm B, participants first peeled without AFF, then alarm or warning AFF (order randomized within the experience level), and finally without AFF. Results. Of the 28 “surgeon” participants, AFF improved membrane peeling performance, reducing average force generated (P < 0.01), SD of forces (P < 0.05), and force × time above 9 mN (P < 0.01). Short training periods with AFF improved subsequent peeling performance when AFF was turned off, with reductions in average force, SD of force, maximum force, time spent above 9 mN, and force × time above 9 mN (all P < 0.001). Except for maximum force, peeling with AFF reduced all force parameters (P < 0.05) more than peeling without AFF after completing a training session. Conclusions. AFF enables the surgeon to reduce the forces generated with improved precision during phantom membrane peeling, regardless of surgical experience. New force-sensing surgical tools combined with AFF offer the potential to enhance surgical training and improve surgical performance. PMID:23329663

Hybrid SnO2/TiO2 Nanocomposites for Selective Detection of Ultra-Low Hydrogen Sulfide Concentrations in Complex Backgrounds

PubMed Central

Larin, Alexander; Womble, Phillip C.; Dobrokhotov, Vladimir

2016-01-01

In this paper, we present a chemiresistive metal oxide (MOX) sensor for detection of hydrogen sulfide. Compared to the previous reports, the overall sensor performance was improved in multiple characteristics, including: sensitivity, selectivity, stability, activation time, response time, recovery time, and activation temperature. The superior sensor performance was attributed to the utilization of hybrid SnO2/TiO2 oxides as interactive catalytic layers deposited using a magnetron radio frequency (RF) sputtering technique. The unique advantage of the RF sputtering for sensor fabrication is the ability to create ultra-thin films with precise control of geometry, morphology and chemical composition of the product of synthesis. Chemiresistive films down to several nanometers can be fabricated as sensing elements. The RF sputtering technique was found to be very robust for bilayer and multilayer oxide structure fabrication. The geometry, morphology, chemical composition and electronic structure of interactive layers were evaluated in relation to their gas sensing performance, using scanning electron microscopy (SEM), X-ray diffraction technique (XRD), atomic force microscopy (AFM), Energy Dispersive X-ray Spectroscopy (EDAX), UV visible spectroscopy, and Kelvin probe measurements. A sensor based on multilayer SnO2/TiO2 catalytic layer with 10% vol. content of TiO2 demonstrated the best gas sensing performance in all characteristics. Based on the pattern relating material’s characteristics to gas sensing performance, the optimization strategy for hydrogen sulfide sensor fabrication was suggested. PMID:27618900

Single-Crystal Sapphire Optical Fiber Sensor Instrumentation

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

Pickrell, Gary; Scott, Brian; Wang, Anbo

2013-12-31

This report summarizes technical progress on the program “Single-Crystal Sapphire Optical Fiber Sensor Instrumentation,” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology of the Bradley Department of Electrical and Computer Engineering at Virginia Tech. This project was completed in three phases, each with a separate focus. Phase I of the program, from October 1999 to April 2002, was devoted to development of sensing schema for use in high temperature, harsh environments. Different sensing designs were proposed and tested in the laboratory. Phase II of the program, frommore » April 2002 to April 2009, focused on bringing the sensor technologies, which had already been successfully demonstrated in the laboratory, to a level where the sensors could be deployed in harsh industrial environments and eventually become commercially viable through a series of field tests. Also, a new sensing scheme was developed and tested with numerous advantages over all previous ones in Phase II. Phase III of the program, September 2009 to December 2013, focused on development of the new sensing scheme for field testing in conjunction with materials engineering of the improved sensor packaging lifetimes. In Phase I, three different sensing principles were studied: sapphire air-gap extrinsic Fabry-Perot sensors; intensity-based polarimetric sensors; and broadband polarimetric sensors. Black body radiation tests and corrosion tests were also performed in this phase. The outcome of the first phase of this program was the selection of broadband polarimetric differential interferometry (BPDI) for further prototype instrumentation development. This approach is based on the measurement of the optical path difference (OPD) between two orthogonally polarized light beams in a single-crystal sapphire disk. At the beginning of Phase II, in June 2004, the BPDI sensor was tested at the Wabash River coal gasifier facility in Terre Haute, Indiana. Due to business conditions at industrial partner and several logistical problems, this field test was not successful. An alternative high-temperature sensing system using sapphire wafer-based extrinsic Fabry-Perot interferometry was then developed as a significant improvement over the BPDI solution. From June 2006 to June 2008, three consecutive field tests were performed with the new sapphire wafer sensors at the TECO coal gasifier in Tampa, Florida. One of the sensors survived in the industrial coal gasifier for 7 months, over which time the existing thermocouples were replaced twice. The outcome of these TECO field tests suggests that the sapphire wafer sensor has very good potential to be commercialized. However packaging and sensor protection issues need additional development. During Phase III, several major improvements in the design and fabrication process of the sensor have been achieved through experiments and theoretical analysis. Studies on the property of the key components in the sensor head, including the sapphire fiber and sapphire wafer, were also conducted, for a better understanding of the sensor behavior. A final design based on all knowledge and experience has been developed, free of any issues encountered during the entire research. Sensors with this design performed well as expected in lab long-term tests, and were deployed in the sensing probe of the final coal-gasifier field test. Sensor packaging and protection was improved through materials engineering through testing of packaging designs in two blank probe packaging tests at Eastman Chemical in Kingsport, TN. Performance analysis of the blank probe packaging resulted in improve package designs culminating in a 3rd generation probe packaging utilized for the full field test of the sapphire optical sensor and materials designed sensor packaging.« less

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Flight-Test Performance

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.

Electrical and Self-Sensing Properties of Ultra-High-Performance Fiber-Reinforced Concrete with Carbon Nanotubes

PubMed Central

You, Ilhwan; Yoo, Doo-Yeol; Kim, Soonho; Kim, Min-Jae; Zi, Goangseup

2017-01-01

This study examined the electrical and self-sensing capacities of ultra-high-performance fiber-reinforced concrete (UHPFRC) with and without carbon nanotubes (CNTs). For this, the effects of steel fiber content, orientation, and pore water content on the electrical and piezoresistive properties of UHPFRC without CNTs were first evaluated. Then, the effect of CNT content on the self-sensing capacities of UHPFRC under compression and flexure was investigated. Test results indicated that higher steel fiber content, better fiber orientation, and higher amount of pore water led to higher electrical conductivity of UHPFRC. The effects of fiber orientation and drying condition on the electrical conductivity became minor as sufficiently high amount of steel fibers, 3% by volume, was added. Including only steel fibers did not impart UHPFRC with piezoresistive properties. Addition of CNTs substantially improved the electrical conductivity of UHPFRC. Under compression, UHPFRC with a CNT content of 0.3% or greater had a self-sensing ability that was activated by the formation of cracks, and better sensing capacity was achieved by including greater amount of CNTs. Furthermore, the pre-peak flexural behavior of UHPFRC was precisely simulated with a fractional change in resistivity when 0.3% CNTs were incorporated. The pre-cracking self-sensing capacity of UHPFRC with CNTs was more effective under tensile stress state than under compressive stress state. PMID:29109388

Electrical and Self-Sensing Properties of Ultra-High-Performance Fiber-Reinforced Concrete with Carbon Nanotubes.

PubMed

You, Ilhwan; Yoo, Doo-Yeol; Kim, Sooho; Kim, Min-Jae; Zi, Goangseup

2017-10-29

This study examined the electrical and self-sensing capacities of ultra-high-performance fiber-reinforced concrete (UHPFRC) with and without carbon nanotubes (CNTs). For this, the effects of steel fiber content, orientation, and pore water content on the electrical and piezoresistive properties of UHPFRC without CNTs were first evaluated. Then, the effect of CNT content on the self-sensing capacities of UHPFRC under compression and flexure was investigated. Test results indicated that higher steel fiber content, better fiber orientation, and higher amount of pore water led to higher electrical conductivity of UHPFRC. The effects of fiber orientation and drying condition on the electrical conductivity became minor as sufficiently high amount of steel fibers, 3% by volume, was added. Including only steel fibers did not impart UHPFRC with piezoresistive properties. Addition of CNTs substantially improved the electrical conductivity of UHPFRC. Under compression, UHPFRC with a CNT content of 0.3% or greater had a self-sensing ability that was activated by the formation of cracks, and better sensing capacity was achieved by including greater amount of CNTs. Furthermore, the pre-peak flexural behavior of UHPFRC was precisely simulated with a fractional change in resistivity when 0.3% CNTs were incorporated. The pre-cracking self-sensing capacity of UHPFRC with CNTs was more effective under tensile stress state than under compressive stress state.

Teachers' Perceptions of Evaluation and Teachers' Sense of Self-Efficacy in High-Performing High Schools

ERIC Educational Resources Information Center

McCall, James P.

2011-01-01

The evaluation, improvement, and accountability of teachers has been the topic of the nation throughout the era of No Child Left Behind. Where some critics point to a business model of measuring outputs (i.e., student achievement scores on standardized tests) to evaluate teacher performance, others will advocate for a fair evaluation system that…

Searching for a new ionomer for 3D printable ionic polymer-metal composites: Aquivion as a candidate

NASA Astrophysics Data System (ADS)

Trabia, Sarah; Olsen, Zakai; Kim, Kwang J.

2017-11-01

The work presented in this paper introduces Aquivion as a potential candidate for additive manufacturing of ionomeric polymers for the application of IPMCs. First, Aquivion was characterized and compared with Nafion to show that it has the similar qualities, with the major difference being the ionic conductivity. Ionic polymer-metal composites (IPMCs) were fabricated using off-the-shelf membranes of Nafion and Aquivion. The actuation tests showed improved performance for an IPMC with Aquivion as the base compared to an IPMC with a Nafion base. With these results in mind, additive manufacturing of unique shapes using Aquivion filament was studied. A 3D printer was modified to work with Aquivion filament and the polymer was printed into various shapes. Using the printed membranes, IPMCs were fabricated using an electroless plating process. Nafion-based and printed Aquivion-based IPMCs were tested for their performance in back relaxation, frequency driven actuation, blocking force, and mechano-electric sensing. The printed Aquivion-based IPMCs performed comparably to Nafion-based IPMC in back relaxation and showed significantly improved performance in frequency driven actuation, blocking force generation, and mechano-electric sensing.

Wearable carbon nanotube-based fabric sensors for monitoring human physiological performance

NASA Astrophysics Data System (ADS)

Wang, Long; Loh, Kenneth J.

2017-05-01

A target application of wearable sensors is to detect human motion and to monitor physical activity for improving athletic performance and for delivering better physical therapy. In addition, measuring human vital signals (e.g., respiration rate and body temperature) provides rich information that can be used to assess a subject’s physiological or psychological condition. This study aims to design a multifunctional, wearable, fabric-based sensing system. First, carbon nanotube (CNT)-based thin films were fabricated by spraying. Second, the thin films were integrated with stretchable fabrics to form the fabric sensors. Third, the strain and temperature sensing properties of sensors fabricated using different CNT concentrations were characterized. Furthermore, the sensors were demonstrated to detect human finger bending motions, so as to validate their practical strain sensing performance. Finally, to monitor human respiration, the fabric sensors were integrated with a chest band, which was directly worn by a human subject. Quantification of respiration rates were successfully achieved. Overall, the fabric sensors were characterized by advantages such as flexibility, ease of fabrication, lightweight, low-cost, noninvasiveness, and user comfort.

Two-Dimensional Atomic-Layered Alloy Junctions for High-Performance Wearable Chemical Sensor.

PubMed

Cho, Byungjin; Kim, Ah Ra; Kim, Dong Jae; Chung, Hee-Suk; Choi, Sun Young; Kwon, Jung-Dae; Park, Sang Won; Kim, Yonghun; Lee, Byoung Hun; Lee, Kyu Hwan; Kim, Dong-Ho; Nam, Jaewook; Hahm, Myung Gwan

2016-08-03

We first report that two-dimensional (2D) metal (NbSe2)-semiconductor (WSe2)-based flexible, wearable, and launderable gas sensors can be prepared through simple one-step chemical vapor deposition of prepatterned WO3 and Nb2O5. Compared to a control device with a Au/WSe2 junction, gas-sensing performance of the 2D NbSe2/WSe2 device was significantly enhanced, which might have resulted from the formation of a NbxW1-xSe2 transition alloy junction lowering the Schottky barrier height. This would make it easier to collect charges of channels induced by molecule adsorption, improving gas response characteristics toward chemical species including NO2 and NH3. 2D NbSe2/WSe2 devices on a flexible substrate provide gas-sensing properties with excellent durability under harsh bending. Furthermore, the device stitched on a T-shirt still performed well even after conventional cleaning with a laundry machine, enabling wearable and launderable chemical sensors. These results could pave a road toward futuristic gas-sensing platforms based on only 2D materials.

Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhong, Yanfei; Han, Xiaobing; Zhang, Liangpei

2018-04-01

Multi-class geospatial object detection from high spatial resolution (HSR) remote sensing imagery is attracting increasing attention in a wide range of object-related civil and engineering applications. However, the distribution of objects in HSR remote sensing imagery is location-variable and complicated, and how to accurately detect the objects in HSR remote sensing imagery is a critical problem. Due to the powerful feature extraction and representation capability of deep learning, the deep learning based region proposal generation and object detection integrated framework has greatly promoted the performance of multi-class geospatial object detection for HSR remote sensing imagery. However, due to the translation caused by the convolution operation in the convolutional neural network (CNN), although the performance of the classification stage is seldom influenced, the localization accuracies of the predicted bounding boxes in the detection stage are easily influenced. The dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage has not been addressed for HSR remote sensing imagery, and causes position accuracy problems for multi-class geospatial object detection with region proposal generation and object detection. In order to further improve the performance of the region proposal generation and object detection integrated framework for HSR remote sensing imagery object detection, a position-sensitive balancing (PSB) framework is proposed in this paper for multi-class geospatial object detection from HSR remote sensing imagery. The proposed PSB framework takes full advantage of the fully convolutional network (FCN), on the basis of a residual network, and adopts the PSB framework to solve the dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage. In addition, a pre-training mechanism is utilized to accelerate the training procedure and increase the robustness of the proposed algorithm. The proposed algorithm is validated with a publicly available 10-class object detection dataset.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

Sub-bandage sensing system for remote monitoring of chronic wounds in healthcare

NASA Astrophysics Data System (ADS)

Hariz, Alex; Mehmood, Nasir; Voelcker, Nico

2015-12-01

Chronic wounds, such as venous leg ulcers, can be monitored non-invasively by using modern sensing devices and wireless technologies. The development of such wireless diagnostic tools may improve chronic wound management by providing evidence on efficacy of treatments being provided. In this paper we present a low-power portable telemetric system for wound condition sensing and monitoring. The system aims at measuring and transmitting real-time information of wound-site temperature, sub-bandage pressure and moisture level from within the wound dressing. The system comprises commercially available non-invasive temperature, moisture, and pressure sensors, which are interfaced with a telemetry device on a flexible 0.15 mm thick printed circuit material, making up a lightweight biocompatible sensing device. The real-time data obtained is transmitted wirelessly to a portable receiver which displays the measured values. The performance of the whole telemetric sensing system is validated on a mannequin leg using commercial compression bandages and dressings. A number of trials on a healthy human volunteer are performed where treatment conditions were emulated using various compression bandage configurations. A reliable and repeatable performance of the system is achieved under compression bandage and with minimal discomfort to the volunteer. The system is capable of reporting instantaneous changes in bandage pressure, moisture level and local temperature at wound site with average measurement resolutions of 0.5 mmHg, 3.0 %RH, and 0.2 °C respectively. Effective range of data transmission is 4-5 m in an open environment.

Trilayer TMDC Heterostructures for MOSFETs and Nanobiosensors

NASA Astrophysics Data System (ADS)

Datta, Kanak; Shadman, Abir; Rahman, Ehsanur; Khosru, Quazi D. M.

2017-02-01

Two dimensional materials such as transition metal dichalcogenides (TMDC) and their bi-layer/tri-layer heterostructures have become the focus of intense research and investigation in recent years due to their promising applications in electronics and optoelectronics. In this work, we have explored device level performance of trilayer TMDC heterostructure (MoS2/MX2/MoS2; M = Mo or, W and X = S or, Se) metal oxide semiconductor field effect transistors (MOSFETs) in the quantum ballistic regime. Our simulation shows that device `on' current can be improved by inserting a WS2 monolayer between two MoS2 monolayers. Application of biaxial tensile strain reveals a reduction in drain current which can be attributed to the lowering of carrier effective mass with increased tensile strain. In addition, it is found that gate underlap geometry improves electrostatic device performance by improving sub-threshold swing. However, increase in channel resistance reduces drain current. Besides exploring the prospect of these materials in device performance, novel trilayer TMDC heterostructure double gate field effect transistors (FETs) are proposed for sensing Nano biomolecules as well as for pH sensing. Bottom gate operation ensures these FETs operating beyond Nernst limit of 59 mV/pH. Simulation results found in this work reveal that scaling of bottom gate oxide results in better sensitivity while top oxide scaling exhibits an opposite trend. It is also found that, for identical operating conditions, proposed TMDC FET pH sensors show super-Nernst sensitivity indicating these materials as potential candidates in implementing such sensor. Besides pH sensing, all these materials show high sensitivity in the sub-threshold region as a channel material in nanobiosensor while MoS2/WS2/MoS2 FET shows the least sensitivity among them.

Multi-Modal Active Perception for Autonomously Selecting Landing Sites on Icy Moons

NASA Technical Reports Server (NTRS)

Arora, A.; Furlong, P. M.; Wong, U.; Fong, T.; Sukkarieh, S.

2017-01-01

Selecting suitable landing sites is fundamental to achieving many mission objectives in planetary robotic lander missions. However, due to sensing limitations, landing sites which are both safe and scientifically valuable often cannot be determined reliably from orbit, particularly, in icy moon missions where orbital sensing data is noisy and incomplete. This paper presents an active perception approach to Entry Descent and Landing (EDL) which enables the lander to autonomously plan informative descent trajectories, acquire high quality sensing data during descent and exploit this additional information to select higher utility landing sites. Our approach consists of two components: probabilistic modeling of landing site features and approximate trajectory planning using a sampling based planner. The proposed framework allows the lander to plan long horizons paths and remain robust to noisy data. Results in simulated environments show large performance improvements over alternative approaches and show promise that our approach has strong potential to improve science return of not only icy moon missions but EDL systems in general.

Stress-anneal-induced magnetic anisotropy in highly textured Fe-Ga and Fe-Al magnetostrictive strips for bending-mode vibrational energy harvesters

NASA Astrophysics Data System (ADS)

Park, Jung Jin; Na, Suok-Min; Raghunath, Ganesh; Flatau, Alison B.

2016-05-01

Magnetostrictive Fe-Ga and Fe-Al alloys are promising materials for use in bending-mode vibrational energy harvesters. For this study, 50.8 mm × 5.0 mm × 0.5 mm strips of Fe-Ga and Fe-Al were cut from 0.50-mm thick rolled sheet. An atmospheric anneal was used to develop a Goss texture through an abnormal grain growth process. The anneal lead to large (011) grains that covered over 90% of sample surface area. The resulting highly-textured Fe-Ga and Fe-Al strips exhibited saturation magnetostriction values (λsat = λ∥ - λ⊥) of ˜280 ppm and ˜130 ppm, respectively. To maximize 90° rotation of magnetic moments during bending of the strips, we employed compressive stress annealing (SA). Samples were heated to 500°C, and a 100-150 MPa compressive stress was applied while at 500°C for 30 minutes and while being cooled. The effectiveness of the SA on magnetic moment rotation was inferred by comparing post-SA magnetostriction with the maximum possible yield of rotated magnetic moments, which is achieved when λ∥ = λsat and λ⊥ = 0. The uniformity of the SA along the sample length and the impact of the SA on sensing/energy harvesting performance were then assessed by comparing pre- and post-SA bending-stress-induced changes in magnetization at five different locations along the samples. The SA process with a 150 MPa compressive load improved Fe-Ga actuation along the sample length from 170 to 225 ppm (from ˜60% to within ˜80% of λsat). The corresponding sensing/energy harvesting performance improved by as much as a factor of eight in the best sample, however the improvement was not at all uniform along the sample length. The SA process with a 100 MPa compressive load improved Fe-Al actuation along the sample length from 60 to 73 ppm (from ˜46% to ˜56% of λsat, indicating only a marginally effective SA and suggesting the need for modification of the SA protocol. In spite of this, the SA was effective at improving the sensing/energy harvesting performance by a factor of ˜2.5 in the best sample. As with the Fe-Ga strip, improvement in performance was quite varied along the strip length.

Improving management performance of P2PSIP for mobile sensing in wireless overlays.

PubMed

Sendín-Raña, Pablo; González-Castaño, Francisco Javier; Gómez-Cuba, Felipe; Asorey-Cacheda, Rafael; Pousada-Carballo, José María

2013-11-08

Future wireless communications are heading towards an all-Internet Protocol (all-IP) design, and will rely on the Session Initiation Protocol (SIP) to manage services, such as voice over IP (VoIP). The centralized architecture of traditional SIP has numerous disadvantages for mobile ad hoc services that may be possibly overcome by advanced peer-to-peer (P2P) technologies initially developed for the Internet. In the context of mobile sensing, P2PSIP protocols facilitate decentralized and fast communications with sensor-enabled terminals. Nevertheless, in order to make P2PSIP protocols feasible in mobile sensing networks, it is necessary to minimize overhead transmissions for signaling purposes, which reduces the battery lifetime. In this paper, we present a solution to improve the management of wireless overlay networks by defining an adaptive algorithm for the calculation of refresh time. The main advantage of the proposed algorithm is that it takes into account new parameters, such as the delay between nodes, and provides satisfactory performance and reliability levels at a much lower management overhead than previous approaches. The proposed solution can be applied to many structured P2P overlays or P2PSIP protocols. We evaluate it with Kademlia-based distributed hash tables (DHT) and dSIP.

Improving Management Performance of P2PSIP for Mobile Sensing in Wireless Overlays

PubMed Central

Sendín-Raña, Pablo; González-Castaño, Francisco Javier; Gómez-Cuba, Felipe; Asorey-Cacheda, Rafael; Pousada-Carballo, José María

2013-01-01

Future wireless communications are heading towards an all-Internet Protocol (all-IP) design, and will rely on the Session Initiation Protocol (SIP) to manage services, such as voice over IP (VoIP). The centralized architecture of traditional SIP has numerous disadvantages for mobile ad hoc services that may be possibly overcome by advanced peer-to-peer (P2P) technologies initially developed for the Internet. In the context of mobile sensing, P2PSIP protocols facilitate decentralized and fast communications with sensor-enabled terminals. Nevertheless, in order to make P2PSIP protocols feasible in mobile sensing networks, it is necessary to minimize overhead transmissions for signaling purposes, which reduces the battery lifetime. In this paper, we present a solution to improve the management of wireless overlay networks by defining an adaptive algorithm for the calculation of refresh time. The main advantage of the proposed algorithm is that it takes into account new parameters, such as the delay between nodes, and provides satisfactory performance and reliability levels at a much lower management overhead than previous approaches. The proposed solution can be applied to many structured P2P overlays or P2PSIP protocols. We evaluate it with Kademlia-based distributed hash tables (DHT) and dSIP PMID:24217358

The efficacy of elastic therapeutic tape variations on measures of ankle function and performance.

PubMed

Brogden, Christopher Michael; Marrin, Kelly; Page, Richard Michael; Greig, Matt

2018-04-23

To investigate the effects of different variations of elastic therapeutic taping (ETT) on tests used to screen for ankle injury risk and function. Randomized crossover. Laboratory. Twelve professional male soccer players completed three experimental trials: No tape (NT), RockTape™ (RT), and Kinesio™ Tape (KT) applied to the ankle complex. Clinical and functional ankle screening tests were used to assess the effects of ETT on measures of joint position sense, postural stability and ground reaction forces. KT (P = 0.04) and RT (P = 0.01) demonstrated significant improvements in end range joint position sense. When compared to NT, RT significantly (P = 0.02) improved mid-range joint position sense at 15°, and time to complete a drop landing task. No significant differences were observed for measures of postural stability (P ≥ 0.12) nor ground reaction force variables (P ≥ 0.33). Results advocate the use of ETT for proprioceptive and functional tasks when applied to the ankles of healthy male soccer players. However, a greater number of practical and significant differences were observed when RT only was applied, indicating that practitioners may potentially advocate the use of RT for tasks requiring proprioception and functional performance. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir; Mutanga, Onisimo; Lottering, Romano; Bangamwabo, Victor; Ismail, Riyad

2016-11-01

The invasive weed Solanum mauritianum (bugweed) has infested large areas of plantation forests in KwaZulu-Natal, South Africa. Bugweed often forms dense infestations and rapidly capitalises on available natural resources hindering the production of forest resources. Precise assessment of bugweed canopy cover, especially at low abundance cover, is essential to an effective weed management strategy. In this study, the utility of AISA Eagle airborne hyperspectral data (393-994 nm) with the new generation Worldview-2 multispectral sensor (427-908 nm) was compared to detect the abundance of bugweed cover within the Hodgsons Sappi forest plantation. Using sparse partial least squares discriminant analysis (SPLS-DA), the best detection results were obtained when performing discrimination using the remotely sensing images combined with LiDAR. Overall classification accuracies subsequently improved by 10% and 11.67% for AISA and Worldview-2 respectively, with improved detection accuracies for bugweed cover densities as low as 5%. The incorporation of LiDAR worked well within the SPLS-DA framework for detecting the abundance of bugweed cover using remotely sensed data. In addition, the algorithm performed simultaneous dimension reduction and variable selection successfully whereby wavelengths in the visible (393-670 nm) and red-edge regions (725-734 nm) of the spectrum were the most effective.

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.

Aviation Safety Program Atmospheric Environment Safety Technologies (AEST) Project

NASA Technical Reports Server (NTRS)

Colantonio, Ron

2011-01-01

Engine Icing: Characterization and Simulation Capability: Develop knowledge bases, analysis methods, and simulation tools needed to address the problem of engine icing; in particular, ice-crystal icing Airframe Icing Simulation and Engineering Tool Capability: Develop and demonstrate 3-D capability to simulate and model airframe ice accretion and related aerodynamic performance degradation for current and future aircraft configurations in an expanded icing environment that includes freezing drizzle/rain Atmospheric Hazard Sensing and Mitigation Technology Capability: Improve and expand remote sensing and mitigation of hazardous atmospheric environments and phenomena

Smart wearable Kevlar-based safeguarding electronic textile with excellent sensing performance.

PubMed

Wang, Sheng; Xuan, Shouhu; Liu, Mei; Bai, Linfeng; Zhang, Shuaishuai; Sang, Min; Jiang, Wanquan; Gong, Xinglong

2017-03-29

A novel S-ST/MWCNT/Kevlar-based wearable electronic textile (WET) with enhanced safeguarding performance and force sensing ability was fabricated. Stab resistance performance tests under quasi-static and dynamic conditions show that the maximum resistance force and penetration impact energy for the WET are 18 N and 11.76 J, which represent a 90% and 50% increment with respect to the neat Kevlar, respectively. Dynamic impact resistance tests show that the WET absorbs all the impact energy. The maximum resistance force of the WET is 1052 N, which represents an improvement of about 190% with respect to neat Kevlar. With the incorporation of multi-walled carbon nanotubes (MWCNTs), the WET can achieve a stable electrical conductivity of ∼10 -2 S m -1 , and the conductivity is highly sensitive to external mechanic forces. Notably, the sensing fabric also exhibits an outstanding ability to detect and analyze external forces. In addition, it can be fixed at any position of the human body and exhibits an ideal monitoring performance. Because of its flexibility, high sensitivity to various types of deformations and excellent safeguarding performance, the WET has a strong potential for wearable monitoring devices that simultaneously provide body protection and monitor the movements of the human body under various conditions.

Trace gas detection in hyperspectral imagery using the wavelet packet subspace

NASA Astrophysics Data System (ADS)

Salvador, Mark A. Z.

This dissertation describes research into a new remote sensing method to detect trace gases in hyperspectral and ultra-spectral data. This new method is based on the wavelet packet transform. It attempts to improve both the computational tractability and the detection of trace gases in airborne and spaceborne spectral imagery. Atmospheric trace gas research supports various Earth science disciplines to include climatology, vulcanology, pollution monitoring, natural disasters, and intelligence and military applications. Hyperspectral and ultra-spectral data significantly increases the data glut of existing Earth science data sets. Spaceborne spectral data in particular significantly increases spectral resolution while performing daily global collections of the earth. Application of the wavelet packet transform to the spectral space of hyperspectral and ultra-spectral imagery data potentially improves remote sensing detection algorithms. It also facilities the parallelization of these methods for high performance computing. This research seeks two science goals, (1) developing a new spectral imagery detection algorithm, and (2) facilitating the parallelization of trace gas detection in spectral imagery data.

Bottle-brush-shaped heterostructures of NiO-ZnO nanowires: growth study and sensing properties

NASA Astrophysics Data System (ADS)

Baratto, C.; Kumar, R.; Comini, E.; Ferroni, M.; Campanini, M.

2017-11-01

We present here heterostructured ZnO-NiO nanowires (NWs), constituted by a core of single crystalline ZnO NWs, covered by poly-crystalline NiO nanorods (NRs). The bottle-brush shape was investigated by scanning electron microscopy and transmission electron microscope, confirming that a columnar growth of NiO occurred over the ZnO core, with a preferred orientation of NiO over ZnO NWs. The heterostructured devices are proposed for gas sensing application. Bare ZnO NWs and heterostructured sensors with two different thicknesses of NiO poly-crystalline NRs were analysed for acetone, ethanol, NO2 and H2 detection. All sensors maintained n-type sensing mechanism, with improved sensing performance for lower thickness of NiO, due to high catalytic activity of NiO. The sensing dynamic is also strongly modified by the presence of heterojunction of NiO/ZnO, with a reduction of response and recovery times towards ethanol and acetone at 400 °C.

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

NASA Astrophysics Data System (ADS)

Lin, Daoyu; Fu, Kun; Wang, Yang; Xu, Guangluan; Sun, Xian

2017-11-01

With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the limited amount of labeled data available, supervised learning is often difficult to carry out. Therefore, we proposed an unsupervised model called multiple-layer feature-matching generative adversarial networks (MARTA GANs) to learn a representation using only unlabeled data. MARTA GANs consists of both a generative model $G$ and a discriminative model $D$. We treat $D$ as a feature extractor. To fit the complex properties of remote sensing data, we use a fusion layer to merge the mid-level and global features. $G$ can produce numerous images that are similar to the training data; therefore, $D$ can learn better representations of remotely sensed images using the training data provided by $G$. The classification results on two widely used remote sensing image databases show that the proposed method significantly improves the classification performance compared with other state-of-the-art methods.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

PubMed Central

Liang, Zhuo-qian

2017-01-01

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

PubMed

Liu, Tong; Liang, Zhuo-Qian

2017-12-05

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

High-Speed Lateral Flow Strategy for a Fast Biosensing with an Improved Selectivity and Binding Affinity.

PubMed

Cho, Dong Guk; Yoo, Haneul; Lee, Haein; Choi, Yeol Kyo; Lee, Minju; Ahn, Dong June; Hong, Seunghun

2018-05-10

We report a high-speed lateral flow strategy for a fast biosensing with an improved selectivity and binding affinity even under harsh conditions. In this strategy, biosensors were fixed at a location away from the center of a round shape disk, and the disk was rotated to create the lateral flow of a target solution on the biosensors during the sensing measurements. Experimental results using the strategy showed high reaction speeds, high binding affinity, and low nonspecific adsorptions of target molecules to biosensors. Furthermore, binding affinity between target molecules and sensing molecules was enhanced even in harsh conditions such as low pH and low ionic strength conditions. These results show that the strategy can improve the performance of conventional biosensors by generating high-speed lateral flows on a biosensor surface. Therefore, our strategy can be utilized as a simple but powerful tool for versatile bio and medical applications.

Low-temperature solution processing of palladium/palladium oxide films and their pH sensing performance.

PubMed

Qin, Yiheng; Alam, Arif U; Pan, Si; Howlader, Matiar M R; Ghosh, Raja; Selvaganapathy, P Ravi; Wu, Yiliang; Deen, M Jamal

2016-01-01

Highly sensitive, easy-to-fabricate, and low-cost pH sensors with small dimensions are required to monitor human bodily fluids, drinking water quality and chemical/biological processes. In this study, a low-temperature, solution-based process is developed to prepare palladium/palladium oxide (Pd/PdO) thin films for pH sensing. A precursor solution for Pd is spin coated onto pre-cleaned glass substrates and annealed at low temperature to generate Pd and PdO. The percentages of PdO at the surface and in the bulk of the electrodes are correlated to their sensing performance, which was studied by using the X-ray photoelectron spectroscope. Large amounts of PdO introduced by prolonged annealing improve the electrode's sensitivity and long-term stability. Atomic force microscopy study showed that the low-temperature annealing results in a smooth electrode surface, which contributes to a fast response. Nano-voids at the electrode surfaces were observed by scanning electron microscope, indicating a reason for the long-term degradation of the pH sensitivity. Using the optimized annealing parameters of 200°C for 48 h, a linear pH response with sensitivity of 64.71±0.56 mV/pH is obtained for pH between 2 and 12. These electrodes show a response time shorter than 18 s, hysteresis less than 8 mV and stability over 60 days. High reproducibility in the sensing performance is achieved. This low-temperature solution-processed sensing electrode shows the potential for the development of pH sensing systems on flexible substrates over a large area at low cost without using vacuum equipment. Copyright © 2015 Elsevier B.V. All rights reserved.

Large-area sheet task advanced dendritic web growth development

NASA Technical Reports Server (NTRS)

Duncan, C. S.; Seidensticker, R. G.; Mchugh, J. P.; Hopkins, R. H.; Meier, D.; Schruben, J.

1982-01-01

The thermal stress model was used to generate the design of a low stress lid and shield configuration, which was fabricated and tested experimentally. In preliminary tests, the New Experimental Web Growth Facility performed as designed, producing web on the first run. These experiments suggested desirable design modifications in the melt level sensing system to improve further its performance, and these are being implemented.

Applications of Microbial Cell Sensors

NASA Astrophysics Data System (ADS)

Shimomura-Shimizu, Mifumi; Karube, Isao

Since the first microbial cell sensor was studied by Karube et al. in 1977, many types of microbial cell sensors have been developed as analytical tools. The microbial cell sensor utilizes microbes as a sensing element and a transducer. The characteristics of microbial cell sensors as sensing devices are a complete contrast to those of enzyme sensors or immunosensors, which are highly specific for the substrates of interest, although the specificity of the microbial cell sensor has been improved by genetic modification of the microbe used as the sensing element. Microbial cell sensors have the advantages of tolerance to measuring conditions, a long lifetime, and good cost performance, and have the disadvantage of a long response time. In this review, applications of microbial cell sensors are summarized.

Airplane detection in remote sensing images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

Lowe, D. S.; Istvan, L. B.; Roller, N. E. G.; Sellman, A. N.; Wagner, T. W.

1975-01-01

The utilization of NASA earth resource survey technology as an important aid in the solution of current problems in resource management and environmental protection in Michigan is discussed. Remote sensing techniques to aid Michigan government agencies were used to achieve the following results: (1) provide data on Great Lakes beach recession rates to establish shoreline zoning ordinances; (2) supply technical justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (3) establish economical and effective methods for performing a statewide wetlands survey; (4) accomplish a variety of regional resource management actions in the Upper Peninsula; and (5) demonstrate improved soil survey methods. The project disseminated information on remote sensing technology and provided advice and assistance to a number of users in Michigan.

On the relevance of using open wireless sensor networks in environment monitoring.

PubMed

Bagula, Antoine B; Inggs, Gordon; Scott, Simon; Zennaro, Marco

2009-01-01

This paper revisits the problem of the readiness for field deployments of wireless sensor networks by assessing the relevance of using Open Hardware and Software motes for environment monitoring. We propose a new prototype wireless sensor network that fine-tunes SquidBee motes to improve the life-time and sensing performance of an environment monitoring system that measures temperature, humidity and luminosity. Building upon two outdoor sensing scenarios, we evaluate the performance of the newly proposed energy-aware prototype solution in terms of link quality when expressed by the Received Signal Strength, Packet Loss and the battery lifetime. The experimental results reveal the relevance of using the Open Hardware and Software motes when setting up outdoor wireless sensor networks.

Bionanomaterials and Bioinspired Nanostructures for Selective Vapor Sensing

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav; Naik, Rajesh R.

2013-07-01

At present, monitoring of air at the workplace, in urban environments, and on battlefields; exhaled air from medical patients; air in packaged food containers; and so forth can be accomplished with different types of analytical instruments. Vapor sensors have their niche in these measurements when an unobtrusive, low-power, and cost-sensitive technical solution is required. Unfortunately, existing vapor sensors often degrade their vapor-quantitation accuracy in the presence of high levels of interferences and cannot quantitate several components in complex gas mixtures. Thus, new sensing approaches with improved sensor selectivity are required. This technological task can be accomplished by the careful design of sensing materials with new performance properties and by coupling these materials with the suitable physical transducers. This review is focused on the assessment of the capabilities of bionanomaterials and bioinspired nanostructures for selective vapor sensing. We demonstrate that these sensing materials can operate with diverse transducers based on electrical, mechanical, and optical readout principles and can provide vapor-response selectivity previously unattainable by using other sensing materials. This ability for selective vapor sensing provides opportunities to significantly impact the major directions in development and application scenarios of vapor sensors.

Online Remote Sensing Interface

NASA Technical Reports Server (NTRS)

Lawhead, Joel

2007-01-01

BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

Theoretical study of modulated multi-layer SPR device for improved refractive index sensing

NASA Astrophysics Data System (ADS)

Mohapatra, Saswat; Moirangthem, Rakesh S.

2018-02-01

In the present work, a theoretical investigation of Surface Plasmon Resonance (SPR) properties of a multilayer film (Au-SiO2-Au) coated on a glass prism is being carried out. In this multilayer structure, each interface corresponds to multiple SPR modes. To obtain the maximum reflection dips in the SPR modes, the thickness of SiO2 layer is optimized by varying it from 100-600 nm. Our calculation also reveals that SPR mode corresponding to Au-ambient interface is very sensitive to the changes in the surrounding medium, least affecting other SPR modes. The sensing performance of the proposed nano-plasmonic sensor is theoretically calculated using bulk refractive index sensing. Such multilayer SPR sensing device has advantages over conventional SPR devices in terms of their bulk sensitivity and self-referencing, claiming itself as a potential candidate for the development of highly sensitive biological sensor.

Compensation of Verdet Constant Temperature Dependence by Crystal Core Temperature Measurement

PubMed Central

Petricevic, Slobodan J.; Mihailovic, Pedja M.

2016-01-01

Compensation of the temperature dependence of the Verdet constant in a polarimetric extrinsic Faraday sensor is of major importance for applying the magneto-optical effect to AC current measurements and magnetic field sensing. This paper presents a method for compensating the temperature effect on the Faraday rotation in a Bi12GeO20 crystal by sensing its optical activity effect on the polarization of a light beam. The method measures the temperature of the same volume of crystal that effects the beam polarization in a magnetic field or current sensing process. This eliminates the effect of temperature difference found in other indirect temperature compensation methods, thus allowing more accurate temperature compensation for the temperature dependence of the Verdet constant. The method does not require additional changes to an existing Δ/Σ configuration and is thus applicable for improving the performance of existing sensing devices. PMID:27706043

Facile and controllable synthesis of hydroxyapatite/graphene hybrid materials with enhanced sensing performance towards ammonia.

PubMed

Zhang, Qing; Liu, Yong; Zhang, Ying; Li, Huixia; Tan, Yanni; Luo, Lanlan; Duan, Junhao; Li, Kaiyang; Banks, Craig E

2015-08-07

In this work, needle-like and micro-spherical agglomerates of nanocrystalline hydroxyapatite (HA) were successfully assembled on the surface of graphene sheets with the aid of dopamine having two roles, as a template and a reductant for graphite oxide during the process of self-polymerization. The crystalline structure and micromorphology of HA can be conveniently regulated by controlling the mineralization route either with a precipitation (cHA/GR) or biomimetic methodology (bHA/GR). Both the composites exhibit improvements of ∼150% and ∼250% in sensitivity towards the sensing of ammonia at room temperature, compared with that of bare graphene. The combination of the multi-adsorption capability of HA and the electric conductivity of graphene is proposed to be the major reason for the observed enhancements. Gas sensing tests demonstrated that the HA/GR composites exhibit excellent selectivity, high sensitivity and repeatable stability towards the analytical sensing of ammonia.

Synthesis of Co3O4/TiO2 composite by pyrolyzing ZIF-67 for detection of xylene

NASA Astrophysics Data System (ADS)

Bai, Shouli; Tian, Ke; Tian, Ye; Guo, Jun; Feng, Yongjun; Luo, Ruixian; Li, Dianqing; Chen, Aifan; Liu, Chung Chiun

2018-03-01

Co3O4/TiO2 composites with p-n heterojunction have been successfully prepared by pyrolyzing sacrificial template of Ti ion loaded Co-based Zeolitic imidazolate framework (ZIF-67). The structure and morphology of composite have been characterized by means of the analysis of XRD, FESEM, HRTEM and XPS spectra. The composite with a Co/Ti molar ratio of 4:1 exhibits the maximum sensing response of 6.17-50 ppm xylene, which is 5 times higher than pristine Co3O4. Moreover, Co3O4/TiO2 composite also shows good selectivity, long-term stability and rapid response and recovery. Such excellent sensing performances are attributed to material porous structure, high specific surface and the formation of abundant p-n heterojunction that permits the gas adsorption, diffusion and surface reaction and then improve the gas sensing performance. This work develops a promising synthesized approach of metal oxide composites for broader MOFs application in gas sensor field.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

Improvement on Timing Accuracy of LIDAR for Remote Sensing

NASA Astrophysics Data System (ADS)

Zhou, G.; Huang, W.; Zhou, X.; Huang, Y.; He, C.; Li, X.; Zhang, L.

2018-05-01

The traditional timing discrimination technique for laser rangefinding in remote sensing, which is lower in measurement performance and also has a larger error, has been unable to meet the high precision measurement and high definition lidar image. To solve this problem, an improvement of timing accuracy based on the improved leading-edge timing discrimination (LED) is proposed. Firstly, the method enables the corresponding timing point of the same threshold to move forward with the multiple amplifying of the received signal. Then, timing information is sampled, and fitted the timing points through algorithms in MATLAB software. Finally, the minimum timing error is calculated by the fitting function. Thereby, the timing error of the received signal from the lidar is compressed and the lidar data quality is improved. Experiments show that timing error can be significantly reduced by the multiple amplifying of the received signal and the algorithm of fitting the parameters, and a timing accuracy of 4.63 ps is achieved.

High-κ GdTixOy sensing membrane-based electrolyte-insulator-semiconductor with magnetic nanoparticles as enzyme carriers for protein contamination-free glucose biosensing.

PubMed

Wu, Min-Hsien; Yang, Hung-Wei; Hua, Mu-Yi; Peng, Yen-Bo; Pan, Tung-Ming

2013-09-15

This paper reports an electrolyte-insulator-semiconductor (EIS) device featuring a novel high-κ GdTixOy sensing membrane for high-performance pH sensing and glucose biosensing. The effect of the annealing temperature (700, 800, or 900°C) on the sensing properties of the GdTixOy membranes was investigated. The GdTixOy EIS device annealed at 900°C exhibited the greatest pH sensing performance, including the highest sensitivity (62.12mV/pH), the smallest hysteresis voltage (5mV), and the lowest drift rate (0.4mV/h), presumably because of its well-crystallized GdTixOy structure. To overcome the problems typically encountered during the practical application of biosensors (e.g., protein adsorption; preservation of enzymatic activity), we employed Fe3O4-based magnetic nanoparticles (MNPs) as enzyme carriers. The adsorption of serum protein on the unmodified sensing membrane led to poor EIS-based pH sensing (r(2)=0.71); the performance was greatly improved, however, after attaching the MNPs to the sensing membrane, thereby blocking protein adsorption significantly (by 98%) and allowing excellent pH sensing (r(2)=0.99). Moreover, we prepared a hybrid configuration of the proposed GdTixOy membrane-EIS, with magnetically attached glucose oxidase-immobilized MNPs, for glucose biosensing. The use of MNPs as enzyme carriers effectively preserved the enzymatic activity of glucose oxidase, with 45.3% of the original enzymatic activity retained after 120h of storage at 4°C (compared with complete loss of the free enzyme's activity under the same storage conditions). In addition, the proposed biosensor exhibited superior detection sensitivity of 11.03mV/mM relative to that (8.17mV/mM) obtained using the conventional enzyme immobilization method. Finally, we established the accuracy of the proposed method for blood glucose measurement; gratifyingly, blood glucose detection was comparable with the high-sensitivity glucose quantification obtained using a commercial glucose assay kit. Copyright © 2013 Elsevier B.V. All rights reserved.

Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy

PubMed Central

Alexopoulou, Dimitra; Andreopoulos, Bill; Dietze, Heiko; Doms, Andreas; Gandon, Fabien; Hakenberg, Jörg; Khelif, Khaled; Schroeder, Michael; Wächter, Thomas

2009-01-01

Background Ontology term labels can be ambiguous and have multiple senses. While this is no problem for human annotators, it is a challenge to automated methods, which identify ontology terms in text. Classical approaches to word sense disambiguation use co-occurring words or terms. However, most treat ontologies as simple terminologies, without making use of the ontology structure or the semantic similarity between terms. Another useful source of information for disambiguation are metadata. Here, we systematically compare three approaches to word sense disambiguation, which use ontologies and metadata, respectively. Results The 'Closest Sense' method assumes that the ontology defines multiple senses of the term. It computes the shortest path of co-occurring terms in the document to one of these senses. The 'Term Cooc' method defines a log-odds ratio for co-occurring terms including co-occurrences inferred from the ontology structure. The 'MetaData' approach trains a classifier on metadata. It does not require any ontology, but requires training data, which the other methods do not. To evaluate these approaches we defined a manually curated training corpus of 2600 documents for seven ambiguous terms from the Gene Ontology and MeSH. All approaches over all conditions achieve 80% success rate on average. The 'MetaData' approach performed best with 96%, when trained on high-quality data. Its performance deteriorates as quality of the training data decreases. The 'Term Cooc' approach performs better on Gene Ontology (92% success) than on MeSH (73% success) as MeSH is not a strict is-a/part-of, but rather a loose is-related-to hierarchy. The 'Closest Sense' approach achieves on average 80% success rate. Conclusion Metadata is valuable for disambiguation, but requires high quality training data. Closest Sense requires no training, but a large, consistently modelled ontology, which are two opposing conditions. Term Cooc achieves greater 90% success given a consistently modelled ontology. Overall, the results show that well structured ontologies can play a very important role to improve disambiguation. Availability The three benchmark datasets created for the purpose of disambiguation are available in Additional file 1. PMID:19159460

The added value of remote sensing products in constraining hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

2017-04-01

The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

Improving the position control of a two degrees of freedom robotic sensing antenna using fractional-order controllers

NASA Astrophysics Data System (ADS)

Feliu-Talegon, D.; Feliu-Batlle, V.

2017-06-01

Flexible links combined with force and torque sensors can be used to detect obstacles in mobile robotics, as well as for surface and object recognition. These devices, called sensing antennae, perform an active sensing strategy in which a servomotor system moves the link back and forth until it hits an object. At this instant, information of the motor angles combined with force and torque measurements allow calculating the positions of the hitting points, which are valuable information about the object surface. In order to move the antenna fast and accurately, this article proposes a new closed-loop control for driving this flexible link-based sensor. The control strategy is based on combining a feedforward term and a feedback phase-lag compensator of fractional order. We demonstrate that some drawbacks of the control of these sensing devices like the apparition of spillover effects when a very fast positioning of the antenna tip is desired, and actuator saturation caused by high-frequency sensor noise, can be significantly reduced by using our newly proposed fractional-order controllers. We have applied these controllers to the position control of a prototype of sensing antenna and experiments have shown the improvements attained with this technique in the accurate and vibration free motion of its tip (the fractional-order controller reduced ten times the residual vibration obtained with the integer-order controller).

Equity Sensitivity in Illinois Public School Teachers

ERIC Educational Resources Information Center

Grossi, Robert G.

2013-01-01

Research supports the importance of teacher quality on effective student learning. School districts recognize this fact and focus extensively on hiring quality teachers and improving teaching skills through professional development programs. Amazingly, despite common sense and a vast amount of research that reflects that employee performance is a…

Smart Sensing and Dynamic Fitting for Enhanced Comfort and Performance of Prosthetics

DTIC Science & Technology

2017-10-01

studying microstrip resonators for bio- impedance measurement. For actuation, we have 1) improved and de -bugged the prosthetic interface control ...studying microstrip resonators for bio‐impedance measurement. For actuation, we have 1) improved and de -bugged the prosthetic interface control ...shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

Research on dynamic performance design of mobile phone application based on context awareness

NASA Astrophysics Data System (ADS)

Bo, Zhang

2018-05-01

It aims to explore the dynamic performance of different mobile phone applications and the user's cognitive differences, reduce the cognitive burden, and enhance the sense of experience. By analyzing the dynamic design performance in four different interactive contexts, and constructing the framework of information service process in the interactive context perception and the two perception principles of the cognitive consensus between designer and user, and the two kinds of knowledge in accordance with the perception principles. The analysis of the context will help users sense the dynamic performance more intuitively, so that the details of interaction will be performed more vividly and smoothly, thus enhance user's experience in the interactive process. The common perception experience enables designers and users to produce emotional resonance in different interactive contexts, and help them achieve rapid understanding of interactive content and perceive the logic and hierarchy of the content and the structure, therefore the effectiveness of mobile applications will be improved.

Effects of annealing temperature on the H2-sensing properties of Pd-decorated WO3 nanorods

NASA Astrophysics Data System (ADS)

Lee, Sangmin; Lee, Woo Seok; Lee, Jae Kyung; Hyun, Soong Keun; Lee, Chongmu; Choi, Seungbok

2018-03-01

The temperature of the post-annealing treatment carried out after noble metal deposition onto semiconducting metal oxides (SMOs) must be carefully optimized to maximize the sensing performance of the metal-decorated SMO sensors. WO3 nanorods were synthesized by thermal evaporation of WO3 powders and decorated with Pd nanoparticles using a sol-gel method, followed by an annealing process. The effects of the annealing temperature on the hydrogen gas-sensing properties of the Pd-decorated WO3 nanorods were then examined; the optimal annealing temperature, leading to the highest response of the WO3 nanorod sensor to H2, was determined to be 600 °C. Post-annealing at 600 °C resulted in nanorods with the highest surface area-to-volume ratio, as well as in the optimal size and the largest number of deposited Pd nanoparticles, leading to the highest response and the shortest response/recovery times toward H2. The improved H2-sensing performance of the Pd-decorated WO3 nanorod sensor, compared to a sensor based on pristine WO3 nanorods, is attributed to the enhanced catalytic activity, increased surface area-to-volume ratio, and higher amounts of surface defects.

Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques

NASA Technical Reports Server (NTRS)

Malila, W. A.; Hieber, R. H.; Sarno, J. E.

1974-01-01

Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

NASA Astrophysics Data System (ADS)

Lee, Hyunki; Kim, Min Young; Moon, Jeon Il

2017-12-01

Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

pH and Protein Sensing with Functionalized Semiconducting Oxide Nanobelt FETs

NASA Astrophysics Data System (ADS)

Cheng, Yi; Yun, C. S.; Strouse, G. F.; Xiong, P.; Yang, R. S.; Wang, Z. L.

2008-03-01

We report solution pH sensing and selective protein detection with high-performance channel-limited field-effect transistors (FETs) based on single semiconducting oxide (ZnO and SnO2) nanobelts^1. The devices were integrated with PDMS microfluidic channels for analyte delivery and the source/drain contacts were passivated for in-solution sensing. pH sensing experiments were performed on FETs with functionalized and unmodified nanobelts. Functionalization of the nanobelts by APTES was found to greatly improve the pH sensitivity. The change in nanobelt conductance as functions of pH values at different gate voltages and ionic strengths showed high sensitivity and consistency. For the protein detection, we achieved highly selective biotinylation of the nanobelt channel with through APTES linkage. The specific binding of fluorescently-tagged streptavidin to the biotinylated nanobelt was verified by fluorescence microscopy; non-specific binding to the substrate was largely eliminated using PEG-silane passivation. The electrical responses of the biotinylated FETs to the streptavidin binding in PBS buffers of different pH values were systematically measured. The results will be presented and discussed. ^1Y. Cheng et al., Appl. Phys. Lett. 89, 093114 (2006). *Supported by NSF NIRT Grant ECS-0210332.

Time response for sensor sensed to actuator response for mobile robotic system

NASA Astrophysics Data System (ADS)

Amir, N. S.; Shafie, A. A.

2017-11-01

Time and performance of a mobile robot are very important in completing the tasks given to achieve its ultimate goal. Tasks may need to be done within a time constraint to ensure smooth operation of a mobile robot and can result in better performance. The main purpose of this research was to improve the performance of a mobile robot so that it can complete the tasks given within time constraint. The problem that is needed to be solved is to minimize the time interval between sensor detection and actuator response. The research objective is to analyse the real time operating system performance of sensors and actuators on one microcontroller and on two microcontroller for a mobile robot. The task for a mobile robot for this research is line following with an obstacle avoidance. Three runs will be carried out for the task and the time between the sensors senses to the actuator responses were recorded. Overall, the results show that two microcontroller system have better response time compared to the one microcontroller system. For this research, the average difference of response time is very important to improve the internal performance between the occurrence of a task, sensors detection, decision making and actuator response of a mobile robot. This research helped to develop a mobile robot with a better performance and can complete task within the time constraint.

The Enhanced Formaldehyde-Sensing Properties of P3HT-ZnO Hybrid Thin Film OTFT Sensor and Further Insight into Its Stability

PubMed Central

Tai, Huiling; Li, Xian; Jiang, Yadong; Xie, Guangzhong; Du, Xiaosong

2015-01-01

A thin-film transistor (TFT) having an organic–inorganic hybrid thin film combines the advantage of TFT sensors and the enhanced sensing performance of hybrid materials. In this work, poly(3-hexylthiophene) (P3HT)-zinc oxide (ZnO) nanoparticles' hybrid thin film was fabricated by a spraying process as the active layer of TFT for the employment of a room temperature operated formaldehyde (HCHO) gas sensor. The effects of ZnO nanoparticles on morphological and compositional features, electronic and HCHO-sensing properties of P3HT-ZnO thin film were systematically investigated. The results showed that P3HT-ZnO hybrid thin film sensor exhibited considerable improvement of sensing response (more than two times) and reversibility compared to the pristine P3HT film sensor. An accumulation p-n heterojunction mechanism model was developed to understand the mechanism of enhanced sensing properties by incorporation of ZnO nanoparticles. X-ray photoelectron spectroscope (XPS) and atomic force microscopy (AFM) characterizations were used to investigate the stability of the sensor in-depth, which reveals the performance deterioration was due to the changes of element composition and the chemical state of hybrid thin film surface induced by light and oxygen. Our study demonstrated that P3HT-ZnO hybrid thin film TFT sensor is beneficial in the advancement of novel room temperature HCHO sensing technology. PMID:25608214

The enhanced formaldehyde-sensing properties of P3HT-ZnO hybrid thin film OTFT sensor and further insight into its stability.

PubMed

Tai, Huiling; Li, Xian; Jiang, Yadong; Xie, Guangzhong; Du, Xiaosong

2015-01-19

A thin-film transistor (TFT) having an organic-inorganic hybrid thin film combines the advantage of TFT sensors and the enhanced sensing performance of hybrid materials. In this work, poly(3-hexylthiophene) (P3HT)-zinc oxide (ZnO) nanoparticles' hybrid thin film was fabricated by a spraying process as the active layer of TFT for the employment of a room temperature operated formaldehyde (HCHO) gas sensor. The effects of ZnO nanoparticles on morphological and compositional features, electronic and HCHO-sensing properties of P3HT-ZnO thin film were systematically investigated. The results showed that P3HT-ZnO hybrid thin film sensor exhibited considerable improvement of sensing response (more than two times) and reversibility compared to the pristine P3HT film sensor. An accumulation p-n heterojunction mechanism model was developed to understand the mechanism of enhanced sensing properties by incorporation of ZnO nanoparticles. X-ray photoelectron spectroscope (XPS) and atomic force microscopy (AFM) characterizations were used to investigate the stability of the sensor in-depth, which reveals the performance deterioration was due to the changes of element composition and the chemical state of hybrid thin film surface induced by light and oxygen. Our study demonstrated that P3HT-ZnO hybrid thin film TFT sensor is beneficial in the advancement of novel room temperature HCHO sensing technology.

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

PubMed Central

Jia, Ruoxi; Jin, Ming; Zou, Han; Yesilata, Yigitcan; Xie, Lihua; Spanos, Costas

2016-01-01

Estimating an occupant’s location is arguably the most fundamental sensing task in smart buildings. The applications for fine-grained, responsive building operations require the location sensing systems to provide location estimates in real time, also known as indoor tracking. Existing indoor tracking systems require occupants to carry specialized devices or install programs on their smartphone to collect inertial sensing data. In this paper, we propose MapSentinel, which performs non-intrusive location sensing based on WiFi access points and ultrasonic sensors. MapSentinel combines the noisy sensor readings with the floormap information to estimate locations. One key observation supporting our work is that occupants exhibit distinctive motion characteristics at different locations on the floormap, e.g., constrained motion along the corridor or in the cubicle zones, and free movement in the open space. While extensive research has been performed on using a floormap as a tool to obtain correct walking trajectories without wall-crossings, there have been few attempts to incorporate the knowledge of space use available from the floormap into the location estimation. This paper argues that the knowledge of space use as an additional information source presents new opportunities for indoor tracking. The fusion of heterogeneous information is theoretically formulated within the Factor Graph framework, and the Context-Augmented Particle Filtering algorithm is developed to efficiently solve real-time walking trajectories. Our evaluation in a large office space shows that the MapSentinel can achieve accuracy improvement of 31.3% compared with the purely WiFi-based tracking system. PMID:27049387

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

PubMed

Jia, Ruoxi; Jin, Ming; Zou, Han; Yesilata, Yigitcan; Xie, Lihua; Spanos, Costas

2016-04-02

Estimating an occupant's location is arguably the most fundamental sensing task in smart buildings. The applications for fine-grained, responsive building operations require the location sensing systems to provide location estimates in real time, also known as indoor tracking. Existing indoor tracking systems require occupants to carry specialized devices or install programs on their smartphone to collect inertial sensing data. In this paper, we propose MapSentinel, which performs non-intrusive location sensing based on WiFi access points and ultrasonic sensors. MapSentinel combines the noisy sensor readings with the floormap information to estimate locations. One key observation supporting our work is that occupants exhibit distinctive motion characteristics at different locations on the floormap, e.g., constrained motion along the corridor or in the cubicle zones, and free movement in the open space. While extensive research has been performed on using a floormap as a tool to obtain correct walking trajectories without wall-crossings, there have been few attempts to incorporate the knowledge of space use available from the floormap into the location estimation. This paper argues that the knowledge of space use as an additional information source presents new opportunities for indoor tracking. The fusion of heterogeneous information is theoretically formulated within the Factor Graph framework, and the Context-Augmented Particle Filtering algorithm is developed to efficiently solve real-time walking trajectories. Our evaluation in a large office space shows that the MapSentinel can achieve accuracy improvement of 31.3% compared with the purely WiFi-based tracking system.

Compressed Sensing for Body MRI

PubMed Central

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh

2016-01-01

The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities. PMID:27981664

Developing improved silica materials and devices for integrated optics applications

NASA Astrophysics Data System (ADS)

Maker, Ashley Julia

Due to their favorable optical and material properties, silica-based materials and devices have found many important applications throughout science and engineering, especially in sensing, communications, lasers, and integrated optics. Often, silica's properties ultimately limit the performance of these applications. To address this limitation, this thesis investigates the development of improved silica materials and optical devices, including silica films, coatings, waveguides, resonators, lasers, and sensors. Using sol-gel chemistry and microfabrication procedures, custom silica materials and devices are developed to benefit many applications. In this thesis, it is first demonstrated how the low optical loss of silica enables fabrication of low loss integrated waveguides and toroidal resonators with ultra-high quality factors. Then, by adding various rare earth and metal dopants to sol-gel silica, hybrid silica materials and devices are made with custom properties such as high refractive index and lasing capabilities. Finally, several applications are demonstrated, including the use of high refractive index coatings to control the behavior of light, development of Raman and ultra-low threshold rare earth microlasers, and a heterodyned microlaser sensor with significantly improved sensing performance. Future applications and directions of this research are also discussed.

Sensory feedback by peripheral nerve stimulation improves task performance in individuals with upper limb loss using a myoelectric prosthesis.

PubMed

Schiefer, Matthew; Tan, Daniel; Sidek, Steven M; Tyler, Dustin J

2016-02-01

Tactile feedback is critical to grip and object manipulation. Its absence results in reliance on visual and auditory cues. Our objective was to assess the effect of sensory feedback on task performance in individuals with limb loss. Stimulation of the peripheral nerves using implanted cuff electrodes provided two subjects with sensory feedback with intensity proportional to forces on the thumb, index, and middle fingers of their prosthetic hand during object manipulation. Both subjects perceived the sensation on their phantom hand at locations corresponding to the locations of the forces on the prosthetic hand. A bend sensor measured prosthetic hand span. Hand span modulated the intensity of sensory feedback perceived on the thenar eminence for subject 1 and the middle finger for subject 2. We performed three functional tests with the blindfolded subjects. First, the subject tried to determine whether or not a wooden block had been placed in his prosthetic hand. Second, the subject had to locate and remove magnetic blocks from a metal table. Third, the subject performed the Southampton Hand Assessment Procedure (SHAP). We also measured the subject's sense of embodiment with a survey and his self-confidence. Blindfolded performance with sensory feedback was similar to sighted performance in the wooden block and magnetic block tasks. Performance on the SHAP, a measure of hand mechanical function and control, was similar with and without sensory feedback. An embodiment survey showed an improved sense of integration of the prosthesis in self body image with sensory feedback. Sensory feedback by peripheral nerve stimulation improved object discrimination and manipulation, embodiment, and confidence. With both forms of feedback, the blindfolded subjects tended toward results obtained with visual feedback.

Tuning Fluorescence Direction with Plasmonic Metal–Dielectric– Metal Substrates

PubMed Central

Choudhury, Sharmistha Dutta; Badugu, Ramachandram; Nowaczyk, Kazimierz; Ray, Krishanu; Lakowicz, Joseph R.

2013-01-01

Controlling the emission properties of fluorophores is essential for improving the performance of fluorescence-based techniques in modern biochemical research, medical diagnosis, and sensing. Fluorescence emission is isotropic in nature, which makes it difficult to capture more than a small fraction of the total emission. Metal– dielectric–metal (MDM) substrates, discussed in this Letter, convert isotropic fluorescence into beaming emission normal to the substrate. This improves fluorescence collection efficiency and also opens up new avenues for a wide range of fluorescence-based applications. We suggest that MDM substrates can be readily adapted for multiple uses, such as in microarray formats, for directional fluorescence studies of multiple probes or for molecule-specific sensing with a high degree of spatial control over the fluorescence emission. SECTION: Physical Processes in Nanomaterials and Nanostructures PMID:24013521

Ethanol gas sensing performance of high-dimensional fuzz metal oxide nanostructure

NASA Astrophysics Data System (ADS)

Ibano, Kenzo; Kimura, Yoshihiro; Sugahara, Tohru; Lee, Heun Tae; Ueda, Yoshio

2018-04-01

Gas sensing ability of the He plasma induced fiber-like nanostructure, so-called fuzz structure, was firstly examined. A thin Mo layer deposited on a quartz surface was irradiated by He plasma to form the fuzz structure and oxidized by annealing in a quartz furnace. Electric conductivity of the fuzz Mo oxide layer was then measured through the Au electrodes deposited on the layer. Changes in electric conductivity by C2H5OH gas flow were examined as a function of temperature from 200 to 400 °C. Improved sensitivities were observed for the specimens after a fuzz nanostructure formation. However, the sensor developed in this study showed lower sensitivities than previously reported MoO3 nano-rod sensor, further optimization of oxidation is needed to improve the sensitivity.

The effect of loading carbon nanotubes onto chitosan films on electrochemical dopamine sensing in the presence of biological interference.

PubMed

Shukla, Sudheesh K; Lavon, Avia; Shmulevich, Offir; Ben-Yoav, Hadar

2018-05-01

In vivo monitoring of the neurotransmitter dopamine can potentially improve the diagnosis of neurological disorders and elucidate their underlying biochemical mechanisms. While electrochemical sensors can detect unlabeled dopamine molecules, their sensing performance is dramatically reduced by electrochemical currents generated by other, interfering molecules (e.g., uric acid) in the biological environment. To overcome this caveat, the surface of the sensor is often modified with electrocatalytic materials, which are encapsulated inside a polymeric film; however, the effect of the encapsulating film on the sensing performance of the electrode has not been systematically studied. This study characterizes the effect of loading carbon nanotubes (CNTs) onto a chitosan film on the electrochemical sensing performance of dopamine in the presence of uric acid. Higher CNT loading increases the diffusion and electron transfer rate coefficients of the sensor and, in the presence of uric acid, provides better sensitivity (3.00µALµmol -1 for 1.75% CNT loading, vs 0.01µALµmol -1 for 1% loading) but a poorer limit-of-detection (2.00µmolL -1 vs 1.00, respectively), as reported here for the first time. These findings can help optimize the sensitivity and the limit-of-detection of electrochemical sensors in complex biofluids to enable an in vivo monitoring of dopamine and other redox-active molecules. Copyright © 2017 Elsevier B.V. All rights reserved.

Low-temperature and highly enhanced NO2 sensing performance of Au-functionalized WO3 microspheres with a hierarchical nanostructure

NASA Astrophysics Data System (ADS)

Shen, Yanbai; Bi, Hongshan; Li, Tingting; Zhong, Xiangxi; Chen, Xiangxiang; Fan, Anfeng; Wei, Dezhou

2018-03-01

Hierarchically nanostructured WO3 microspheres that had two types of Au functionalization modes (i.e., Au-loaded mode and Au-doped mode) were characterized in terms of their microstructure and NO2 sensing performance. Pure, Au-loaded, and Au-doped WO3 microspheres were synthesized using a hydrothermal method, followed by a dipping method for Au-loaded WO3 microspheres. Microstructure characterization indicated that uniform microspheres with 3-6 μm in diameter were assembled from numerous well-defined individual WO3 nanorods with a single crystal hexagonal structure. The morphology and size of the WO3 microspheres were not affected by the functionalization of the Au nanoparticles, and the W, O, and Au elements were well-distributed in the WO3 microspheres. The NO2 sensing properties indicated that the Au nanoparticles not only improved the sensor response and reproducibility but also decreased the operating temperature at which the sensor response reached a maximum. Gas sensors based on pure, Au-loaded, and Au-doped WO3 microspheres exhibited a linear relationship between the sensor response and NO2 concentration. The sensing performance was significantly enhanced in the following order: pure, Au-loaded, and Au-doped WO3 microspheres. This result is due to the modulation of the depletion layer via oxygen adsorption as well as chemical and electronic sensitization of Au nanoparticles.

Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes

NASA Technical Reports Server (NTRS)

Spechler, Joshua A.; Hoppe, Daniel J.; Sigrist, Norbert; Shi, Fang; Seo, Byoung-Joon; Bikkannavar, Siddarayappa A.

2013-01-01

Segment mirror phasing, a critical step of segment mirror alignment, requires the ability to sense and correct the relative pistons between segments from up to a few hundred microns to a fraction of wavelength in order to bring the mirror system to its full diffraction capability. When sampling the aperture of a telescope, using auto-collimating flats (ACFs) is more economical. The performance of a telescope with a segmented primary mirror strongly depends on how well those primary mirror segments can be phased. One such process to phase primary mirror segments in the axial piston direction is dispersed fringe sensing (DFS). DFS technology can be used to co-phase the ACFs. DFS is essentially a signal fitting and processing operation. It is an elegant method of coarse phasing segmented mirrors. DFS performance accuracy is dependent upon careful calibration of the system as well as other factors such as internal optical alignment, system wavefront errors, and detector quality. Novel improvements to the algorithm have led to substantial enhancements in DFS performance. The Advanced Dispersed Fringe Sensing (ADFS) Algorithm is designed to reduce the sensitivity to calibration errors by determining the optimal fringe extraction line. Applying an angular extraction line dithering procedure and combining this dithering process with an error function while minimizing the phase term of the fitted signal, defines in essence the ADFS algorithm.

Through-Layer Buckle Wavelength-Gradient Design for the Coupling of High Sensitivity and Stretchability in a Single Strain Sensor.

PubMed

He, Tengyu; Lin, Chucheng; Shi, Liangjing; Wang, Ranran; Sun, Jing

2018-03-21

Recent years have witnessed a breathtaking development of wearable strain sensors. Coupling high sensitivity and stretchability in a strain sensor is greatly desired by emerging wearable applications but remains a big challenge. To tackle this issue, a through-layer buckle wavelength-gradient design is proposed and a facile and universal fabrication strategy is demonstrated to introduce such a gradient into the sensing film with multilayered sensing units. Following this strategy, strain sensors are fabricated using graphene woven fabrics (GWFs) as sensing units, which exhibit highly tunable electromechanical performances. Specifically, the sensor with 10-layer GWFs has a gauge factor (GF) of 2996 at a maximum strain of 242.74% and an average GF of 327. It also exhibits an extremely low minimum detection limit of 0.02% strain, a fast signal response of less than 90 ms, and a high cyclic durability through more than 10 000 cycling test. Such excellent performances qualify it in accurately monitoring full-range human activities, ranging from subtle stimuli (e.g., pulse, respiration, and voice recognition) to vigorous motions (finger bending, walking, jogging, and jumping). The combination of experimental observations and modeling study shows that the predesigned through-layer buckle wavelength gradient leads to a layer-by-layer crack propagation process, which accounts for the underlying working mechanism. Modeling study shows a great potential for further improvement of sensing performances by adjusting fabrication parameters such as layers of sensing units ( n) and step pre-strain (ε sp ). For one thing, when ε sp is fixed, the maximum sensing strain could be adjusted from >240% ( n = 10) to >450% ( n = 15) and >1200% ( n = 20). For the other, when n is fixed, the maximum sensing strain could be adjusted from >240% (ε sp = 13.2%) to >400% (ε sp = 18%) and >800% (ε sp = 25%).

Building Knowledge Structures by Testing Helps Children with Mathematical Learning Difficulty

ERIC Educational Resources Information Center

Zhang, Yiyun; Zhou, Xinlin

2016-01-01

Mathematical learning difficulty (MLD) is prevalent in the development of mathematical abilities. Previous interventions for children with MLD have focused on number sense or basic mathematical skills. This study investigated whether mathematical performance of fifth grade children with MLD could be improved by developing knowledge structures by…

Health Wise

ERIC Educational Resources Information Center

Holland, Jim

2009-01-01

Good indoor environmental quality (IEQ) is an important component for improving the productivity of students, teachers and support staff. It is crucial for a sense of health and well-being. The overall IEQ has a significant influence on student attendance and performance. Studies have shown that poor indoor air quality results in more illness,…

Improving canopy sensor algorithms with soil and weather information

USDA-ARS?s Scientific Manuscript database

Nitrogen (N) need to support corn (Zea mays L.) production can be highly variable within fields. Canopy reflectance sensing for assessing crop N health has been implemented on many farmers’ fields to side-dress or top-dress variable-rate N application, but at times farmers report the performance of ...

Improvement of signal to noise ratio of time domain mutliplexing fiber Bragg grating sensor network with Golay complementary codes

NASA Astrophysics Data System (ADS)

Elgaud, M. M.; Zan, M. S. D.; Abushagur, A. G.; Bakar, A. Ashrif A.

2017-07-01

This paper reports the employment of autocorrelation properties of Golay complementary codes (GCC) to enhance the performance of the time domain multiplexing fiber Bragg grating (TDM-FBG) sensing network. By encoding the light from laser with a stream of non-return-to-zero (NRZ) form of GCC and launching it into the sensing area that consists of the FBG sensors, we have found that the FBG signals can be decoded correctly with the autocorrelation calculations, confirming the successful demonstration of coded TDM-FBG sensor network. OptiGrating and OptiSystem simulators were used to design customized FBG sensors and perform the coded TDM-FBG sensor simulations, respectively. Results have substantiated the theoretical dependence of SNR enhancement on the code length of GCC, where the maximum SNR improvement of about 9 dB is achievable with the use of 256 bits of GCC compared to that of 4 bits case. Furthermore, the GCC has also extended the strain exposure up to 30% higher compared to the maximum of the conventional single pulse case. The employment of GCC in the TDM-FBG sensor system provides overall performance enhancement over the conventional single pulse case, under the same conditions.

The influence of performance on action-effect integration in sense of agency.

PubMed

Wen, Wen; Yamashita, Atsushi; Asama, Hajime

2017-08-01

Sense of agency refers to the subjective feeling of being able to control an outcome through one's own actions or will. Prior studies have shown that both sensory processing (e.g., comparisons between sensory feedbacks and predictions basing on one's motor intentions) and high-level cognitive/constructive processes (e.g., inferences based on one's performance or the consequences of one's actions) contribute to judgments of sense of agency. However, it remains unclear how these two types of processes interact, which is important for clarifying the mechanisms underlying sense of agency. Thus, we examined whether performance-based inferences influence action-effect integration in sense of agency using a delay detection paradigm in two experiments. In both experiments, participants pressed left and right arrow keys to control the direction in which a moving dot was travelling. The dot's response delay was manipulated randomly on 7 levels (0-480ms) between the trials; for each trial, participants were asked to judge whether the dot response was delayed and to rate their level of agency over the dot. In Experiment 1, participants tried to direct the dot to reach a destination on the screen as quickly as possible. Furthermore, the computer assisted participants by ignoring erroneous commands for half of the trials (assisted condition), while in the other half, all of the participants' commands were executed (self-control condition). In Experiment 2, participants directed the dot as they pleased (without a specific goal), but, in half of the trials, the computer randomly ignored 32% of their commands (disturbed condition) rather than assisted them. The results from the two experiments showed that performance enhanced action-effect integration. Specifically, when task performance was improved through the computer's assistance in Experiment 1, delay detection was reduced in the 480-ms delay condition, despite the fact that 32% of participants' commands were ignored. Conversely, when no feedback on task performance was given (as in Experiment 2), the participants reported greater delay when some of their commands were randomly ignored. Furthermore, the results of a logistic regression analysis showed that the threshold of delay detection was greater in the assisted condition than in the self-control condition in Experiment 1, which suggests a wider time window for action-effect integration. A multivariate analysis also revealed that assistance was related to reduced delay detection via task performance, while reduced delay detection was directly correlated with a better sense of agency. These results indicate an association between the implicit and explicit aspects of sense of agency. Copyright © 2017 Elsevier Inc. All rights reserved.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

Multi-applicative tetragonal TiO2/SnO2 nanocomposites for photocatalysis and gas sensing

NASA Astrophysics Data System (ADS)

Patil, S. M.; Dhodamani, A. G.; Vanalakar, S. A.; Deshmukh, S. P.; Delekar, S. D.

2018-04-01

TiO2-based mixed metal oxide heteronanostructures have multiple applications in photocatalysis and gas sensing because of their charge transport properties. In this study, we prepared tetragonal TiO2/SnO2 nanocomposites (NCs) with different weight percentages using a simple wet impregnation method. The physicochemical properties of the NCs were investigated using X-ray diffraction, Fourier transform-infrared spectroscopy, ultraviolet-visible spectroscopy, field-emission scanning electron microscopy, energy dispersive X-ray spectroscopy, transmission electron microscopy, and Brunauer-Emmett-Teller surface area analysis. The results showed that the surface area of the NCs increased significantly and the anatase TiO2 was sensitized after the addition of a small amount of cassiterite SnO2 NPs. We systematically studied the as-prepared NCs during the photocatalytic degradation of Congo Red dye under visible light irradiation (λ > 420 nm) and NH3 gas sensing, which demonstrated the efficient photocatalytic performance and the superior sensing response of the catalyst with a weight composition of 25% SnO2 in TiO2 (4:1) compared with the other NCs or the bare individual nanoparticles. The improved photocatalytic and gas sensing performance of the TiO2/SnO2 (4:1) NCs may be attributed to the increased active surface area, the increased adsorption of the dye and target gas molecules, as well as efficient electron-hole charge separation and transfer.

Ultra-short FBG based distributed sensing using shifted optical Gaussian filters and microwave-network analysis.

PubMed

Cheng, Rui; Xia, Li; Sima, Chaotan; Ran, Yanli; Rohollahnejad, Jalal; Zhou, Jiaao; Wen, Yongqiang; Yu, Can

2016-02-08

Ultrashort fiber Bragg gratings (US-FBGs) have significant potential as weak grating sensors for distributed sensing, but the exploitation have been limited by their inherent broad spectra that are undesirable for most traditional wavelength measurements. To address this, we have recently introduced a new interrogation concept using shifted optical Gaussian filters (SOGF) which is well suitable for US-FBG measurements. Here, we apply it to demonstrate, for the first time, an US-FBG-based self-referencing distributed optical sensing technique, with the advantages of adjustable sensitivity and range, high-speed and wide-range (potentially >14000 με) intensity-based detection, and resistance to disturbance by nonuniform parameter distribution. The entire system is essentially based on a microwave network, which incorporates the SOGF with a fiber delay-line between the two arms. Differential detections of the cascaded US-FBGs are performed individually in the network time-domain response which can be obtained by analyzing its complex frequency response. Experimental results are presented and discussed using eight cascaded US-FBGs. A comprehensive numerical analysis is also conducted to assess the system performance, which shows that the use of US-FBGs instead of conventional weak FBGs could significantly improve the power budget and capacity of the distributed sensing system while maintaining the crosstalk level and intensity decay rate, providing a promising route for future sensing applications.

Enhanced Dibutyl Phthalate Sensing Performance of a Quartz Crystal Microbalance Coated with Au-Decorated ZnO Porous Microspheres

PubMed Central

Zhang, Kaihuan; Fan, Guokang; Hu, Ruifen; Li, Guang

2015-01-01

Noble metals addition on nanostructured metal oxides is an attractive way to enhance gas sensing properties. Herein, hierarchical zinc oxide (ZnO) porous microspheres decorated with cubic gold particles (Au particles) were synthesized using a facile hydrothermal method. The as-prepared Au-decorated ZnO was then utilized as the sensing film of a gas sensor based on a quartz crystal microbalance (QCM). This fabricated sensor was applied to detect dibutyl phthalate (DBP), which is a widely used plasticizer, and its coating load was optimized. When tested at room temperature, the sensor exhibited a high sensitivity of 38.10 Hz/ppb to DBP in a low concentration range from 2 ppb to 30 ppb and the calculated theoretical detection limit is below 1 ppb. It maintains good repeatability as well as long-term stability. Compared with the undecorated ZnO based QCM, the Au-decorated one achieved a 1.62-time enhancement in sensitivity to DBP, and the selectivity was also improved. According to the experimental results, Au-functionalized ZnO porous microspheres displayed superior sensing performance towards DBP, indicating its potential use in monitoring plasticizers in the gaseous state. Moreover, Au decoration of porous metal oxide nanostructures is proved to be an effective approach for enhancing the gas sensing properties and the corresponding mechanism was investigated. PMID:26343661

Communication training improves sense of performance expectancy of public health nurses engaged in long-term elderly prevention care program.

PubMed

Tanabe, Motoko; Suzukamo, Yoshimi; Tsuji, Ichiro; Izumi, Sin-Ichi

2012-01-01

This study examines the effectiveness of a communication skill training based on a coaching theory for public health nurses (PHNs) who are engaged in Japan's long-term care prevention program. The participants in this study included 112 PHNs and 266 service users who met with these PHNs in order to create a customized care plan within one month after the PHNs' training. The participants were divided into three groups: a supervised group in which the PHNs attended the 1-day training seminar and the follow-up supervision; a seminar group attended only the 1-day training seminar; a control group. The PHNs' sense of performance expectancy, and user's satisfaction, user's spontaneous behavior were evaluated at the baseline (T1), at one month (T2), and at three months (T3) after the PHNs' training. At T3, the PHNs performed a recalled evaluation (RE) of their communication skills before the training. The PHNs' sense of performance expectancy increased significantly over time in the supervised group and the control group (F = 11.28, P < 0.001; F = 4.03, P < 0.05, resp.). The difference score between T3-RE was significantly higher in the supervised group than the control group (P < 0.01). No significant differences in the users' outcomes were found.

Evaluation of humidity sensing properties of TMBHPET thin film embedded with spinel cobalt ferrite nanoparticles

NASA Astrophysics Data System (ADS)

Zafar, Qayyum; Azmer, Mohamad Izzat; Al-Sehemi, Abdullah G.; Al-Assiri, Mohammad S.; Kalam, Abul; Sulaiman, Khaulah

2016-07-01

In this study, we report the enhanced sensing parameters of previously reported TMBHPET-based humidity sensor. Significant improved sensing performance has been demonstrated by coupling of TMBHPET moisture sensing thin film with cobalt ferrite nanoparticles (synthesized by eco-benign ultrasonic method). The mean size of CoFe2O4 nanoparticles has been estimated to be 6.5 nm. It is assumed that the thin film of organic-ceramic hybrid matrix (TMBHPET:CoFe2O4) is a potential candidate for humidity sensing utility by virtue of its high specific surface area and porous surface morphology (as evident from TEM, FESEM, and AFM images). The hybrid suspension has been drop-cast onto the glass substrate with preliminary deposited coplanar aluminum electrodes separated by 40 µm distance. The influence of humidity on the capacitance of the hybrid humidity sensor (Al/TMBHPET:CoFe2O4/Al) has been investigated at three different frequencies of the AC applied voltage ( V rms 1 V): 100 Hz, 1 kHz, and 10 kHz. It has been observed that at 100 Hz, under a humidity of 99 % RH, the capacitance of the sensor increased by 2.61 times, with respect to 30 % RH condition. The proposed sensor exhibits significantly improved sensitivity 560 fF/ % RH at 100 Hz, which is nearly 7.5 times as high as that of pristine TMBHPET-based humidity sensor. Further, the capacitive sensor exhibits improved dynamic range (30-99 % RH), small hysteresis ( 2.3 %), and relatively quicker response and recovery times ( 12 s, 14 s, respectively). It is assumed that the humidity response of the sensor is associated with the diffusion kinetics of water vapors and doping of the semiconductor nanocomposite by water molecules.

Thermal oxidation synthesis hollow MoO{sub 3} microspheres and their applications in lithium storage and gas-sensing

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

Zhao, Xinyu; School of Petrochemical Engineering, Shenyang University of Technology, Liaoyang 111003; Cao, Minhua, E-mail: caomh@bit.edu.cn

2013-06-01

Graphical abstract: MoO{sub 3} hollow microspheres were synthesized via a facile and template-free solvothermal route and subsequent heat treatment in air. The MoO{sub 3} hollow microspheres exhibit an improved lithium storage and gas-sensing performance. Highlights: ► Hollow MoO{sub 3} microspheres were synthesized by thermal oxidation of hollow MoO{sub 2}. ► The MoO{sub 3} hollow microspheres have a relatively high specific surface area. ► The MoO{sub 3} hollow microspheres exhibit improved lithium storage performance. ► The MoO{sub 3} hollow microspheres show good responses to ammonia gas. - Abstract: In this paper, MoO{sub 3} hollow microspheres were synthesized via a facile andmore » template-free solvothermal route and subsequent heat treatment in air. The MoO{sub 3} hollow microspheres have a relatively high specific surface area, and with such a feature, the as-synthesized MoO{sub 3} hollow microspheres have potential applications in Li-ion battery and gas-sensor. When tested as a Li-storage anode material, the MoO{sub 3} hollow microspheres show a higher discharge capacity of 1377.1 mA h g{sup −1} in the first discharge and a high reversible capacity of 780 mA h g{sup −1} after 100 cycles at a rate of 1 C. Furthermore, as a gas sensing material, the MoO{sub 3} hollow microspheres exhibit an improved sensitivity and short response/recovery time to trace levels of ammonia gas.« less

Effect of proprioception training on knee joint position sense in female team handball players.

PubMed

Pánics, G; Tállay, A; Pavlik, A; Berkes, I

2008-06-01

A number of studies have shown that proprioception training can reduce the risk of injuries in pivoting sports, but the mechanism is not clearly understood. To determine the contributing effects of propioception on knee joint position sense among team handball players. Prospective cohort study. Two professional female handball teams were followed prospectively for the 2005-6 season. 20 players in the intervention team followed a prescribed proprioceptive training programme while 19 players in the control team did not have a specific propioceptive training programme. The coaches recorded all exposures of the individual players. The location and nature of injuries were recorded. Joint position sense (JPS) was measured by a goniometer on both knees in three angle intervals, testing each angle five times. Assessments were performed before and after the season by the same examiner for both teams. In the intervention team a third assessment was also performed during the season. Complete data were obtained for 15 subjects in the intervention team and 16 in the control team. Absolute error score, error of variation score and SEM were calculated and the results of the intervention and control teams were compared. The proprioception sensory function of the players in the intervention team was significantly improved between the assessments made at the start and the end of the season (mean (SD) absolute error 9.78-8.21 degrees (7.19-6.08 degrees ) vs 3.61-4.04 degrees (3.71-3.20 degrees ), p<0.05). No improvement was seen in the sensory function in the control team between the start and the end of the season (mean (SD) absolute error 6.31-6.22 degrees (6.12-3.59 degrees ) vs 6.13-6.69 degrees (7.46-6.49 degrees ), p>0.05). This is the first study to show that proprioception training improves the joint position sense in elite female handball players. This may explain the effect of neuromuscular training in reducing the injury rate.

Sensor fusion approaches for EMI and GPR-based subsurface threat identification

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Despite advances in both electromagnetic induction (EMI) and ground penetrating radar (GPR) sensing and related signal processing, neither sensor alone provides a perfect tool for detecting the myriad of possible buried objects that threaten the lives of Soldiers and civilians. However, while neither GPR nor EMI sensing alone can provide optimal detection across all target types, the two approaches are highly complementary. As a result, many landmine systems seek to make use of both sensing modalities simultaneously and fuse the results from both sensors to improve detection performance for targets with widely varying metal content and GPR responses. Despite this, little work has focused on large-scale comparisons of different approaches to sensor fusion and machine learning for combining data from these highly orthogonal phenomenologies. In this work we explore a wide array of pattern recognition techniques for algorithm development and sensor fusion. Results with the ARA Nemesis landmine detection system suggest that nonlinear and non-parametric classification algorithms provide significant performance benefits for single-sensor algorithm development, and that fusion of multiple algorithms can be performed satisfactorily using basic parametric approaches, such as logistic discriminant classification, for the targets under consideration in our data sets.

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

Gpm Level 1 Science Requirements: Science and Performance Viewed from the Ground

NASA Technical Reports Server (NTRS)

Petersen, W.; Kirstetter, P.; Wolff, D.; Kidd, C.; Tokay, A.; Chandrasekar, V.; Grecu, M.; Huffman, G.; Jackson, G. S.

2016-01-01

GPM meets Level 1 science requirements for rain estimation based on the strong performance of its radar algorithms. Changes in the V5 GPROF algorithm should correct errors in V4 and will likely resolve GPROF performance issues relative to L1 requirements. L1 FOV Snow detection largely verified but at unknown SWE rate threshold (likely < 0.5 –1 mm/hr/liquid equivalent). Ongoing work to improve SWE rate estimation for both satellite and GV remote sensing.

Photoinduced Electron Transfer Based Ion Sensing within an Optical Fiber

PubMed Central

Englich, Florian V.; Foo, Tze Cheung; Richardson, Andrew C.; Ebendorff-Heidepriem, Heike; Sumby, Christopher J.; Monro, Tanya M.

2011-01-01

We combine suspended-core microstructured optical fibers with the photoinduced electron transfer (PET) effect to demonstrate a new type of fluorescent optical fiber-dip sensing platform for small volume ion detection. A sensor design based on a simple model PET-fluoroionophore system and small core microstructured optical fiber capable of detecting sodium ions is demonstrated. The performance of the dip sensor operating in a high sodium concentration regime (925 ppm Na+) and for lower sodium concentration environments (18.4 ppm Na+) is explored and future approaches to improving the sensor’s signal stability, sensitivity and selectivity are discussed. PMID:22163712

A New Mirroring Circuit for Power MOS Current Sensing Highly Immune to EMI

PubMed Central

Aiello, Orazio; Fiori, Franco

2013-01-01

This paper deals with the monitoring of power transistor current subjected to radio-frequency interference. In particular, a new current sensor with no connection to the power transistor drain and with improved performance with respect to the existing current-sensing schemes is presented. The operation of the above mentioned current sensor is discussed referring to time-domain computer simulations. The susceptibility of the proposed circuit to radio-frequency interference is evaluated through time-domain computer simulations and the results are compared with those obtained for a conventional integrated current sensor. PMID:23385408

Studies on Five Senses Treatment

NASA Astrophysics Data System (ADS)

Sato, Sadaka; Miao, Tiejun; Oyama-Higa, Mayumi

2011-06-01

This study proposed a therapy from complementary and alternative medicine to treat mental disorder by through interactions of five senses between therapist and patient. In this method sounding a certain six voices play an important role in healing and recovery. First, we studied effects of speaking using scalp- EEG measurement. Chaos analysis of EEG showed a largely enhanced largest Lyapunov exponent (LLE) during the speaking. In addition, EEG power spectrum showed an increase over most frequencies. Second, we performed case studies on mental disorder using the therapy. Running power spectrum of EEG of patients indicated decreasing power at end of treatment, implying five senses therapy induced relaxed and lowered energy in central neural system. The results agreed with patient's reports that there were considerable decline in anxiety and improvements in mood.

Surfactant modified SnO2 nanostructured thin film for improved sensing performance of LPG and ammonia

NASA Astrophysics Data System (ADS)

Kumari, K. Prasanna; Thomas, Boben

2017-05-01

SnO2 nanostructured thin films have been successfully synthesized by way of spray pyrolysis from surfactant added solution. The X-ray diffraction pattern discloses the tetragonal rutile phase of the deposited SnO2 films, which experience a grain size reduction from 35 nm to 19 nm, on the addition of PVP surfactant in precursor. Gas sensing investigations on the surfactant modified film show considerable LPG and NH3 response at a lower operating temperature of 150°C. Quick response (˜20s) and fast recovery (˜30s) are the main features of these sensors. The measurement of AC conductivity of the sample allows understanding the conduction mechanism and sensing action for to enhance the detection sensitivity greatly.

[New type distributed optical fiber temperature sensor (DTS) based on Raman scattering and its' application].

PubMed

Wang, Jian-Feng; Liu, Hong-Lin; Zhang, Shu-Qin; Yu, Xiang-Dong; Sun, Zhong-Zhou; Jin, Shang-Zhong; Zhang, Zai-Xuan

2013-04-01

Basic principles, development trends and applications status of distributed optical fiber Raman temperature sensor (DTS) are introduced. Performance parameters of DTS system include the sensing optical fiber length, temperature measurement uncertainty, spatial resolution and measurement time. These parameters have a certain correlation and it is difficult to improve them at the same time by single technology. So a variety of key techniques such as Raman amplification, pulse coding technique, Raman related dual-wavelength self-correction technique and embedding optical switching technique are researched to improve the performance of the DTS system. A 1 467 nm continuous laser is used as pump laser and the light source of DTS system (1 550 nm pulse laser) is amplified. When the length of sensing optical fiber is 50 km the Raman gain is about 17 dB. Raman gain can partially compensate the transmission loss of optical fiber, so that the sensing length can reach 50 km. In DTS system using pulse coding technique, pulse laser is coded by 211 bits loop encoder and correlation calculation is used to demodulate temperature. The encoded laser signal is related, whereas the noise is not relevant. So that signal-to-noise ratio (SNR) of DTS system can be improved significantly. The experiments are carried out in DTS system with single mode optical fiber and multimode optical fiber respectively. Temperature measurement uncertainty can all reach 1 degrees C. In DTS system using Raman related dual-wavelength self-correction technique, the wavelength difference of the two light sources must be one Raman frequency shift in optical fiber. For example, wavelength of the main laser is 1 550 nm and wavelength of the second laser must be 1 450 nm. Spatial resolution of DTS system is improved to 2 m by using dual-wavelength self-correction technique. Optical switch is embedded in DTS system, so that the temperature measurement channel multiply extended and the total length of the sensing optical fiber effectively extended. Optical fiber sensor network is composed.

Conducting Polymer-Based Nanohybrid Transducers: A Potential Route to High Sensitivity and Selectivity Sensors

PubMed Central

Park, Seon Joo; Kwon, Oh Seok; Lee, Ji Eun; Jang, Jyongsik; Yoon, Hyeonseok

2014-01-01

The development of novel sensing materials provides good opportunities to realize previously unachievable sensor performance. In this review, conducting polymer-based nanohybrids are highlighted as innovative transducers for high-performance chemical and biological sensing devices. Synthetic strategies of the nanohybrids are categorized into four groups: (1) impregnation, followed by reduction; (2) concurrent redox reactions; (3) electrochemical deposition; (4) seeding approach. Nanocale hybridization of conducting polymers with inorganic components can lead to improved sorption, catalytic reaction and/or transport behavior of the material systems. The nanohybrids have thus been used to detect nerve agents, toxic gases, volatile organic compounds, glucose, dopamine, and DNA. Given further advances in nanohybrids synthesis, it is expected that sensor technology will also evolve, especially in terms of sensitivity and selectivity. PMID:24561406

A model-based analysis of extinction ratio effects on phase-OTDR distributed acoustic sensing system performance

NASA Astrophysics Data System (ADS)

Aktas, Metin; Maral, Hakan; Akgun, Toygar

2018-02-01

Extinction ratio is an inherent limiting factor that has a direct effect on the detection performance of phase-OTDR based distributed acoustics sensing systems. In this work we present a model based analysis of Rayleigh scattering to simulate the effects of extinction ratio on the received signal under varying signal acquisition scenarios and system parameters. These signal acquisition scenarios are constructed to represent typically observed cases such as multiple vibration sources cluttered around the target vibration source to be detected, continuous wave light sources with center frequency drift, varying fiber optic cable lengths and varying ADC bit resolutions. Results show that an insufficient ER can result in high optical noise floor and effectively hide the effects of elaborate system improvement efforts.

Secure and Energy-Efficient Data Transmission System Based on Chaotic Compressive Sensing in Body-to-Body Networks.

PubMed

Peng, Haipeng; Tian, Ye; Kurths, Jurgen; Li, Lixiang; Yang, Yixian; Wang, Daoshun

2017-06-01

Applications of wireless body area networks (WBANs) are extended from remote health care to military, sports, disaster relief, etc. With the network scale expanding, nodes increasing, and links complicated, a WBAN evolves to a body-to-body network. Along with the development, energy saving and data security problems are highlighted. In this paper, chaotic compressive sensing (CCS) is proposed to solve these two crucial problems, simultaneously. Compared with the traditional compressive sensing, CCS can save vast storage space by only storing the matrix generation parameters. Additionally, the sensitivity of chaos can improve the security of data transmission. Aimed at image transmission, modified CCS is proposed, which uses two encryption mechanisms, confusion and mask, and performs a much better encryption quality. Simulation is conducted to verify the feasibility and effectiveness of the proposed methods. The results show that the energy efficiency and security are strongly improved, while the storage space is saved. And the secret key is extremely sensitive, [Formula: see text] perturbation of the secret key could lead to a total different decoding, the relative error is larger than 100%. Particularly for image encryption, the performance of the modified method is excellent. The adjacent pixel correlation is smaller than 0.04 in different directions including horizontal, vertical, and diagonal; the entropy of the cipher image with a 256-level gray value is larger than 7.98.

Integration and management of massive remote-sensing data based on GeoSOT subdivision model

NASA Astrophysics Data System (ADS)

Li, Shuang; Cheng, Chengqi; Chen, Bo; Meng, Li

2016-07-01

Owing to the rapid development of earth observation technology, the volume of spatial information is growing rapidly; therefore, improving query retrieval speed from large, rich data sources for remote-sensing data management systems is quite urgent. A global subdivision model, geographic coordinate subdivision grid with one-dimension integer coding on 2n-tree, which we propose as a solution, has been used in data management organizations. However, because a spatial object may cover several grids, ample data redundancy will occur when data are stored in relational databases. To solve this redundancy problem, we first combined the subdivision model with the spatial array database containing the inverted index. We proposed an improved approach for integrating and managing massive remote-sensing data. By adding a spatial code column in an array format in a database, spatial information in remote-sensing metadata can be stored and logically subdivided. We implemented our method in a Kingbase Enterprise Server database system and compared the results with the Oracle platform by simulating worldwide image data. Experimental results showed that our approach performed better than Oracle in terms of data integration and time and space efficiency. Our approach also offers an efficient storage management system for existing storage centers and management systems.

Construction of 1D SnO2-coated ZnO nanowire heterojunction for their improved n-butylamine sensing performances

NASA Astrophysics Data System (ADS)

Wang, Liwei; Li, Jintao; Wang, Yinghui; Yu, Kefu; Tang, Xingying; Zhang, Yuanyuan; Wang, Shaopeng; Wei, Chaoshuai

2016-10-01

One-dimensional (1D) SnO2-coated ZnO nanowire (SnO2/ZnO NW) N-N heterojunctions were successfully constructed by an effective solvothermal treatment followed with calcination at 400 °C. The obtained samples were characterized by means of XRD, SEM, TEM, Scanning TEM coupled with EDS and XPS analysis, which confirmed that the outer layers of N-type SnO2 nanoparticles (avg. 4 nm) were uniformly distributed onto our pre-synthesized n-type ZnO nanowire supports (diameter 80~100 nm, length 12~16 μm). Comparisons of the gas sensing performances among pure SnO2, pure ZnO NW and the as-fabricated SnO2/ZnO NW heterojunctions revealed that after modification, SnO2/ZnO NW based sensor exhibited remarkably improved response, fast response and recovery speeds, good selectivity and excellent reproducibility to n-butylamine gas, indicating it can be used as promising candidates for high-performance organic amine sensors. The enhanced gas-sensing behavior should be attributed to the unique 1D wire-like morphology of ZnO support, the small size effect of SnO2 nanoparticles, and the semiconductor depletion layer model induced by the strong interfacial interaction between SnO2 and ZnO of the heterojunctions. The as-prepared SnO2/ZnO NW heterojunctions may also supply other novel applications in the fields like photocatalysis, lithium-ion batteries, waste water purification, and so on.

Evaluation of a functional hand orthosis combined with electrical stimulation adjunct to arm-hand rehabilitation in subacute stroke patients with a severely to moderately affected hand function.

PubMed

Franck, Johan Anton; Smeets, Rob Johannes Elise Marie; Seelen, Henk Alexander Maria

2018-01-09

To investigate the usability and effectiveness of a functional hand orthosis, combined with electrical stimulation adjunct to therapy-as-usual, on functional use of the moderately/severely impaired hand in sub-acute stroke patients. Single case experiment (A-B-A'-design) involving eight sub-acute stroke patients. The functional hand orthosis and electrical stimulation were used for six weeks, four days/week, 45'/day. Action_Research_Arm_Test, Intrinsic_Motivation_Inventory. At group level, patients improved 19.2 points (median value) (interquartile range: [8.8, 29.5] points) on the Action_Research_Arm_Test (p = 0.001). After correcting for spontaneous recovery and/or therapy-as-usual effects Action_Research_Arm_Test scores still improved significantly (median: 17.2 points; interquartile range: [5.1, 29.2] points) (p = 0.002). At individual level, six patients had improved as to arm-hand skill performance at follow-up (p < = 0.010). In one patient, arm-hand skill performance improvement did not attain statistical significance. In another patient, no arm-hand skill performance improvement was observed. Average Intrinsic_Motivation_Inventory sub-scores were between 4.6 and 6.3 (maximum: 7), except for 'perceived pressure/tension' (3.3). Sub-acute stroke patients who display only little/modest improvement on their capacity to perform daily activities, seem to benefit from training with a dynamic arm orthosis in combination with electrical stimulation. Patients' perceived intrinsic motivation and sense of self-regulation was high. Implications for rehabilitation Arm-hand training featuring the dynamic hand orthosis in combination with electrical stimulation shows a shift from no dexterity to dexterity. As to the users' experience regarding the dynamic hand orthosis, patients perceive a high-intrinsic motivation and sense of self-regulation. Combining the orthosis with electrical stimulation creates opportunities for a nonfunctional hand towards task-oriented training.

Design and Field Experimentation of a Cooperative ITS Architecture Based on Distributed RSUs.

PubMed

Moreno, Asier; Osaba, Eneko; Onieva, Enrique; Perallos, Asier; Iovino, Giovanni; Fernández, Pablo

2016-07-22

This paper describes a new cooperative Intelligent Transportation System architecture that aims to enable collaborative sensing services. The main goal of this architecture is to improve transportation efficiency and performance. The system, which has been proven within the participation in the ICSI (Intelligent Cooperative Sensing for Improved traffic efficiency) European project, encompasses the entire process of capture and management of available road data. For this purpose, it applies a combination of cooperative services and methods for data sensing, acquisition, processing and communication amongst road users, vehicles, infrastructures and related stakeholders. Additionally, the advantages of using the proposed system are exposed. The most important of these advantages is the use of a distributed architecture, moving the system intelligence from the control centre to the peripheral devices. The global architecture of the system is presented, as well as the software design and the interaction between its main components. Finally, functional and operational results observed through the experimentation are described. This experimentation has been carried out in two real scenarios, in Lisbon (Portugal) and Pisa (Italy).

Design and Field Experimentation of a Cooperative ITS Architecture Based on Distributed RSUs †

PubMed Central

Moreno, Asier; Osaba, Eneko; Onieva, Enrique; Perallos, Asier; Iovino, Giovanni; Fernández, Pablo

2016-01-01

This paper describes a new cooperative Intelligent Transportation System architecture that aims to enable collaborative sensing services. The main goal of this architecture is to improve transportation efficiency and performance. The system, which has been proven within the participation in the ICSI (Intelligent Cooperative Sensing for Improved traffic efficiency) European project, encompasses the entire process of capture and management of available road data. For this purpose, it applies a combination of cooperative services and methods for data sensing, acquisition, processing and communication amongst road users, vehicles, infrastructures and related stakeholders. Additionally, the advantages of using the proposed system are exposed. The most important of these advantages is the use of a distributed architecture, moving the system intelligence from the control centre to the peripheral devices. The global architecture of the system is presented, as well as the software design and the interaction between its main components. Finally, functional and operational results observed through the experimentation are described. This experimentation has been carried out in two real scenarios, in Lisbon (Portugal) and Pisa (Italy). PMID:27455277

Practical applications of remote sensing technology

NASA Technical Reports Server (NTRS)

Whitmore, Roy A., Jr.

1990-01-01

Land managers increasingly are becoming dependent upon remote sensing and automated analysis techniques for information gathering and synthesis. Remote sensing and geographic information system (GIS) techniques provide quick and economical information gathering for large areas. The outputs of remote sensing classification and analysis are most effective when combined with a total natural resources data base within the capabilities of a computerized GIS. Some examples are presented of the successes, as well as the problems, in integrating remote sensing and geographic information systems. The need to exploit remotely sensed data and the potential that geographic information systems offer for managing and analyzing such data continues to grow. New microcomputers with vastly enlarged memory, multi-fold increases in operating speed and storage capacity that was previously available only on mainframe computers are a reality. Improved raster GIS software systems have been developed for these high performance microcomputers. Vector GIS systems previously reserved for mini and mainframe systems are available to operate on these enhanced microcomputers. One of the more exciting areas that is beginning to emerge is the integration of both raster and vector formats on a single computer screen. This technology will allow satellite imagery or digital aerial photography to be presented as a background to a vector display.

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.

Investigation related to multispectral imaging systems

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Erickson, J. D.

1974-01-01

A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications.

PubMed

Le, Duc V; Nguyen, Thuong; Scholten, Hans; Havinga, Paul J M

2017-11-29

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

PubMed Central

Scholten, Hans; Havinga, Paul J. M.

2017-01-01

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring. PMID:29186037

MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA

USGS Publications Warehouse

Lestina, Jordan; Cook, Maxwell; Kumar, Sunil; Morisette, Jeffrey T.; Ode, Paul J.; Peirs, Frank

2016-01-01

Wheat stem sawfly (Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.

Experimental Validation of Advanced Dispersed Fringe Sensing (ADFS) Algorithm Using Advanced Wavefront Sensing and Correction Testbed (AWCT)

NASA Technical Reports Server (NTRS)

Wang, Xu; Shi, Fang; Sigrist, Norbert; Seo, Byoung-Joon; Tang, Hong; Bikkannavar, Siddarayappa; Basinger, Scott; Lay, Oliver

2012-01-01

Large aperture telescope commonly features segment mirrors and a coarse phasing step is needed to bring these individual segments into the fine phasing capture range. Dispersed Fringe Sensing (DFS) is a powerful coarse phasing technique and its alteration is currently being used for JWST.An Advanced Dispersed Fringe Sensing (ADFS) algorithm is recently developed to improve the performance and robustness of previous DFS algorithms with better accuracy and unique solution. The first part of the paper introduces the basic ideas and the essential features of the ADFS algorithm and presents the some algorithm sensitivity study results. The second part of the paper describes the full details of algorithm validation process through the advanced wavefront sensing and correction testbed (AWCT): first, the optimization of the DFS hardware of AWCT to ensure the data accuracy and reliability is illustrated. Then, a few carefully designed algorithm validation experiments are implemented, and the corresponding data analysis results are shown. Finally the fiducial calibration using Range-Gate-Metrology technique is carried out and a <10nm or <1% algorithm accuracy is demonstrated.

Surface-area-controlled synthesis of porous TiO2 thin films for gas-sensing applications

NASA Astrophysics Data System (ADS)

Park, Jae Young; Kim, Ho-hyoung; Rana, Dolly; Jamwal, Deepika; Katoch, Akash

2017-03-01

Surface-area-controlled porous TiO2 thin films were prepared via a simple sol-gel chemical route, and their gas-sensing properties were thoroughly investigated in the presence of typical oxidizing NO2 gas. The surface area of TiO2 thin films was controlled by developing porous TiO2 networked by means of controlling the TiO2-to-TTIP (titanium isopropoxide, C12H28O4Ti) molar ratio, where TiO2 nanoparticles of size ˜20 nm were used. The sensor’s response was found to depend on the surface area of the TiO2 thin films. The porous TiO2 thin-film sensor with greater surface area was more sensitive than those of TiO2 thin films with lesser surface area. The improved sensing ability was ascribed to the porous network formed within the thin films by TiO2 sol. Our results show that surface area is a key parameter for obtaining superior gas-sensing performance; this provides important guidelines for preparing and using porous thin films for gas-sensing applications.

Isoelectric Bovine Serum Albumin: Robust Blocking Agent for Enhanced Performance in Optical-Fiber Based DNA Sensing.

PubMed

Wang, Ruoyu; Zhou, Xiaohong; Zhu, Xiyu; Yang, Chao; Liu, Lanhua; Shi, Hanchang

2017-02-24

Surface blocking is a well-known process for reducing unwanted nonspecific adsorption in sensor fabrication, especially important in the emerging field where DNA/RNA applied. Bovine serum albumin (BSA) is one of the most popular blocking agents with an isoelectric point at pH 4.6. Although it is widely recognized that the adsorption of a blocking agent is strongly affected by its net charge and the maximum adsorption is often observed under its isoelectric form, BSA has long been perfunctorily used for blocking merely in neutral solution, showing poor blocking performances in the optical-fiber evanescent wave (OFEW) based sensing toward DNA target. To meet this challenge, we first put forward the view that isoelectric BSA (iep-BSA) has the best blocking performance and use an OFEW sensor platform to demonstrate this concept. An optical-fiber was covalently modified with amino-DNA, and further coupled with the optical system to detect fluorophore labeled complementary DNA within the evanescent field. A dramatic improvement in the reusability of this DNA modified sensing surface was achieved with 120 stable detection cycles, which ensured accurate quantitative bioassay. As expected, the iep-BSA blocked OFEW system showed enhanced sensing performance toward target DNA with a detection limit of 125 pM. To the best of our knowledge, this is the highest number of regeneration cycles ever reported for a DNA immobilized optical-fiber surface. This study can also serve as a good reference and provide important implications for developing similar DNA-directed surface biosensors.

Gas Sensing Properties of ZnO-SnO2 Nanostructures.

PubMed

Chen, Weigen; Li, Qianzhu; Xu, Lingna; Zeng, Wen

2015-02-01

One-dimensional (1D) semiconductor metal oxide nanostructures have attracted increasing attention in electrochemistry, optics, magnetic, and gas sensing fields for the good properties. N-type low dimensional semiconducting oxides such as SnO2 and ZnO have been known for the detection of inflammable or toxic gases. In this paper, we fabricated the ZnO-SnO2 and SnO2 nanoparticles by hydrothermal synthesis. Microstructure characterization was performed using X-ray diffraction (XRD) and surface morphologies for both the pristine and doped samples were observed using field emission scanning electron microscope (FESEM), transmission electron microscopy (TEM) and high resolution transmission electron microscopy (HRTEM). Then we made thin film gas sensor to study the gas sensing properties of ZnO-SnO2 and SnO2 gas sensor to H2 and CO. A systematic comparison study reveals an enhanced gas sensing performance for the sensor made of SnO2 and ZnO toward H2 and CO over that of the commonly applied undecorated SnO2 nanoparticles. The improved gas sensing properties are attributed to the size of grains and pronounced electron transfer between the compound nanostructures and the absorbed oxygen species as well as to the heterojunctions of the ZnO nanoparticles to the SnO2 nanoparticles, which provide additional reaction rooms. The results represent an advance of compound nanostructures in further enhancing the functionality of gas sensors, and this facile method could be applicable to many sensing materials, offering a new avenue and direction to detect gases of interest based on composite tin oxide nanoparticles.

Magnetic-field sensing with quantum error detection under the effect of energy relaxation

NASA Astrophysics Data System (ADS)

Matsuzaki, Yuichiro; Benjamin, Simon

2017-03-01

A solid state spin is an attractive system with which to realize an ultrasensitive magnetic field sensor. A spin superposition state will acquire a phase induced by the target field, and we can estimate the field strength from this phase. Recent studies have aimed at improving sensitivity through the use of quantum error correction (QEC) to detect and correct any bit-flip errors that may occur during the sensing period. Here we investigate the performance of a two-qubit sensor employing QEC and under the effect of energy relaxation. Surprisingly, we find that the standard QEC technique to detect and recover from an error does not improve the sensitivity compared with the single-qubit sensors. This is a consequence of the fact that the energy relaxation induces both a phase-flip and a bit-flip noise where the former noise cannot be distinguished from the relative phase induced from the target fields. However, we have found that we can improve the sensitivity if we adopt postselection to discard the state when error is detected. Even when quantum error detection is moderately noisy, and allowing for the cost of the postselection technique, we find that this two-qubit system shows an advantage in sensing over a single qubit in the same conditions.

Sensing Technologies for Autism Spectrum Disorder Screening and Intervention

PubMed Central

Cabibihan, John-John; Javed, Hifza; Aldosari, Mohammed; Frazier, Thomas W.; Elbashir, Haitham

2016-01-01

This paper reviews the state-of-the-art in sensing technologies that are relevant for Autism Spectrum Disorder (ASD) screening and therapy. This disorder is characterized by difficulties in social communication, social interactions, and repetitive behaviors. It is diagnosed during the first three years of life. Early and intensive interventions have been shown to improve the developmental trajectory of the affected children. The earlier the diagnosis, the sooner the intervention therapy can begin, thus, making early diagnosis an important research goal. Technological innovations have tremendous potential to assist with early diagnosis and improve intervention programs. The need for careful and methodological evaluation of such emerging technologies becomes important in order to assist not only the therapists and clinicians in their selection of suitable tools, but to also guide the developers of the technologies in improving hardware and software. In this paper, we survey the literatures on sensing technologies for ASD and we categorize them into eye trackers, movement trackers, electrodermal activity monitors, tactile sensors, vocal prosody and speech detectors, and sleep quality assessment devices. We assess their effectiveness and study their limitations. We also examine the challenges faced by this growing field that need to be addressed before these technologies can perform up to their theoretical potential. PMID:28036004

Market Assessment of Forward-Looking Turbulence Sensing Systems

NASA Technical Reports Server (NTRS)

Kauffmann, Paul; Sousa-Poza, Andres

2001-01-01

In recognition of the importance of turbulence mitigation as a tool to improve aviation safety, NASA's Aviation Safety Program developed a Turbulence Detection and Mitigation Sub-element. The objective of this effort is to develop highly reliable turbulence detection technologies for commercial transport aircraft to sense dangerous turbulence with sufficient time warning so that defensive measures can be implemented and prevent passenger and crew injuries. Current research involves three forward sensing products to improve the cockpit awareness of possible turbulence hazards. X-band radar enhancements will improve the capabilities of current weather radar to detect turbulence associated with convective activity. LIDAR (Light Detection and Ranging) is a laser-based technology that is capable of detecting turbulence in clear air. Finally, a possible Radar-LIDAR hybrid sensor is envisioned to detect the full range of convective and clear air turbulence. To support decisions relating to the development of these three forward-looking turbulence sensor technologies, the objective of this study was defined as examination of cost and implementation metrics. Tasks performed included the identification of cost factors and certification issues, the development and application of an implementation model, and the development of cost budget/targets for installing the turbulence sensor and associated software devices into the commercial transport fleet.

The Potential of Environmental Sensors for Improving the Mobility Performance of Mainstream Blind Students. Final Report.

ERIC Educational Resources Information Center

Weisgerber, Robert A.; deHaas, Carla

The report describes an effort to develop and test instructional materials, techniques and procedures - ESSETS (environmental sensing, selection, evaluation and training system) - for teaching functionally blind young adults to use electronic travel aids (ETAs). Considered are development of training guidelines, field site selection and instructor…

Turning around Maple Shade Middle School: A Principal's Initial Reform Efforts

ERIC Educational Resources Information Center

Salmonowicz, Michael J.; Levy, Melissa K.

2009-01-01

This case was written for use in courses dealing with school administration, specifically those related to organizational change, school improvement/turnaround, and the principalship. It explores a veteran principal's first year as a "turnaround specialist" in a low-performing middle school, where she works with a sense of urgency to achieve an…

Motivation Levels among Traditional and Open Learning Undergraduate Students in India

ERIC Educational Resources Information Center

Singh, Shashi; Singh, Ajay; Singh, Kiran

2012-01-01

Motivation plays a crucial role in learning. Motivation energizes the behavior of the individual. It also directs the behavior towards specific goals. It helps students acquire knowledge, develop social qualities, increase initiation, persist in activities, improve performance, and develop a sense of discipline. This paper aims to compare the…

State Test Data and School Improvement Efforts

ERIC Educational Resources Information Center

Beaver, Jessica K.; Weinbaum, Elliot H.

2015-01-01

Although much has been written about the potential benefits of effective data use in schools, considerably less attention has been paid to how schools make sense of the data generated from performance-based accountability measures. This article explores schools' usage of state test data, the intensity of data use, and the perceived utility of…

Aeronautics and Space Report of the President: 1977 Activities.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Washington, DC.

The national programs in aeronautics and space made steady progress in 1977 toward their long-term objectives. In aeronautics the goals were improved performance, energy efficiency, and safety in aircraft. In space the goals were: (1) better remote sensing systems to generate more sophisticated information about the Earth's environment; (2)…

Assessment of Performance of the Industrial Process of Bulk Vacuum Packaging of Raw Meat with Nondestructive Optical Oxygen Sensing Systems.

PubMed

Kelly, Caroline A; Cruz-Romero, Malco; Kerry, Joseph P; Papkovsky, Dmitri P

2018-05-02

The commercially-available optical oxygen-sensing system Optech-O₂ Platinum was applied to nondestructively assess the in situ performance of bulk, vacuum-packaged raw beef in three ~300 kg containers. Twenty sensors were attached to the inner surface of the standard bin-contained laminate bag (10 on the front and back sides), such that after filling with meat and sealing under vacuum, the sensors were accessible for optical interrogation with the external reader device. After filling and sealing each bag, the sensors were measured repetitively and nondestructively over a 15-day storage period at 1 °C, thus tracking residual oxygen distribution in the bag and changes during storage. The sensors revealed a number of unidentified meat quality and processing issues, and helped to improve the packaging process by pouring flakes of dry ice into the bag. Sensor utility in mapping the distribution of residual O₂ in sealed bulk containers and optimising and improving the packaging process, including handling and storage of bulk vacuum-packaged meat bins, was evident.

An investigation into non-invasive physical activity recognition using smartphones.

PubMed

Kelly, Daniel; Caulfield, Brian

2012-01-01

Technology utilized to automatically monitor Activities of Daily Living (ADL) could be a key component in identifying deviations from normal functional profiles and providing feedback on interventions aimed at improving health. However, if activity recognition systems are to be implemented in real world scenarios such as health and wellness monitoring, the activity sensing modality must unobtrusively fit the human environment rather than forcing humans to adhere to sensor specific conditions. Modern smart phones represent a ubiquitous computing device which has already undergone mainstream adoption. In this paper, we investigate the feasibility of using a modern smartphone, with limited placement constraints, as the sensing modality for an activity recognition system. A dataset of 4 subjects performing 7 activities, using varying sensor placement conditions, is utilized to investigate this. Initial experiments show that a decision tree classifier performs activity classification with precision and recall scores of 0.75 and 0.73 respectively. More importantly, as part of this initial experiment, 3 main problems, and subsequently 3 solutions, relating to unconstrained sensor placement were identified. Using our proposed solutions, classification precision and recall scores were improved by +13% and +14.6% respectively.

A T-Type Capacitive Sensor Capable of Measuring 5-DOF Error Motions of Precision Spindles

PubMed Central

Xiang, Kui; Qiu, Rongbo; Mei, Deqing; Chen, Zichen

2017-01-01

The precision spindle is a core component of high-precision machine tools, and the accurate measurement of its error motions is important for improving its rotation accuracy as well as the work performance of the machine. This paper presents a T-type capacitive sensor (T-type CS) with an integrated structure. The proposed sensor can measure the 5-degree-of-freedom (5-DOF) error motions of a spindle in-situ and simultaneously by integrating electrode groups in the cylindrical bore of the stator and the outer end face of its flange, respectively. Simulation analysis and experimental results show that the sensing electrode groups with differential measurement configuration have near-linear output for the different types of rotor displacements. What’s more, the additional capacitance generated by fringe effects has been reduced about 90% with the sensing electrode groups fabricated based on flexible printed circuit board (FPCB) and related processing technologies. The improved signal processing circuit has also been increased one times in the measuring performance and makes the measured differential output capacitance up to 93% of the theoretical values. PMID:28846631

Substrate-dependent structural and CO sensing properties of LaCoO3 epitaxial films

NASA Astrophysics Data System (ADS)

Liu, Haifeng; Sun, Hongjuan; Xie, Ruishi; Zhang, Xingquan; Zheng, Kui; Peng, Tongjiang; Wu, Xiaoyu; Zhang, Yanping

2018-06-01

LaCoO3 thin films were grown on different (0 0 1) oriented LaAlO3, SrTiO3 and (LaAlO3)0.3(Sr2AlTaO6)0.7 by the polymer assisted deposition method, respectively. All the LaCoO3 thin films are in epitaxial growth on these substrates, with tetragonal distortion of CoO6 octahedrons. Due to different in-plane lattice mismatch, the LaCoO3 film on LaAlO3 has the largest tetragonal distortion of CoO6 octahedrons while the film grown on (LaAlO3)0.3(Sr2AlTaO6)0.7 has the smallest tetragonal distortion. The relative contents of the surface absorbed oxygen species are found to increase for the LaCoO3 epitaxial films grown on (0 0 1) oriented (LaAlO3)0.3(Sr2AlTaO6)0.7, SrTiO3 and LaAlO3 substrates, sequentially. The film sensors exhibit good CO sensing properties at 150 °C, and the LaCoO3 film on LaAlO3 shows the highest response but the film on (LaAlO3)0.3(Sr2AlTaO6)0.7 shows the lowest. It reveals that the larger degree of Jahn-Teller-like tetragonal distortion of CoO6 octahedrons may greatly improve the surface absorbing and catalytic abilities, corresponding to more excellent CO sensing performance. The present study suggests that the formation of epitaxial films is an efficient methodology for controlling the octahedral distortion and thereby improving the gas sensing performance of perovskite transition metal oxides.

Prevalence of E/A wave fusion and A wave truncation in DDD pacemaker patients with complete AV block under nominal AV intervals.

PubMed

Poller, Wolfram C; Dreger, Henryk; Schwerg, Marius; Melzer, Christoph

2015-01-01

Optimization of the AV-interval (AVI) in DDD pacemakers improves cardiac hemodynamics and reduces pacemaker syndromes. Manual optimization is typically not performed in clinical routine. In the present study we analyze the prevalence of E/A wave fusion and A wave truncation under resting conditions in 160 patients with complete AV block (AVB) under the pre-programmed AVI. We manually optimized sub-optimal AVI. We analyzed 160 pacemaker patients with complete AVB, both in sinus rhythm (AV-sense; n = 129) and under atrial pacing (AV-pace; n = 31). Using Doppler analyses of the transmitral inflow we classified the nominal AVI as: a) normal, b) too long (E/A wave fusion) or c) too short (A wave truncation). In patients with a sub-optimal AVI, we performed manual optimization according to the recommendations of the American Society of Echocardiography. All AVB patients with atrial pacing exhibited a normal transmitral inflow under the nominal AV-pace intervals (100%). In contrast, 25 AVB patients in sinus rhythm showed E/A wave fusion under the pre-programmed AV-sense intervals (19.4%; 95% confidence interval (CI): 12.6-26.2%). A wave truncations were not observed in any patient. All patients with a complete E/A wave fusion achieved a normal transmitral inflow after AV-sense interval reduction (mean optimized AVI: 79.4 ± 13.6 ms). Given the rate of 19.4% (CI 12.6-26.2%) of patients with a too long nominal AV-sense interval, automatic algorithms may prove useful in improving cardiac hemodynamics, especially in the subgroup of atrially triggered pacemaker patients with AV node diseases.

Assessment of analytical quality in Nordic clinical chemistry laboratories using data from contemporary national programs.

PubMed

Aronsson, T; Bjørnstad, P; Leskinen, E; Uldall, A; de Verdier, C H

1984-01-01

The aim of this investigation was primarily to assess analytical quality expressed as between-laboratory, within-laboratory, and total imprecision, not in order to detect laboratories with poor performance, but in the positive sense to provide data for improving critical steps in analytical methodology. The aim was also to establish the present state of the art in comparison with earlier investigations to see if improvement in analytical quality could be observed.

A robot-aided visuo-motor training that improves proprioception and spatial accuracy of untrained movement.

PubMed

Elangovan, Naveen; Cappello, Leonardo; Masia, Lorenzo; Aman, Joshua; Konczak, Jürgen

2017-12-06

Proprioceptive function can become enhanced during motor learning. Yet, we have incomplete knowledge to what extent proprioceptive function is trainable and how a training that enhances proprioception may influence performance in untrained motor skills. To address this knowledge gap, healthy young adults (N = 14) trained in a visuomotor task that required learners to make increasingly accurate wrist movements. Using a robotic exoskeleton coupled with a virtual visual environment, participants tilted a virtual table through continuous wrist flexion/extension movements with the goal to position a rolling ball on table into a target. With learning progress, the level of difficulty increased by altering the virtual ball mechanics and the gain between joint movement and ball velocity. Before and after training, wrist position sense acuity and spatial movement accuracy in an untrained, discrete wrist-pointing task was assessed using the same robot. All participants showed evidence of proprioceptive-motor learning. Mean position sense discrimination threshold improved by 34%. Wrist movement accuracy in the untrained pointing task improved by 27% in 13/14 participants. This demonstrates that a short sensorimotor training challenging proprioception can a) effectively enhance proprioceptive acuity and b) improve the accuracy of untrained movement. These findings provide a scientific basis for applying such somatosensory-based motor training to clinical populations with known proprioceptive dysfunction to enhance sensorimotor performance.

Self-sensing performance of MWCNT-low density polyethylene nanocomposites

NASA Astrophysics Data System (ADS)

Gupta, Tejendra K.; Kumar, S.; Khan, Amal Z.; Varadarajan, Kartik M.; Cantwell, Wesley J.

2018-01-01

Carbon nanotubes (CNTs) based polymer nanocomposites offer a range of remarkable properties. Here, we demonstrate self-sensing performance of low density polyethylene (LDPE)-multiwalled carbon nanotubes (MWCNTs) nanocomposites for the first time. The dispersion of the CNTs and the morphology of the nanocomposites was investigated using scanning electron microscopy, x-ray diffraction and Raman spectroscopic techniques. The thermal properties were measured using thermal gravimetric analysis and differential scanning calorimetry and were found to increase with increasing wt% of MWCNTs in LDPE matrix. An overall improvement in ultimate tensile strength, yield strength and Young’s modulus was found to be 59.6%, 48.5% and 129.3%, respectively for 5.0 wt% loading of MWCNTs. The electrical percolation threshold was observed at 1.0 wt% of MWCNTs and the highest electrical conductivity of 2.8 × 10-2 Scm-1 was observed at 5.0 wt% loading of MWCNTs. These piezo-resistive nanocomposites offer tunable self-sensing capabilities with gauge factors in the ranges of 17-52 and 42-530 in linear elastic (strain ˜3%) and inelastic regimes (strain ˜15%) respectively. Our demonstration would provide guidelines for the fabrication of low cost, self-sensing MWCNT-LDPE nanocomposites for potential use as civil water pipelines and landfill membranes.

Study on room temperature gas-sensing performance of CuO film-decorated ordered porous ZnO composite by In2O3 sensitization

NASA Astrophysics Data System (ADS)

Li, Tian-tian; Bao, Na; Geng, Ai-fang; Yu, Hui; Yang, Ying; Dong, Xiang-ting

2018-02-01

For the first time, ordered mesoporous ZnO nanoparticles have been synthesized by a template method. The electroplating after chemical plating method was creatively used to form copper film on the surface of the prepared ZnO, and then a CuO film-decorated ordered porous ZnO composite (CuO/ZnO) was obtained by a high-temperature oxidation method. In2O3 was loaded into the prepared CuO film-ZnO by an ultrasonic-assisted method to sensitize the room temperature gas-sensing performance of the prepared CuO/ZnO materials. The doped In2O3 could effectively improve the gas-sensing properties of the prepared materials to nitrogen oxides (NOx) at room temperature. The 1% In2O3 doped CuO/ZnO sample (1 wt% In2O3-CuO/ZnO) showed the best gas-sensing properties whose response to 100 ppm NOx reached 82%, and the detectable minimum concentration reached 1 ppm at room temperature. The prepared materials had a good selectivity, better response, very low detection limit, and high sensitivity to NOx gas at room temperature, which would have a great development space in the gas sensor field and a great research value.

Energy harvesting influences electrochemical performance of microbial fuel cells

NASA Astrophysics Data System (ADS)

Lobo, Fernanda Leite; Wang, Xin; Ren, Zhiyong Jason

2017-07-01

Microbial fuel cells (MFCs) can be effective power sources for remote sensing, wastewater treatment and environmental remediation, but their performance needs significant improvement. This study systematically analyzes how active harvesting using electrical circuits increased MFC system outputs as compared to passive resistors not only in the traditional maximal power point (MPP) but also in other desired operating points such as the maximum current point (MCP) and the maximum voltage point (MVP). Results show that active harvesting in MPP increased power output by 81-375% and active harvesting in MCP increased Coulombic efficiency by 207-805% compared with resisters operated at the same points. The cyclic voltammograms revealed redox potential shifts and supported the performance data. The findings demonstrate that active harvesting is a very effective approach to improve MFC performance across different operating points.

SPOT satellite family: Past, present, and future of the operations in the mission and control center

NASA Technical Reports Server (NTRS)

Philippe, Pacholczyk

1993-01-01

SPOT sun-synchronous remote sensing satellites are operated by CNES since February 1986. Today, the SPOT mission and control center (CCM) operates SPOT1, SPOT2, and is ready to operate SPOT3. During these seven years, the way to operate changed and the CCM, initially designed for the control of one satellite, has been modified and upgraded to support these new operating modes. All these events have shown the performances and the limits of the system. A new generation of satellite (SPOT4) will continue the remote sensing mission during the second half of the 90's. Its design takes into account the experience of the first generation and supports several improvements. A new generation of control center (CMP) has been developed and improves the efficiency, quality, and reliability of the operations. The CMP is designed for operating two satellites at the same time during launching, in-orbit testing, and operating phases. It supports several automatic procedures and improves data retrieval and reporting.

Stretchable Electronic Sensors of Nanocomposite Network Films for Ultrasensitive Chemical Vapor Sensing.

PubMed

Yan, Hong; Zhong, Mengjuan; Lv, Ze; Wan, Pengbo

2017-11-01

A stretchable, transparent, and body-attachable chemical sensor is assembled from the stretchable nanocomposite network film for ultrasensitive chemical vapor sensing. The stretchable nanocomposite network film is fabricated by in situ preparation of polyaniline/MoS 2 (PANI/MoS 2 ) nanocomposite in MoS 2 suspension and simultaneously nanocomposite deposition onto prestrain elastomeric polydimethylsiloxane substrate. The assembled stretchable electronic sensor demonstrates ultrasensitive sensing performance as low as 50 ppb, robust sensing stability, and reliable stretchability for high-performance chemical vapor sensing. The ultrasensitive sensing performance of the stretchable electronic sensors could be ascribed to the synergistic sensing advantages of MoS 2 and PANI, higher specific surface area, the reliable sensing channels of interconnected network, and the effectively exposed sensing materials. It is expected to hold great promise for assembling various flexible stretchable chemical vapor sensors with ultrasensitive sensing performance, superior sensing stability, reliable stretchability, and robust portability to be potentially integrated into wearable electronics for real-time monitoring of environment safety and human healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hydrogen Gas Sensing Characteristics of Nanostructured NiO Thin Films Synthesized by SILAR Method

NASA Astrophysics Data System (ADS)

Karaduman, Irmak; Çorlu, Tugba; Yıldırım, M. Ali; Ateş, Aytunç; Acar, Selim

2017-07-01

Nanostructured NiO thin films have been synthesized by a facile, low-cost successive ionic layer adsorption and reaction (SILAR) method, and the effects of the film thickness on their hydrogen gas sensing properties investigated. The samples were characterized by scanning electron microscopy (SEM), x-ray diffraction (XRD) analysis, and energy-dispersive x-ray analysis. The XRD results revealed that the crystallinity improved with increasing thickness, exhibiting polycrystalline structure. SEM studies showed that all the films covered the glass substrate well. According to optical absorption measurements, the optical bandgap decreased with increasing film thickness. The gas sensing properties of the nanostructured NiO thin films were studied as a function of operating temperature and gas concentration. The samples showed good sensing performance of H2 gas with high response. The maximum response was 75% at operating temperature of 200°C for hydrogen gas concentration of 40 ppm. These results demonstrate that nanostructured NiO thin films synthesized by the SILAR method have potential for application in hydrogen detection.

Carbon Nanotubes Blended Hydroxyapatite Ethanol Sensor

NASA Astrophysics Data System (ADS)

Anjum, S. R.; Khairnar, R. S.

2016-12-01

Nano crystals of Hydroxyapatite (HAp) were synthesized by a wet chemical precipitation method. The nano composite materials were developed by doping various weight concentrations of carbon nanotubes in HAp, followed by characterization using scanning electron microscopy, and X-ray diffraction. Thick films of these materials were prepared by using screen printing technique. The ethanol sensing properties of these nano crystals and nano composite films were investigated by two probe electrical method. The gas sensing features such as operating temperature, response and recovery time, maximum gas detection limit, etc. were studied, since these parameters are of prime importance for sensor. The results revealed that at room temperature, the composite materials exhibited improved sensing performance towards 100 ppm ethanol with fast response times. It also showed shorter recovery time with higher vapor uptake capacity. The ethanol adsorption processes on doped and undoped substrates can be explained by surface chemical reactions as well as providing the possible adsorption models. The novelty of this work lies in developing reusable sensor substrates for room temperature sensing.

Adsorption Site of Gas Molecules on Defective Armchair Graphene Nanoribbon Formed Through Ion Bombardment

NASA Astrophysics Data System (ADS)

Auzar, Zuriana; Johari, Zaharah; Sakina, S. H.; Alias, N. Ezaila

2018-02-01

High sensitivity and selectivity is desired in sensing devices. The aim of this study is to investigate the use of the ion bombardment process in creating a defect on graphene nanoribbons (GNR), which significantly affects sensing properties, in particular adsorption energy, charge transfer and sensitivity. A process has been developed to form the defect on the GNR surface using molecular dynamic (MD) with a reactive force field with nitrogen ion. The sensing properties were calculated using the extended Huckel theory when oxygen (O2) and ammonia (NH3) molecules are exposed to different areas on the defective site. Through simulation, it was found that the ion bombardment process formed various types of defects on the GNR surface. Most notably, molecules adsorbed on the ripple area considerably improve the sensitivity by more than 50%. This indicates that the defect on the armchair graphene nanoribbon (AGNR) surface can be a method to enhance graphene-based sensing performance.

Metal organic frameworks enhanced graphene oxide electrode for humidity sensor

NASA Astrophysics Data System (ADS)

Zhang, Wen; Meng, Siyu; Wang, Hui; He, Yongning

2018-03-01

Copper benzene-1,3,5-tricarboxylate (Cu-BTC), a typical metal organic framework, is deposited on the graphene oxide (GO) film to prepare a resistance humidity sensor (Cu- BTC/GO) for improving humidity sensing. The characteristics of Cu-BTC, GO and Cu- BTC/GO were measured by scanning electron microscopy (SEM), X-ray diffraction (XRD), nitrogen isotherm adsorption and electrochemical impedance spectroscopy (EIS). The humidity sensing properties of the Cu-BTC/GO were investigated in detail. The obtained Cu-BTC/GO demonstrates good sensitivity and repeatability over 11%-85% relative humidity (RH) measurements. The Cu-BTC/GO coated device shows high normalized response (S) value (6200%), which is much higher than that of pure GO coated device. Sensing mechanism of Cu- BTC/GO is discussed based on different RH and the results indicate that moderate amounts of Cu-BTC deposition can enhance sensing abilities of GO. High specific surface area and interfacial conductivity are crucial factors to fabricate humidity sensors with high performance.

Au-modified three-dimensional In₂O₃ inverse opals: synthesis and improved performance for acetone sensing toward diagnosis of diabetes.

PubMed

Xing, Ruiqing; Li, Qingling; Xia, Lei; Song, Jian; Xu, Lin; Zhang, Jiahuan; Xie, Yi; Song, Hongwei

2015-08-14

Analyzing the volatile organic compounds (VOCs) in exhaled breath effectively is crucial to medical treatment, which can provide a fast and noninvasive way to diagnose disease. Well-designed materials with controlled structures have great influence on the sensing performance. In this work, the ordered three dimensional inverse opal (3DIO) macroporous In2O3 films with additional via-hole architectures were fabricated and different amounts of gold nanoparticles (Au NPs) were loaded on the In2O3 films aiming at enhancing their electrical responses. The gas sensing to acetone toward diabetes diagnosis in exhaled breath was performed with different Au/In2O3 electrodes. Representatively, the best 3DIO Au/In2O3 sensor can detect acetone effectively at 340 °C with response of 42.4 to 5 ppm, the actual detection limit is as low as 20 ppb, and it holds a dynamic response of 11 s and a good selectivity. Moreover, clinical tests proved that the as-prepared 3DIO Au/In2O3 IO sensor could distinguish acetone biomarkers in human breath clearly. The excellent gas sensing properties of the Au/In2O3 electrodes were attributed to the "spillover effects" between Au and In2O3 and the special 3DIO structure. This work indicates that 3DIO Au/In2O3 composite is a promising electrode material for actual application in the monitoring and detection of diabetes through exhaled breath.

Electrochemical dopamine sensor based on P-doped graphene: Highly active metal-free catalyst and metal catalyst support.

PubMed

Chu, Ke; Wang, Fan; Zhao, Xiao-Lin; Wang, Xin-Wei; Tian, Ye

2017-12-01

Heteroatom doping is an effective strategy to enhance the catalytic activity of graphene and its hybrid materials. Despite a growing interest of P-doped graphene (P-G) in energy storage/generation applications, P-G has rarely been investigated for electrochemical sensing. Herein, we reported the employment of P-G as both metal-free catalyst and metal catalyst support for electrochemical detection of dopamine (DA). As a metal-free catalyst, P-G exhibited prominent DA sensing performances due to the important role of P doping in improving the electrocatalytic activity of graphene toward DA oxidation. Furthermore, P-G could be an efficient supporting material for loading Au nanoparticles, and resulting Au/P-G hybrid showed a dramatically enhanced electrocatalytic activity and extraordinary sensing performances with a wide linear range of 0.1-180μM and a low detection limit of 0.002μM. All these results demonstrated that P-G might be a very promising electrode material for electrochemical sensor applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of pests and diseases of Dalbergia hainanensis based on EVI time series and classification of decision tree

NASA Astrophysics Data System (ADS)

Luo, Qiu; Xin, Wu; Qiming, Xiong

2017-06-01

In the process of vegetation remote sensing information extraction, the problem of phenological features and low performance of remote sensing analysis algorithm is not considered. To solve this problem, the method of remote sensing vegetation information based on EVI time-series and the classification of decision-tree of multi-source branch similarity is promoted. Firstly, to improve the time-series stability of recognition accuracy, the seasonal feature of vegetation is extracted based on the fitting span range of time-series. Secondly, the decision-tree similarity is distinguished by adaptive selection path or probability parameter of component prediction. As an index, it is to evaluate the degree of task association, decide whether to perform migration of multi-source decision tree, and ensure the speed of migration. Finally, the accuracy of classification and recognition of pests and diseases can reach 87%--98% of commercial forest in Dalbergia hainanensis, which is significantly better than that of MODIS coverage accuracy of 80%--96% in this area. Therefore, the validity of the proposed method can be verified.

Scalability Issues for Remote Sensing Infrastructure: A Case Study.

PubMed

Liu, Yang; Picard, Sean; Williamson, Carey

2017-04-29

For the past decade, a team of University of Calgary researchers has operated a large "sensor Web" to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system's memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

A comparison of PCA/ICA for data preprocessing in remote sensing imagery classification

NASA Astrophysics Data System (ADS)

He, Hui; Yu, Xianchuan

2005-10-01

In this paper a performance comparison of a variety of data preprocessing algorithms in remote sensing image classification is presented. These selected algorithms are principal component analysis (PCA) and three different independent component analyses, ICA (Fast-ICA (Aapo Hyvarinen, 1999), Kernel-ICA (KCCA and KGV (Bach & Jordan, 2002), EFFICA (Aiyou Chen & Peter Bickel, 2003). These algorithms were applied to a remote sensing imagery (1600×1197), obtained from Shunyi, Beijing. For classification, a MLC method is used for the raw and preprocessed data. The results show that classification with the preprocessed data have more confident results than that with raw data and among the preprocessing algorithms, ICA algorithms improve on PCA and EFFICA performs better than the others. The convergence of these ICA algorithms (for data points more than a million) are also studied, the result shows EFFICA converges much faster than the others. Furthermore, because EFFICA is a one-step maximum likelihood estimate (MLE) which reaches asymptotic Fisher efficiency (EFFICA), it computers quite small so that its demand of memory come down greatly, which settled the "out of memory" problem occurred in the other algorithms.

Feedback about action performed can alter the sense of self-agency

PubMed Central

Kumar, Neeraj; Manjaly, Jaison A.; Miyapuram, Krishna P.

2014-01-01

Sense of agency refers to the sense of authorship of an action and its outcome. Sense of agency is often explained through computational models of motor control (e.g., the comparator model). Previous studies using the comparator model have manipulated action-outcome contingency to understand its effect on the sense of agency. More recent studies have shown that cues related to outcome, priming outcome and priming action have an effect on agency attribution. However, relatively few studies have focused on the effect of recalibrating internal predictions on the sense of agency. This study aims to investigate how feedback about action can recalibrate prediction and modulates the sense of agency. While participants performed a Flanker task, we manipulated the feedback about the validity of the action performed, independent of their responses. When true feedback is given, the sense of agency would reflect congruency between the sensory outcome and the action performed. The results show an opposite effect on the sense of agency when false feedback was given. We propose that feedback about action performed can recalibrate the prediction of sensory outcome and thus alter the sense of agency. PMID:24611059

Compact SAR and Small Satellite Solutions for Earth Observation

NASA Astrophysics Data System (ADS)

LaRosa, M.; L'Abbate, M.

2016-12-01

Requirements for near and short term mission applications (Observation and Reconnaissance, SIGINT, Early Warning, Meteorology,..) are increasingly calling for spacecraft operational responsiveness, flexible configuration, lower cost satellite constellations and flying formations, to improve both the temporal performance of observation systems (revisit, response time) and the remote sensing techniques (distributed sensors, arrays, cooperative sensors). In answer to these users' needs, leading actors in Space Systems for EO are involved in development of Small and Microsatellites solutions. Thales Alenia Space (TAS) has started the "COMPACT-SAR" project to develop a SAR satellite characterized by low cost and reduced mass while providing, at the same time, high image quality in terms of resolution, swath size, and radiometric performance. Compact SAR will embark a X-band SAR based on a deployable reflector antenna fed by an active phased array feed. This concept allows high performance, providing capability of electronic beam steering both in azimuth and elevation planes, improving operational performance over a purely mechanically steered SAR system. Instrument provides both STRIPMAP and SPOTLIGHT modes, and thanks to very high gain antenna, can also provide a real maritime surveillance mode based on a patented Low PRF radar mode. Further developments are in progress considering missions based on Microsatellites technology, which can provide effective solutions for different user needs, such as Operational responsiveness, low cost constellations, distributed observation concept, flying formations, and can be conceived for applications in the field of Observation, Atmosphere sensing, Intelligence, Surveillance, Reconnaissance (ISR), Signal Intelligence. To satisfy these requirements, flexibility of small platforms is a key driver and especially new miniaturization technologies able to optimize the performance. An overview new micros-satellite (based on NIMBUS platform) and mission concepts is provided, such as passive SAR for multi-static imaging and tandem, Medium swath/medium resolution dual pol MICROSAR for in L-C-X band multi-application for maritime surveillance and land monitoring, applications for Space Debris monitoring, precision farming, Atmosphere sensing.

Performance improvement of coherent free-space optical communication with quadrature phase-shift keying modulation using digital phase estimation.

PubMed

Li, Xueliang; Geng, Tianwen; Ma, Shuang; Li, Yatian; Gao, Shijie; Wu, Zhiyong

2017-06-01

The performance of coherent free-space optical (CFSO) communication with phase modulation is limited by both phase fluctuations and intensity scintillations induced by atmospheric turbulence. To improve the system performance, one effective way is to use digital phase estimation. In this paper, a CFSO communication system with quadrature phase-shift keying modulation is studied. With consideration of the effects of log-normal amplitude fluctuations and Gauss phase fluctuations, a two-stage Mth power carrier phase estimation (CPE) scheme is proposed. The simulation results show that the phase noise can be suppressed greatly by this scheme, and the system symbol error rate performance with the two-stage Mth power CPE can be three orders lower than that of the single-stage Mth power CPE. Therefore, the two-stage CPE we proposed can contribute to the performance improvements of the CFSO communication system and has determinate guidance sense to its actual application.

System and method for improving performance of a fluid sensor for an internal combustion engine

DOEpatents

Kubinski, David [Canton, MI; Zawacki, Garry [Livonia, MI

2009-03-03

A system and method for improving sensor performance of an on-board vehicle sensor, such as an exhaust gas sensor, while sensing a predetermined substance in a fluid flowing through a pipe include a structure for extending into the pipe and having at least one inlet for receiving fluid flowing through the pipe and at least one outlet generally opposite the at least one inlet, wherein the structure redirects substantially all fluid flowing from the at least one inlet to the sensor to provide a representative sample of the fluid to the sensor before returning the fluid through the at least one outlet.

Carbon Nanotube Electrode Arrays For Enhanced Chemical and Biological Sensing

NASA Technical Reports Server (NTRS)

Han, Jie

2003-01-01

Applications of carbon nanotubes for ultra-sensitive electrical sensing of chemical and biological species have been a major focus in NASA Ames Center for Nanotechnology. Great progress has been made toward controlled growth and chemical functionalization of vertically aligned carbon nanotube arrays and integration into micro-fabricated chip devices. Carbon nanotube electrode arrays devices have been used for sub-attomole detection of DNA molecules. Interdigitated carbon nanotubes arrays devices have been applied to sub ppb (part per billion) level chemical sensing for many molecules at room temperature. Stability and reliability have also been addressed in our device development. These results show order of magnitude improvement in device performance, size and power consumption as compared to micro devices, promising applications of carbon nanotube electrode arrays for clinical molecular diagnostics, personal medical testing and monitoring, and environmental monitoring.

Hydrogen Gas Sensors Based on Semiconductor Oxide Nanostructures

PubMed Central

Gu, Haoshuang; Wang, Zhao; Hu, Yongming

2012-01-01

Recently, the hydrogen gas sensing properties of semiconductor oxide (SMO) nanostructures have been widely investigated. In this article, we provide a comprehensive review of the research progress in the last five years concerning hydrogen gas sensors based on SMO thin film and one-dimensional (1D) nanostructures. The hydrogen sensing mechanism of SMO nanostructures and some critical issues are discussed. Doping, noble metal-decoration, heterojunctions and size reduction have been investigated and proved to be effective methods for improving the sensing performance of SMO thin films and 1D nanostructures. The effect on the hydrogen response of SMO thin films and 1D nanostructures of grain boundary and crystal orientation, as well as the sensor architecture, including electrode size and nanojunctions have also been studied. Finally, we also discuss some challenges for the future applications of SMO nanostructured hydrogen sensors. PMID:22778599

Study on Building Extraction from High-Resolution Images Using Mbi

NASA Astrophysics Data System (ADS)

Ding, Z.; Wang, X. Q.; Li, Y. L.; Zhang, S. S.

2018-04-01

Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. However, the diversity and complexity of buildings make building extraction methods still face challenges in terms of accuracy, efficiency, and so on. In this study, a new building extraction framework based on MBI and combined with image segmentation techniques, spectral constraint, shadow constraint, and shape constraint is proposed. In order to verify the proposed method, worldview-2, GF-2, GF-1 remote sensing images covered Xiamen Software Park were used for building extraction experiments. Experimental results indicate that the proposed method improve the original MBI significantly, and the correct rate is over 86 %. Furthermore, the proposed framework reduces the false alarms by 42 % on average compared to the performance of the original MBI.

Photonic crystal resonances for sensing and imaging

NASA Astrophysics Data System (ADS)

Pitruzzello, Giampaolo; Krauss, Thomas F.

2018-07-01

This review provides an insight into the recent developments of photonic crystal (PhC)-based devices for sensing and imaging, with a particular emphasis on biosensors. We focus on two main classes of devices, namely sensors based on PhC cavities and those on guided mode resonances (GMRs). This distinction is able to capture the richness of possibilities that PhCs are able to offer in this space. We present recent examples highlighting applications where PhCs can offer new capabilities, open up new applications or enable improved performance, with a clear emphasis on the different types of structures and photonic functions. We provide a critical comparison between cavity-based devices and GMR devices by highlighting strengths and weaknesses. We also compare PhC technologies and their sensing mechanism to surface plasmon resonance, microring resonators and integrated interferometric sensors.

Metal Oxide Nanostructures and Their Gas Sensing Properties: A Review

PubMed Central

Sun, Yu-Feng; Liu, Shao-Bo; Meng, Fan-Li; Liu, Jin-Yun; Jin, Zhen; Kong, Ling-Tao; Liu, Jin-Huai

2012-01-01

Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called “small size effect”, yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given. PMID:22736968

Metal oxide nanostructures and their gas sensing properties: a review.

PubMed

Sun, Yu-Feng; Liu, Shao-Bo; Meng, Fan-Li; Liu, Jin-Yun; Jin, Zhen; Kong, Ling-Tao; Liu, Jin-Huai

2012-01-01

Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called "small size effect", yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given.

Development of self-sensing BFRP bars with distributed optic fiber sensors

NASA Astrophysics Data System (ADS)

Tang, Yongsheng; Wu, Zhishen; Yang, Caiqian; Shen, Sheng; Wu, Gang; Hong, Wan

2009-03-01

In this paper, a new type of self-sensing basalt fiber reinforced polymer (BFRP) bars is developed with using the Brillouin scattering-based distributed optic fiber sensing technique. During the fabrication, optic fiber without buffer and sheath as a core is firstly reinforced through braiding around mechanically dry continuous basalt fiber sheath in order to survive the pulling-shoving process of manufacturing the BFRP bars. The optic fiber with dry basalt fiber sheath as a core embedded further in the BFRP bars will be impregnated well with epoxy resin during the pulling-shoving process. The bond between the optic fiber and the basalt fiber sheath as well as between the basalt fiber sheath and the FRP bar can be controlled and ensured. Therefore, the measuring error due to the slippage between the optic fiber core and the coating can be improved. Moreover, epoxy resin of the segments, where the connection of optic fibers will be performed, is uncured by isolating heat from these parts of the bar during the manufacture. Consequently, the optic fiber in these segments of the bar can be easily taken out, and the connection between optic fibers can be smoothly carried out. Finally, a series of experiments are performed to study the sensing and mechanical properties of the propose BFRP bars. The experimental results show that the self-sensing BFRP bar is characterized by not only excellent accuracy, repeatability and linearity for strain measuring but also good mechanical property.

Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling.

PubMed

Walz, Yvonne; Wegmann, Martin; Leutner, Benjamin; Dech, Stefan; Vounatsou, Penelope; N'Goran, Eliézer K; Raso, Giovanna; Utzinger, Jürg

2015-11-30

Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d'Ivoire using high- and moderate-resolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixel-based modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

Changes in frontal-parietal activation and math skills performance following adaptive number sense training: Preliminary results from a pilot study

PubMed Central

Kesler, Shelli R.; Sheau, Kristen; Koovakkattu, Della; Reiss, Allan L.

2011-01-01

Number sense is believed to be critical for math development. It is putatively an implicitly learned skill and may therefore have limitations in terms of being explicitly trained, particularly in individuals with altered neurodevelopment. A case series study was conducted using an adaptive, computerized program that focused on number sense and general problem solving skills was designed to investigate training effects on performance as well as brain function in a group of children with Turner syndrome who are at risk for math difficulties and altered development of math-related brain networks. Standardized measurements of math and math-related cognitive skills as well as functional magnetic resonance imaging (fMRI) were used to assess behavioral and neurobiologic outcomes following training. Participants demonstrated significantly increased basic math skills, including number sense, and calculation as well as processing speed, cognitive flexibility and visual-spatial processing skills. With the exception of calculation, increased scores also were clinically significant (i.e. recovered) based on reliable change analysis. Participants additionally demonstrated significantly increased bilateral parietal lobe activation and decreased frontal-striatal and mesial temporal activation following the training program. These findings show proof of concept for an accessible training approach that may be potentially associated with improved number sense, math and related skills, as well as functional changes in math-related neural systems, even among individuals at risk for altered brain development. PMID:21714745

Instrumentation for optical remote sensing from space; Proceedings of the Meeting, Cannes, France, November 27-29, 1985

NASA Technical Reports Server (NTRS)

Seeley, John S. (Editor); Lear, John W. (Editor); Russak, Sidney L. (Editor); Monfils, Andre (Editor)

1986-01-01

Papers are presented on such topics as the development of the Imaging Spectrometer for Shuttle and space platform applications; the in-flight calibration of pushbroom remote sensing instruments for the SPOT program; buttable detector arrays for 1.55-1.7 micron imaging; the design of the Improved Stratospheric and Mesospheric Sounder on the Upper Atmosphere Research Satellite; and SAGE II design and in-orbit performance. Consideration is also given to the Shuttle Imaging Radar-B/C instruments; the Venus Radar Mapper multimode radar system design; various ISO instruments (ISOCAM, ISOPHOT, and SWS and LWS); and instrumentation for the Space Infrared Telescope Facility.

Automated extraction of metadata from remotely sensed satellite imagery

NASA Technical Reports Server (NTRS)

Cromp, Robert F.

1991-01-01

The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.

Gravimetric chemical sensors based on silica-based mesoporous organic-inorganic hybrids.

PubMed

Xu, Jiaqiang; Zheng, Qi; Zhu, Yongheng; Lou, Huihui; Xiang, Qun; Cheng, Zhixuan

2014-09-01

Silica-based mesoporous organic-inorganic hybrid material modified quartz crystal microbalance (QCM) sensors have been examined for their ability to achieve highly sensitive and selective detection. Mesoporous silica SBA-15 serves as an inorganic host with large specific surface area, facilitating gas adsorption, and thus leads to highly sensitive response; while the presence of organic functional groups contributes to the greatly improved specific sensing property. In this work, we summarize our efforts in the rational design and synthesis of novel sensing materials for the detection of hazardous substances, including simulant nerve agent, organic vapor, and heavy metal ion, and develop high-performance QCM-based chemical sensors.

Bio-inspired sensing and control for disturbance rejection and stabilization

NASA Astrophysics Data System (ADS)

Gremillion, Gregory; Humbert, James S.

2015-05-01

The successful operation of small unmanned aircraft systems (sUAS) in dynamic environments demands robust stability in the presence of exogenous disturbances. Flying insects are sensor-rich platforms, with highly redundant arrays of sensors distributed across the insect body that are integrated to extract rich information with diminished noise. This work presents a novel sensing framework in which measurements from an array of accelerometers distributed across a simulated flight vehicle are linearly combined to directly estimate the applied forces and torques with improvements in SNR. In simulation, the estimation performance is quantified as a function of sensor noise level, position estimate error, and sensor quantity.

Evaluation of Flexible Force Sensors for Pressure Monitoring in Treatment of Chronic Venous Disorders.

PubMed

Parmar, Suresh; Khodasevych, Iryna; Troynikov, Olga

2017-08-21

The recent use of graduated compression therapy for treatment of chronic venous disorders such as leg ulcers and oedema has led to considerable research interest in flexible and low-cost force sensors. Properly applied low pressure during compression therapy can substantially improve the treatment of chronic venous disorders. However, achievement of the recommended low pressure levels and its accurate determination in real-life conditions is still a challenge. Several thin and flexible force sensors, which can also function as pressure sensors, are commercially available, but their real-life sensing performance has not been evaluated. Moreover, no researchers have reported information on sensor performance during static and dynamic loading within the realistic test conditions required for compression therapy. This research investigated the sensing performance of five low-cost commercial pressure sensors on a human-leg-like test apparatus and presents quantitative results on the accuracy and drift behaviour of these sensors in both static and dynamic conditions required for compression therapy. Extensive experimental work on this new human-leg-like test setup demonstrated its utility for evaluating the sensors. Results showed variation in static and dynamic sensing performance, including accuracy and drift characteristics. Only one commercially available pressure sensor was found to reliably deliver accuracy of 95% and above for all three test pressure points of 30, 50 and 70 mmHg.

Evaluation of Flexible Force Sensors for Pressure Monitoring in Treatment of Chronic Venous Disorders

PubMed Central

Parmar, Suresh; Khodasevych, Iryna; Troynikov, Olga

2017-01-01

The recent use of graduated compression therapy for treatment of chronic venous disorders such as leg ulcers and oedema has led to considerable research interest in flexible and low-cost force sensors. Properly applied low pressure during compression therapy can substantially improve the treatment of chronic venous disorders. However, achievement of the recommended low pressure levels and its accurate determination in real-life conditions is still a challenge. Several thin and flexible force sensors, which can also function as pressure sensors, are commercially available, but their real-life sensing performance has not been evaluated. Moreover, no researchers have reported information on sensor performance during static and dynamic loading within the realistic test conditions required for compression therapy. This research investigated the sensing performance of five low-cost commercial pressure sensors on a human-leg-like test apparatus and presents quantitative results on the accuracy and drift behaviour of these sensors in both static and dynamic conditions required for compression therapy. Extensive experimental work on this new human-leg-like test setup demonstrated its utility for evaluating the sensors. Results showed variation in static and dynamic sensing performance, including accuracy and drift characteristics. Only one commercially available pressure sensor was found to reliably deliver accuracy of 95% and above for all three test pressure points of 30, 50 and 70 mmHg. PMID:28825672

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

The suitability of remotely sensed soil moisture for improving operational flood forecasting

NASA Astrophysics Data System (ADS)

Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

2013-11-01

We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model for flood predictions with lead times up to 10 days. For this study, satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF, are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more data is assimilated into the system and the best performance is achieved with the assimilation of both discharge and satellite observations. The additional gain is highest when discharge observations from both upstream and downstream areas are used in combination with the soil moisture data. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

Improvements to an earth observing statistical performance model with applications to LWIR spectral variability

NASA Astrophysics Data System (ADS)

Zhao, Runchen; Ientilucci, Emmett J.

2017-05-01

Hyperspectral remote sensing systems provide spectral data composed of hundreds of narrow spectral bands. Spectral remote sensing systems can be used to identify targets, for example, without physical interaction. Often it is of interested to characterize the spectral variability of targets or objects. The purpose of this paper is to identify and characterize the LWIR spectral variability of targets based on an improved earth observing statistical performance model, known as the Forecasting and Analysis of Spectroradiometric System Performance (FASSP) model. FASSP contains three basic modules including a scene model, sensor model and a processing model. Instead of using mean surface reflectance only as input to the model, FASSP transfers user defined statistical characteristics of a scene through the image chain (i.e., from source to sensor). The radiative transfer model, MODTRAN, is used to simulate the radiative transfer based on user defined atmospheric parameters. To retrieve class emissivity and temperature statistics, or temperature / emissivity separation (TES), a LWIR atmospheric compensation method is necessary. The FASSP model has a method to transform statistics in the visible (ie., ELM) but currently does not have LWIR TES algorithm in place. This paper addresses the implementation of such a TES algorithm and its associated transformation of statistics.

Impact of SenseCam on memory, identity and mood in Korsakoff's syndrome: a single case experimental design study.

PubMed

Svanberg, Jenny; Evans, Jonathan J

2014-01-01

This study aimed to investigate the impact of SenseCam, a wearable, automatic camera, on subjective mood and identity in a patient with severe memory impairment due to Korsakoff's syndrome. It was hypothesised that SenseCam would improve Ms A's mood and identity through enhancing recall of autobiographical memories of recent events, therefore supporting a coherent sense of self; the lack of which was contributing to Ms A's mood deterioration. An ABA single case experimental design investigated whether using SenseCam to record regular activities impacted on Ms A's mood and identity. Ms A experienced improved recall for events recorded using SenseCam, and showed improvement on subjective ratings of identity. However, a corresponding improvement in mood was not seen, and the study was ended early at Ms A's request. Qualitative information was gathered to explore Ms A's experience of the study, and investigate psychosocial factors that may have impacted on the use of SenseCam. SenseCam may be of significant use as a compensatory memory aid for people with Korsakoff's syndrome and other types of alcohol-related brain damage (ARBD), but acceptance of memory impairment and consistent support may be among the factors required to support the use of such assistive technologies in a community setting.

Ergonomics and design: its principles applied in the industry.

PubMed

Tavares, Ademario Santos; Silva, Francisco Nilson da

2012-01-01

Industrial Design encompasses both product development and optimization of production process. In this sense, Ergonomics plays a fundamental role, because its principles, methods and techniques can help operators to carry out their tasks most successfully. A case study carried out in an industry shows that the interaction among Design, Production Engineering and Materials Engineering departments may improve some aspects concerned security, comfort, efficiency and performance. In this process, Ergonomics had shown to be of essential importance to strategic decision making to the improvement of production section.

Principal Concerns in Wisconsin: Focus on Future Leaders for Rural Schools. Data Brief

ERIC Educational Resources Information Center

Martin, Katherine

2013-01-01

Common sense and recent research make it clear that schools cannot be successful without strong principals. Strong principals help improve student performance in many ways, from shaping a school's mission and culture to hiring, developing, and retaining its teachers. Even so, principals often get short shrift in today's debates about human capital…

A Sense of Balance: District Aligns Personalized Learning with School and System Goals

ERIC Educational Resources Information Center

Donsky, Debbie; Witherow, Kathy

2015-01-01

This article addresses the challenge of personalizing learning while also ensuring alignment with system and school improvement plans. Leaders of the York Region District School Board in Ontario knew that what took their high-performing school district from good to great would not take it from great to excellent. The district's early model of…

Exploring the Impact of Undergraduate Intramural Sports on Undergraduate Students' Perceived Sense of Community: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Penland, Nathan Paul

2017-01-01

Research has shown benefits to the student experience for college students when they participate in intramural sports on university campuses. These benefits include improved physical and social health as well as academic performance. This non-experimental, predictive correlational study sought to understand if a relationship exists between the…

Development of an ultrahigh-performance infrared detector platform for advanced spectroscopic sensing systems

NASA Astrophysics Data System (ADS)

Jain, Manish; Wicks, Gary; Marshall, Andrew; Craig, Adam; Golding, Terry; Hossain, Khalid; McEwan, Ken; Howle, Chris

2014-05-01

Laser-based stand-off sensing of threat agents (e.g. explosives, toxic industrial chemicals or chemical warfare agents), by detection of distinct infrared spectral absorption signature of these materials, has made significant advances recently. This is due in part to the availability of infrared and terahertz laser sources with significantly improved power and tunability. However, there is a pressing need for a versatile, high performance infrared sensor that can complement and enhance the recent advances achieved in laser technology. This work presents new, high performance infrared detectors based on III-V barrier diodes. Unipolar barrier diodes, such as the nBn, have been very successful in the MWIR using InAs(Sb)-based materials, and in the MWIR and LWIR using type-II InAsSb/InAs superlattice-based materials. This work addresses the extension of the barrier diode architecture into the SWIR region, using GaSb-based and InAs-based materials. The program has resulted in detectors with unmatched performance in the 2-3 μm spectral range. Temperature dependent characterization has shown dark currents to be diffusion limited and equal to, or within a factor of 5, of the Rule 07 expression for Auger-limited HgCdTe detectors. Furthermore, D* values are superior to those of existing detectors in the 2-3 μm band. Of particular significance to spectroscopic sensing systems is the ability to have near-background limited performance at operation temperatures compatible with robust and reliable solid state thermoelectric coolers.

Development of nanostructured antireflection coatings for infrared technologies and applications

NASA Astrophysics Data System (ADS)

Pethuraja, Gopal G.; Zeller, John W.; Welser, Roger E.; Efstathiadis, Harry; Haldar, Pradeep; Wijewarnasuriya, Priyalal S.; Dhar, Nibir K.; Sood, Ashok K.

2017-09-01

Infrared (IR) sensing technologies and systems operating from the near-infrared (NIR) to long-wave infrared (LWIR) spectra are being developed for a variety of defense and commercial systems applications. Reflection losses affecting a significant portion of the incident signal limits the performance of IR sensing systems. One of the critical technologies that will overcome this limitation and enhance the performance of IR sensing systems is the development of advanced antireflection (AR) coatings. Magnolia is actively involved in the development and advancement of ultrahigh performance AR coatings for a wide variety of defense and commercial applications. Ultrahigh performance nanostructured AR coatings have been demonstrated for UV to LWIR spectral bands using various substrates. The AR coatings enhance the optical transmission through optical components and devices by significantly minimizing reflection losses, a substantial improvement over conventional thin-film AR coating technologies. Nanostructured AR coatings are fabricated using a tunable self-assembly process on substrates that are transparent for a given spectrum of interest ranging from UV to LWIR. The nanostructured multilayer structures have been designed, developed and optimized for various optoelectronic applications. The optical properties of the AR-coated optical components and sensor substrates have been measured and fine-tuned to achieve a predicted high level of performance of the coatings. In this paper, we review our latest work on high quality nanostructure-based AR coatings, including recent efforts towards the development of nanostructured AR coatings on IR-transparent substrates.

NDSI products system based on Hadoop platform

NASA Astrophysics Data System (ADS)

Zhou, Yan; Jiang, He; Yang, Xiaoxia; Geng, Erhui

2015-12-01

Snow is solid state of water resources on earth, and plays an important role in human life. Satellite remote sensing is significant in snow extraction with the advantages of cyclical, macro, comprehensiveness, objectivity, timeliness. With the continuous development of remote sensing technology, remote sensing data access to the trend of multiple platforms, multiple sensors and multiple perspectives. At the same time, in view of the remote sensing data of compute-intensive applications demand increase gradually. However, current the producing system of remote sensing products is in a serial mode, and this kind of production system is used for professional remote sensing researchers mostly, and production systems achieving automatic or semi-automatic production are relatively less. Facing massive remote sensing data, the traditional serial mode producing system with its low efficiency has been difficult to meet the requirements of mass data timely and efficient processing. In order to effectively improve the production efficiency of NDSI products, meet the demand of large-scale remote sensing data processed timely and efficiently, this paper build NDSI products production system based on Hadoop platform, and the system mainly includes the remote sensing image management module, NDSI production module, and system service module. Main research contents and results including: (1)The remote sensing image management module: includes image import and image metadata management two parts. Import mass basis IRS images and NDSI product images (the system performing the production task output) into HDFS file system; At the same time, read the corresponding orbit ranks number, maximum/minimum longitude and latitude, product date, HDFS storage path, Hadoop task ID (NDSI products), and other metadata information, and then create thumbnails, and unique ID number for each record distribution, import it into base/product image metadata database. (2)NDSI production module: includes the index calculation, production tasks submission and monitoring two parts. Read HDF images related to production task in the form of a byte stream, and use Beam library to parse image byte stream to the form of Product; Use MapReduce distributed framework to perform production tasks, at the same time monitoring task status; When the production task complete, calls remote sensing image management module to store NDSI products. (3)System service module: includes both image search and DNSI products download. To image metadata attributes described in JSON format, return to the image sequence ID existing in the HDFS file system; For the given MapReduce task ID, package several task output NDSI products into ZIP format file, and return to the download link (4)System evaluation: download massive remote sensing data and use the system to process it to get the NDSI products testing the performance, and the result shows that the system has high extendibility, strong fault tolerance, fast production speed, and the image processing results with high accuracy.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

EDITORIAL: Nanotechnology impact on sensors Nanotechnology impact on sensors

NASA Astrophysics Data System (ADS)

Brugger, Jürgen

2009-10-01

A sensor is a device that responds to a stimulus by generating a functional output induced by a change in some intrinsic properties. We are surrounded by sensors and sensing networks that monitor a multitude of parameters in view of enhancing our safety and quality of life. Sensors assist us in health care and diagnostics, they monitor our environment, our aeroplanes and automobiles, our mobile phones, game consoles and watches, and last but not least, many of our human body functions. Modern sensing systems have greatly benefited in recent decades from advances in microelectronics and microengineering, mainly in view of making sensors smaller, cheaper, more sensitive, more selective, and with a better signal-to-noise ratio, following classical scaling rules. So how about nanotechnology-enabled sensing? Nanoscale features have a great impact on many (though not all) sensing systems, in particular where the surface-to-volume ratio plays a fundamental role, such as in certain chemical and gas sensors. The high surface-to-volume ratios of nanoporous and nanostructured materials have led to their implementation in sensing systems since sensing research first began to engage with the nanotechnology. The surface plasmon resonances of nanostructures have also enriched the scope for developing novel sensing devices. On the other hand, sensors where bulk properties dominate, such as inertial sensors, are less likely to benefit from extreme scaling. Advances in thin film techniques and chemical synthesis have allowed material properties to be tailored to sensing requirements for enhanced performance. These bottom-up fabrication techniques enable parallel fabrication of ordered nanostructures, often in domain-like areas with molecular precision. At the same time the progress in top-down methods such as scanning probe lithography, nanoimprint lithography, soft-lithography and stencil lithography have also facilitated research into sensing and actuating nanotechnology. Although radically different from each other, these techniques represent a formidable toolset for structuring materials at the nanoscale in a multitude of fashions. The availability of these new nanopatterning techniques are increasingly implemented in the manufacturing of advanced sensor systems, and we can expect in the next decade an increased emergence of micro- and nanosensor systems that implement novel nano-functionalities thanks to cost-effective fabrication. Moreover, some of these techniques are desktop tools that can be used on your kitchen table at home. Thus, over the past 20 years we have witnessed a democratization of nanotechnology. More and more researchers, engineers, and even schoolchildren, can benefit from and use these new methods and devise novel applications for nanosystems. This is certainly beneficial to expediting a further dramatic increase in knowledge and the development of actual devices and applications that put gains in our understanding of nanosystems into practice. Nanotechnology is a relatively young discipline compared to classical engineering, and it is inherently interdisciplinary. It seems that in many fields we are actually just beginning to venture into these new dimensions. Challenges remain, however, in all aspects of nanotechnology. We need to improve imaging performance by enabling faster (video rate) coverage of larger surfaces, eventually down to the molecular scale. We also need to perfect nanopatterning methods to improve resolution, overlay and throughput capabilities. Future nanomanufacturing will most likely rely on combinations of top-down engineering and bottom-up self-assembly. Last but not least, we need to find ways for the mutual integration of multiple length-scale devices (nano/micro/macro) so that we can program a 'nano-functionality' into a microsystem exactly where it is needed. Such improvements will ultimately lead to improved sensors and contribute not only to improvements in our quality of life but also to building energy-saving systems that can be fabricated with low-waste manufacturing methods.

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.

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Characterization and Design of Spiral Frequency Steerable Acoustic Transducers

NASA Astrophysics Data System (ADS)

Repale, Rohan

Structural Health Monitoring (SHM) is an emerging research area devoted to improving the safety and maintainability of civil structures. Guided wave structural testing method is an effective approach used for SHM of plate-like structures using piezoelectric transducers. These transducers are attached to the surface of the structure and are capable of sensing its health by using surface waves. Transducers with beam steering i.e. electronic scanning capabilities can perform surface interrogation with higher precision and ease. A frequency steerable acoustic transducer (FSAT) is capable of beam steering and directional surface wave sensing to detect and localize damage in structures. The objective of this research is to further explore the possibilities of FSAT technology by designing and testing new FSAT designs. The beam steering capability of FSAT can be controlled by manipulating its design parameters. These design parameters therefore play a significant role in FSAT's performance. Studying the design parameters and documenting the performance improvements based on parameter variation is the primary goal of this research. Design and characterization of spiral FSAT was performed and results were simulated. Array FSAT documented results were validated. Modified designs were modeled based on design parameter variations. Characterization of these designs was done and their performance was recorded. Plate simulation results confirm direct relationship between design parameters and beam steering. A set of guidelines for future designs was also proposed. Two designs developed based on the set guidelines were sent to our collaborator Genziko Inc. for fabrication.

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

Mene, Ravindra U.; School of Physical Sciences, Swami Ramanand Teerth Marathwada University, Nanded 431606, M.S.; Mahabole, Megha P.

Highlights: • We report improved gas sensing and dielectric characteristics of Fe ion exchanged HAp films. • Fe doped HAp film shows maximum gas response at relatively lower temperature. • Response and gas uptake capacity of sensors is improved for appropriate amount of Fe ions in HAp matrix. • Fe-HAp films exhibit remarkable improvement in dielectric properties compared to pure HAp. • Fe doped HAp films show significant improvement in gas sensing as well as in dielectric properties. - Abstract: In the present work Fe doped hydroxyapatite (Fe-HAp) thick films has been successfully utilized to improve the gas sensing asmore » well as its dielectric properties. Initially, HAp nano powder is synthesized by chemical precipitation process and later on Fe ions are doped in HAp by ion exchange process. Structural and morphological modifications are observed by means of X-ray diffraction and scanning electron microscopy analysis. The sensing parameters such as operating temperature, response/recovery time and gas uptake capacity are experimentally determined. The Fe-HAp (0.05 M) film shows improved CO and CO{sub 2} gas sensing capacity at lower operating temperature compared to pure HAp. Moreover, variation of dielectric constant and dielectric loss for pure and Fe-HAp thick films are studied as a function of frequency in the range of 10 Hz–1 MHz. The study reveals that Fe doped HAp thick films improve the sensing and dielectric characteristics as compared to pure HAp.« less

On-board error correction improves IR earth sensor accuracy

NASA Astrophysics Data System (ADS)

Alex, T. K.; Kasturirangan, K.; Shrivastava, S. K.

1989-10-01

Infra-red earth sensors are used in satellites for attitude sensing. Their accuracy is limited by systematic and random errors. The sources of errors in a scanning infra-red earth sensor are analyzed in this paper. The systematic errors arising from seasonal variation of infra-red radiation, oblate shape of the earth, ambient temperature of sensor, changes in scan/spin rates have been analyzed. Simple relations are derived using least square curve fitting for on-board correction of these errors. Random errors arising out of noise from detector and amplifiers, instability of alignment and localized radiance anomalies are analyzed and possible correction methods are suggested. Sun and Moon interference on earth sensor performance has seriously affected a number of missions. The on-board processor detects Sun/Moon interference and corrects the errors on-board. It is possible to obtain eight times improvement in sensing accuracy, which will be comparable with ground based post facto attitude refinement.

Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks

PubMed Central

Wang, Dawei; Ren, Pinyi; Du, Qinghe; Sun, Li; Wang, Yichen

2016-01-01

The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN’s interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users’ activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN’s transmission rate by taking into account the spectrum sensing errors. Then, the SN’s transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN’s transmission outage probability. Simulation results show that: (1) the performance of the SN’s average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy. PMID:27897988

Effect of Vertical Annealing on the Nitrogen Dioxide Response of Organic Thin Film Transistors

PubMed Central

Hou, Sihui; Zhuang, Xinming; Yang, Zuchong

2018-01-01

Nitrogen dioxide (NO2) sensors based on organic thin-film transistors (OTFTs) were fabricated by conventional annealing (horizontal) and vertical annealing processes of organic semiconductor (OSC) films. The NO2 responsivity of OTFTs to 15 ppm of NO2 is 1408% under conditions of vertical annealing and only 72% when conventional annealing is applied. Moreover, gas sensors obtained by vertical annealing achieve a high sensing performance of 589% already at 1 ppm of NO2, while showing a preferential response to NO2 compared with SO2, NH3, CO, and H2S. To analyze the mechanism of performance improvement of OTFT gas sensors, the morphologies of 6,13-bis(triisopropylsilylethynyl)-pentacene (TIPS-pentacene) films were characterized by atomic force microscopy (AFM) in tapping mode. The results show that, in well-aligned TIPS-pentacene films, a large number of effective grain boundaries inside the conducting channel contribute to the enhancement of NO2 gas sensing performance. PMID:29596331

On the performance of energy detection-based CR with SC diversity over IG channel

NASA Astrophysics Data System (ADS)

Verma, Pappu Kumar; Soni, Sanjay Kumar; Jain, Priyanka

2017-12-01

Cognitive radio (CR) is a viable 5G technology to address the scarcity of the spectrum. Energy detection-based sensing is known to be the simplest method as far as hardware complexity is concerned. In this paper, the performance of spectrum sensing-based energy detection technique in CR networks over inverse Gaussian channel for selection combining diversity technique is analysed. More specifically, accurate analytical expressions for the average detection probability under different detection scenarios such as single channel (no diversity) and with diversity reception are derived and evaluated. Further, the detection threshold parameter is optimised by minimising the probability of error over several diversity branches. The results clearly show the significant improvement in the probability of detection when optimised threshold parameter is applied. The impact of shadowing parameters on the performance of energy detector is studied in terms of complimentary receiver operating characteristic curve. To verify the correctness of our analysis, the derived analytical expressions are corroborated via exact result and Monte Carlo simulations.

Molecular manipulations for enhancing luminescent bioreporters performance in the detection of toxic chemicals.

PubMed

Yagur-Kroll, Sharon; Belkin, Shimshon

2014-01-01

Microbial whole-cell bioreporters are genetically modified microorganisms that produce a quantifiable output in response to the presence of toxic chemicals or other stress factors. These bioreporters harbor a genetic fusion between a sensing element (usually a gene regulatory element responsive to the target) and a reporter element, the product of which may be quantitatively monitored either by its presence or by its activity. In this chapter we review genetic manipulations undertaken in order to improve bioluminescent bioreporter performance by increasing luminescent output, lowering the limit of detection, and shortening the response time. We describe molecular manipulations applied to all aspects of whole-cell bioreporters: the host strain, the expression system, the sensing element, and the reporter element. The molecular construction of whole-cell luminescent bioreporters, harboring fusions of gene promoter elements to reporter genes, has been around for over three decades; in most cases, these two genetic elements are combined "as is." This chapter outlines diverse molecular manipulations for enhancing the performance of such sensors.

Urban Spatial Ecological Performance Based on the Data of Remote Sensing of Guyuan

NASA Astrophysics Data System (ADS)

Ren, X.-J.; Chen, X.-J.; Ma, Q.

2018-04-01

The evolution analysis of urban landuse and spatial ecological performance are necessary and useful to recognizing the stage of urban development and revealing the regularity and connotation of urban spatial expansion. Moreover, it lies in the core that should be exmined in the urban sustainable development. In this paper, detailed information has been acquired from the high-resolution satellite imageries of Guyuan, China case study. With the support of GIS, the land-use mapping information and the land cover changes are analyzed, and the process of urban spatial ecological performance evolution by the hierarchical methodology is explored. Results demonstrate that in the past 11 years, the urban spatial ecological performance show an improved process with the dramatic landcover change in Guyuan. Firstly, the landuse structure of Guyuan changes significantly and shows an obvious stage characteristic. Secondly, the urban ecological performance of Guyuan continues to be optimized over the 11 years. Thirdly, the findings suggest that a dynamic monitoring mechanism of urban land use based on high-resolution remote sensing data should be established in urban development, and the rational development of urban land use should be guided by the spatial ecological performance as the basic value orientation.

Improving proprioceptive deficits after stroke through robot-assisted training of the upper limb: a pilot case report study.

PubMed

Colombo, R; Sterpi, I; Mazzone, A; Delconte, C; Pisano, F

2016-01-01

The purpose of this study was to determine whether a conventional robot-assisted therapy of the upper limb was able to improve proprioception and motor recovery of an individual after stroke who exhibited proprioceptive deficits. After robotic sensorimotor training, significant changes were observed in kinematic performance variables. Two quantitative parameters evaluating position sense improved after training. Range of motion during shoulder and wrist flexion improved, but only wrist flexion remained improved at 3-month follow-up. These preliminary results suggest that intensive robot-aided rehabilitation may play an important role in the recovery of sensory function. However, further studies are required to confirm these data.

High sensitivity and accuracy dissolved oxygen (DO) detection by using PtOEP/poly(MMA-co-TFEMA) sensing film.

PubMed

Zhang, Ke; Zhang, Honglin; Wang, Ying; Tian, Yanqing; Zhao, Jiupeng; Li, Yao

2017-01-05

Fluorinated acrylate polymer has received great interest in recent years due to its extraordinary characteristics such as high oxygen permeability, good stability, low surface energy and refractive index. In this work, platinum octaethylporphyrin/poly(methylmethacrylate-co-trifluoroethyl methacrylate) (PtOEP/poly(MMA-co-TFEMA)) oxygen sensing film was prepared by the immobilizing of PtOEP in a poly(MMA-co-TFEMA) matrix and the technological readiness of optical properties was established based on the principle of luminescence quenching. It was found that the oxygen-sensing performance could be improved by optimizing the monomer ratio (MMA/TFEMA=1:1), tributylphosphate(TBP, 0.05mL) and PtOEP (5μg) content. Under this condition, the maximum quenching ratio I0/I100 of the oxygen sensing film is obtained to be about 8.16, Stern-Volmer equation is I0/I=1.003+2.663[O2] (R(2)=0.999), exhibiting a linear relationship, good photo-stability, high sensitivity and accuracy. Finally, the synthesized PtOEP/poly(MMA-co-TFEMA) sensing film was used for DO detection in different water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

High sensitivity and accuracy dissolved oxygen (DO) detection by using PtOEP/poly(MMA-co-TFEMA) sensing film

NASA Astrophysics Data System (ADS)

Zhang, Ke; Zhang, Honglin; Wang, Ying; Tian, Yanqing; Zhao, Jiupeng; Li, Yao

2017-01-01

Fluorinated acrylate polymer has received great interest in recent years due to its extraordinary characteristics such as high oxygen permeability, good stability, low surface energy and refractive index. In this work, platinum octaethylporphyrin/poly(methylmethacrylate-co-trifluoroethyl methacrylate) (PtOEP/poly(MMA-co-TFEMA)) oxygen sensing film was prepared by the immobilizing of PtOEP in a poly(MMA-co-TFEMA) matrix and the technological readiness of optical properties was established based on the principle of luminescence quenching. It was found that the oxygen-sensing performance could be improved by optimizing the monomer ratio (MMA/TFEMA = 1:1), tributylphosphate(TBP, 0.05 mL) and PtOEP (5 μg) content. Under this condition, the maximum quenching ratio I0/I100 of the oxygen sensing film is obtained to be about 8.16, Stern-Volmer equation is I0/I = 1.003 + 2.663[O2] (R2 = 0.999), exhibiting a linear relationship, good photo-stability, high sensitivity and accuracy. Finally, the synthesized PtOEP/poly(MMA-co-TFEMA) sensing film was used for DO detection in different water samples.

Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

2015-04-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

Kalman/Map filtering-aided fast normalized cross correlation-based Wi-Fi fingerprinting location sensing.

PubMed

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-11-13

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

PubMed Central

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-01-01

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results. PMID:24233027

Contribution of non-negative matrix factorization to the classification of remote sensing images

NASA Astrophysics Data System (ADS)

Karoui, M. S.; Deville, Y.; Hosseini, S.; Ouamri, A.; Ducrot, D.

2008-10-01

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. The classification process requires some pre-processing, especially for data size reduction. The most usual technique is Principal Component Analysis. Another approach consists in regarding each pixel of the multispectral image as a mixture of pure elements contained in the observed area. Using Blind Source Separation (BSS) methods, one can hope to unmix each pixel and to perform the recognition of the classes constituting the observed scene. Our contribution consists in using Non-negative Matrix Factorization (NMF) combined with sparse coding as a solution to BSS, in order to generate new images (which are at least partly separated images) using HRV SPOT images from Oran area, Algeria). These images are then used as inputs of a supervised classifier integrating textural information. The results of classifications of these "separated" images show a clear improvement (correct pixel classification rate improved by more than 20%) compared to classification of initial (i.e. non separated) images. These results show the contribution of NMF as an attractive pre-processing for classification of multispectral remote sensing imagery.

Simple functionalization method for single conical pores with a polydopamine layer

NASA Astrophysics Data System (ADS)

Horiguchi, Yukichi; Goda, Tatsuro; Miyahara, Yuji

2018-04-01

Resistive pulse sensing (RPS) is an interesting analytical system in which micro- to nanosized pores are used to evaluate particles or small analytes. Recently, molecular immobilization techniques to improve the performance of RPS have been reported. The problem in functionalization for RPS is that molecular immobilization by chemical reaction is restricted by the pore material type. Herein, a simple functionalization is performed using mussel-inspired polydopamine as an intermediate layer to connect the pore material with functional molecules.

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.

Toward Modular Soft Robotics: Proprioceptive Curvature Sensing and Sliding-Mode Control of Soft Bidirectional Bending Modules.

PubMed

Luo, Ming; Skorina, Erik H; Tao, Weijia; Chen, Fuchen; Ozel, Selim; Sun, Yinan; Onal, Cagdas D

2017-06-01

Real-world environments are complex, unstructured, and often fragile. Soft robotics offers a solution for robots to safely interact with the environment and human coworkers, but suffers from a host of challenges in sensing and control of continuously deformable bodies. To overcome these challenges, this article considers a modular soft robotic architecture that offers proprioceptive sensing of pressure-operated bending actuation modules. We present integrated custom magnetic curvature sensors embedded in the neutral axis of bidirectional bending actuators. We describe our recent advances in the design and fabrication of these modules to improve the reliability of proprioceptive curvature feedback over our prior work. In particular, we study the effect of dimensional parameters on improving the linearity of curvature measurements. In addition, we present a sliding-mode controller formulation that drives the binary solenoid valve states directly, giving the control system the ability to hold the actuator steady without continuous pressurization and depressurization. In comparison to other methods, this control approach does not rely on pulse width modulation and hence offers superior dynamic performance (i.e., faster response rates). Our experimental results indicate that the proposed soft robotic modules offer a large range of bending angles with monotonic and more linear embedded curvature measurements, and that the direct sliding-mode control system exhibits improved bandwidth and a notable reduction in binary valve actuation operations compared to our earlier iterative sliding-mode controller.

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.

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

NASA Astrophysics Data System (ADS)

Mojica, Edson; Pertuz, Said; Arguello, Henry

2017-12-01

One of the main challenges in Computed Tomography (CT) is obtaining accurate reconstructions of the imaged object while keeping a low radiation dose in the acquisition process. In order to solve this problem, several researchers have proposed the use of compressed sensing for reducing the amount of measurements required to perform CT. This paper tackles the problem of designing high-resolution coded apertures for compressed sensing computed tomography. In contrast to previous approaches, we aim at designing apertures to be used with low-resolution detectors in order to achieve super-resolution. The proposed method iteratively improves random coded apertures using a gradient descent algorithm subject to constraints in the coherence and homogeneity of the compressive sensing matrix induced by the coded aperture. Experiments with different test sets show consistent results for different transmittances, number of shots and super-resolution factors.

Tungsten-Doped TiO2 Nanolayers with Improved CO2 Gas Sensing Properties for Environmental Applications

NASA Astrophysics Data System (ADS)

Saberi, Maliheh; Ashkarran, Ali Akbar

Tungsten-doped TiO2 gas sensors were successfully synthesized using sol-gel process and spin coating technique. The fabricated sensor was characterized by field emission scanning electron microscopy (FE-SEM), ultraviolet visible (UV-Vis) spectroscopy, transmission electron microscopy (TEM), X-Ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. Gas sensing properties of pristine and tungsten-doped TiO2 nanolayers (NLs) were probed by detection of CO2 gas. A series of experiments were conducted in order to find the optimum operating temperature of the prepared sensors and also the optimum value of tungsten concentration in TiO2 matrix. It was found that introducing tungsten into the TiO2 matrix enhanced the gas sensing performance. The maximum response was found to be (1.37) for 0.001g tungsten-doped TiO2 NLs at 200∘C as an optimum operating temperature.

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.

Compressive sensing sectional imaging for single-shot in-line self-interference incoherent holography

NASA Astrophysics Data System (ADS)

Weng, Jiawen; Clark, David C.; Kim, Myung K.

2016-05-01

A numerical reconstruction method based on compressive sensing (CS) for self-interference incoherent digital holography (SIDH) is proposed to achieve sectional imaging by single-shot in-line self-interference incoherent hologram. The sensing operator is built up based on the physical mechanism of SIDH according to CS theory, and a recovery algorithm is employed for image restoration. Numerical simulation and experimental studies employing LEDs as discrete point-sources and resolution targets as extended sources are performed to demonstrate the feasibility and validity of the method. The intensity distribution and the axial resolution along the propagation direction of SIDH by angular spectrum method (ASM) and by CS are discussed. The analysis result shows that compared to ASM the reconstruction by CS can improve the axial resolution of SIDH, and achieve sectional imaging. The proposed method may be useful to 3D analysis of dynamic systems.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

ZnO Nanoparticles/Reduced Graphene Oxide Bilayer Thin Films for Improved NH3-Sensing Performances at Room Temperature

NASA Astrophysics Data System (ADS)

Tai, Huiling; Yuan, Zhen; Zheng, Weijian; Ye, Zongbiao; Liu, Chunhua; Du, Xiaosong

2016-03-01

ZnO nanoparticles and graphene oxide (GO) thin film were deposited on gold interdigital electrodes (IDEs) in sequence via simple spraying process, which was further restored to ZnO/reduced graphene oxide (rGO) bilayer thin film by the thermal reduction treatment and employed for ammonia (NH3) detection at room temperature. rGO was identified by UV-vis absorption spectra and X-ray photoelectron spectroscope (XPS) analyses, and the adhesion between ZnO nanoparticles and rGO nanosheets might also be formed. The NH3-sensing performances of pure rGO film and ZnO/rGO bilayer films with different sprayed GO amounts were compared. The results showed that ZnO/rGO film sensors exhibited enhanced response properties, and the optimal GO amount of 1.5 ml was achieved. Furthermore, the optimal ZnO/rGO film sensor showed an excellent reversibility and fast response/recovery rate within the detection range of 10-50 ppm. Meanwhile, the sensor also displayed good repeatability and selectivity to NH3. However, the interference of water molecules on the prepared sensor is non-ignorable; some techniques should be researched to eliminate the effect of moisture in the further work. The remarkably enhanced NH3-sensing characteristics were speculated to be attributed to both the supporting role of ZnO nanoparticles film and accumulation heterojunction at the interface between ZnO and rGO. Thus, the proposed ZnO/rGO bilayer thin film sensor might give a promise for high-performance NH3-sensing applications.

Reducing the racial achievement gap: a social-psychological intervention.

PubMed

Cohen, Geoffrey L; Garcia, Julio; Apfel, Nancy; Master, Allison

2006-09-01

Two randomized field experiments tested a social-psychological intervention designed to improve minority student performance and increase our understanding of how psychological threat mediates performance in chronically evaluative real-world environments. We expected that the risk of confirming a negative stereotype aimed at one's group could undermine academic performance in minority students by elevating their level of psychological threat. We tested whether such psychological threat could be lessened by having students reaffirm their sense of personal adequacy or "self-integrity." The intervention, a brief in-class writing assignment, significantly improved the grades of African American students and reduced the racial achievement gap by 40%. These results suggest that the racial achievement gap, a major social concern in the United States, could be ameliorated by the use of timely and targeted social-psychological interventions.

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

2017-07-01

The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

Study on room temperature gas-sensing performance of CuO film-decorated ordered porous ZnO composite by In2O3 sensitization

PubMed Central

Li, Tian-tian; Bao, Na; Geng, Ai-fang; Yang, Ying; Dong, Xiang-ting

2018-01-01

For the first time, ordered mesoporous ZnO nanoparticles have been synthesized by a template method. The electroplating after chemical plating method was creatively used to form copper film on the surface of the prepared ZnO, and then a CuO film-decorated ordered porous ZnO composite (CuO/ZnO) was obtained by a high-temperature oxidation method. In2O3 was loaded into the prepared CuO film–ZnO by an ultrasonic-assisted method to sensitize the room temperature gas-sensing performance of the prepared CuO/ZnO materials. The doped In2O3 could effectively improve the gas-sensing properties of the prepared materials to nitrogen oxides (NOx) at room temperature. The 1% In2O3 doped CuO/ZnO sample (1 wt% In2O3–CuO/ZnO) showed the best gas-sensing properties whose response to 100 ppm NOx reached 82%, and the detectable minimum concentration reached 1 ppm at room temperature. The prepared materials had a good selectivity, better response, very low detection limit, and high sensitivity to NOx gas at room temperature, which would have a great development space in the gas sensor field and a great research value. PMID:29515887

Chemical Sensing for Buried Landmines - Fundamental Processes Influencing Trace Chemical Detection

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

PHELAN, JAMES M.

2002-05-01

Mine detection dogs have a demonstrated capability to locate hidden objects by trace chemical detection. Because of this capability, demining activities frequently employ mine detection dogs to locate individual buried landmines or for area reduction. The conditions appropriate for use of mine detection dogs are only beginning to emerge through diligent research that combines dog selection/training, the environmental conditions that impact landmine signature chemical vapors, and vapor sensing performance capability and reliability. This report seeks to address the fundamental soil-chemical interactions, driven by local weather history, that influence the availability of chemical for trace chemical detection. The processes evaluated include:more » landmine chemical emissions to the soil, chemical distribution in soils, chemical degradation in soils, and weather and chemical transport in soils. Simulation modeling is presented as a method to evaluate the complex interdependencies among these various processes and to establish conditions appropriate for trace chemical detection. Results from chemical analyses on soil samples obtained adjacent to landmines are presented and demonstrate the ultra-trace nature of these residues. Lastly, initial measurements of the vapor sensing performance of mine detection dogs demonstrates the extreme sensitivity of dogs in sensing landmine signature chemicals; however, reliability at these ultra-trace vapor concentrations still needs to be determined. Through this compilation, additional work is suggested that will fill in data gaps to improve the utility of trace chemical detection.« less

A versatile near-infrared asymmetric tricarbocyanine for zinc ion sensing in water.

PubMed

Menéndez, Guillermo O; López, Cecilia Samaniego; Jares-Erijman, Elizabeth A; Spagnuolo, Carla C

2013-01-01

We have synthesized a near-infrared emissive asymmetric tricarbocyanine conveniently functionalized to improve bioconjugation. The leading structure contains a versatile derivatization point at the meso position for facile radical-nucleophilic aromatic substitution. We have evaluated a DPEN (N,N-di(2-picolyl)ethylendiamine) derivative of this dye as a highly selective sensor for zinc (II) in aqueous medium, which performs in an appropriate sensitivity range for biological studies. The probe was successfully conjugated to a protein-ligand model with high affinity and specificity (biotin-streptavidin technology) rendering an excellent performance of sensing. In a general strategy to obtain sensitive probes combining fluorescent nanoparticles and molecular fluorophores, a preliminary design of a supramolecular assembly derived from the conjugation of the molecular sensor to quantum dots (QDs) was also investigated. The advantages and problems of FRET-based sensors are also discussed. © 2013 The American Society of Photobiology.

Fabrication and characterization of optical sensors using metallic core-shell thin film nanoislands for ozone detection

NASA Astrophysics Data System (ADS)

Addanki, Satish; Nedumaran, D.

2017-07-01

Core-Shell nanostructures play a vital role in the sensor field owing to their performance improvements in sensing characteristics and well-established synthesis procedures. These nanostructures can be ingeniously tuned to achieve tailored properties for a particular application of interest. In this work, an Ag-Au core-shell thin film nanoislands with APTMS (3-Aminopropyl trimethoxysilane) and PVA (Polyvinyl alcohol) binding agents was modeled, synthesized and characterized. The simulation results were used to fabricate the sensor through chemical route. The results of this study confirmed that the APTMS based Ag-Au core-shell thin film nanoislands offered a better performance over the PVA based Ag-Au core-shell thin film nanoislands. Also, the APTMS based Ag-Au core-shell thin film nanoislands exhibited better sensitivity towards ozone sensing over the other types, viz., APTMS/PVA based Au-Ag core-shell and standalone Au/Ag thin film nanoislands.

Enabling fiber optic serotyping of pathogenic bacteria through improved anti-fouling functional surfaces

NASA Astrophysics Data System (ADS)

Janssen, K. P. F.; Knez, K.; Vanysacker, L.; Schrooten, J.; Spasic, D.; Lammertyn, J.

2012-06-01

Significant research efforts are continually being directed towards the development of sensitive and accurate surface plasmon resonance biosensors for sequence specific DNA detection. These sensors hold great potential for applications in healthcare and diagnostics. However, the performance of these sensors in practical usage scenarios is often limited due to interference from the sample matrix. This work shows how the co-immobilization of glycol (PEG) diluents or ‘back filling’ of the DNA sensing layer can successfully address these problems. A novel SPR based melting assay is used for the analysis of a synthetic oligomer target as well as PCR amplified genomic DNA extracted from Legionella pneumophila. The benefits of sensing layer back filling on the assay performance are first demonstrated through melting analysis of the oligomer target and it is shown how back filling enables accurate discrimination of Legionella pneumophila serogroups directly from the PCR reaction product with complete suppression of sensor fouling.

Development of a Temperature Sensor for Jet Engine and Space Mission Applications

NASA Technical Reports Server (NTRS)

Patterson, Richard L.; Hammoud, Ahmad; Elbuluk, Malik; Culley, Dennis

2008-01-01

Electronics for Distributed Turbine Engine Control and Space Exploration Missions are expected to encounter extreme temperatures and wide thermal swings. In particular, circuits deployed in a jet engine compartment are likely to be exposed to temperatures well exceeding 150 C. To meet this requirement, efforts exist at the NASA Glenn Research Center (GRC), in support of the Fundamental Aeronautics Program/Subsonic Fixed Wing Project, to develop temperature sensors geared for use in high temperature environments. The sensor and associated circuitry need to be located in the engine compartment under distributed control architecture to simplify system design, improve reliability, and ease signal multiplexing. Several circuits were designed using commercial-off-the-shelf as well as newly-developed components to perform temperature sensing at high temperatures. The temperature-sensing circuits will be described along with the results pertaining to their performance under extreme temperature.

Apparatus and method for sensing motion in a microelectro-mechanical system

DOEpatents

Dickey, Fred M.; Holswade, Scott C.

1999-01-01

An apparatus and method are disclosed for optically sensing motion in a microelectromechanical system (also termed a MEMS device) formed by surface micromachining or LIGA. The apparatus operates by reflecting or scattering a light beam off a corrugated surface (e.g. gear teeth or a reference feature) of a moveable member (e.g. a gear, rack or linkage) within the MEMS device and detecting the reflected or scattered light. The apparatus can be used to characterize a MEMS device, measuring one or more performance characteristic such as spring and damping coefficients, torque and friction, or uniformity of motion of the moveable member. The apparatus can also be used to determine the direction and extent of motion of the moveable member; or to determine a particular mechanical state that a MEMS device is in. Finally, the apparatus and method can be used for providing feedback to the MEMS device to improve performance and reliability.

High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures.

PubMed

Kim, Daehyun; Trzasko, Joshua; Smelyanskiy, Mikhail; Haider, Clifton; Dubey, Pradeep; Manduca, Armando

2011-01-01

Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However, the computationally intensive nature of CS reconstructions has precluded their use in routine clinical practice. In this work, we investigate how different throughput-oriented architectures can benefit one CS algorithm and what levels of acceleration are feasible on different modern platforms. We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. We then show that Intel's Knights Ferry can perform the same 3D MRI reconstruction in only 12 seconds, bringing CS methods even closer to clinical viability.

Dual-Emitting UiO-66(Zr&Eu) Metal-Organic Framework Films for Ratiometric Temperature Sensing.

PubMed

Feng, Ji-Fei; Liu, Tian-Fu; Shi, Jianlin; Gao, Shui-Ying; Cao, Rong

2018-06-20

A novel dual-emitting metal-organic framework based on Zr and Eu, named as UiO-66(Zr&Eu), was built using a clever strategy based on secondary building units. With the use of polymers, the obtained UiO-66(Zr&Eu) was subsequently deposited as thin films that can be utilized as smart thermometers. The UiO-66(Zr&Eu) polymer films can be used for the detection of temperature changes in the range of 237-337 K due to the energy transfer between the lanthanide ions (Eu in clusters) and the luminescent ligands, and the relative sensitivity reaches 4.26% K -1 at 337 K. Moreover, the sensitivity can be improved to 19.67% K -1 by changing the film thickness. In addition, the temperature-sensing performance of the films is superior to that of the powders, and the sensor can be reused 3 times without loss of performance.

In-Network Processing for Mission-Critical Wireless Networked Sensing and Control: A Real-Time, Efficiency, and Resiliency Perspective

ERIC Educational Resources Information Center

Xiang, Qiao

2014-01-01

As wireless cyber-physical systems (WCPS) are increasingly being deployed in mission-critical applications, it becomes imperative that we consider application QoS requirements in in-network processing (INP). In this dissertation, we explore the potentials of two INP methods, packet packing and network coding, on improving network performance while…

Effects of bathymetric lidar errors on flow properties predicted with a multi-dimensional hydraulic model

Treesearch

J. McKean; D. Tonina; C. Bohn; C. W. Wright

2014-01-01

New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional...

George Washington: A Grounded Leader

DTIC Science & Technology

2011-04-08

not well educated in a formal sense, George Washington was highly intellectual. His commitment to self -improvement, coupled with native abilities, and...and additional qualifiers separated by commas, e.g. Smith, Richard, Jr. 7. PERFORMING ORGANIZATION NAME{S) AND ADDRESS{ES). Self -explanatory. 8...PERMITTED PROVIDED PROPER ACKNOWLEDGEMENT IS MADE. ii Acknowledgements In the beginning was Dr. Donald F. Bittner. Dr. Bittner was my esteemed faculty

Fusion and Sense Making of Heterogeneous Sensor Network and Other Sources

DTIC Science & Technology

2017-03-16

multimodal fusion framework that uses both training data and web resources for scene classification, the experimental results on the benchmark datasets...show that the proposed text-aided scene classification framework could significantly improve classification performance. Experimental results also show...human whose adaptability is achieved by reliability- dependent weighting of different sensory modalities. Experimental results show that the proposed

UWB radar technique for arc detection in coaxial cables and waveguides

NASA Astrophysics Data System (ADS)

Maggiora, R.; Salvador, S.

2009-11-01

As spread spectrum technology has revolutionized the communications industry, Ultra Wide Band (UWB) technology is dramatically improving radar performances. These advanced signal processing techniques have been adapted to coaxial cables and waveguides to provide new features and enhanced performance on arc detection. UWB signals constituted by a sequence of chips (properly chosen to reduce side lobes and to improve detection accuracy) are transmitted along the transmission lines at a specified Pulse Repetition Frequency (PRF) and their echoes are received by means of directional couplers. The core of the receiver is an ultra high-speed correlator implemented in a Digital Signal Processor (DSP). When a target (arc) is detected, its position and its "radar cross section" are calculated to be able to provide the arc position along the transmission line and to be able to classify the type of detected arc. The "background scattering" is routinely extracted from the received signal at any pulse. This permits to be resilient to the background structure of transmission lines (bends, junctions, windows, etc.). Thanks to the localization feature, segmentation is also possible for creating sensed and non-sensed zones (for example, to be insensitive to antenna load variations).

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning

PubMed Central

2017-01-01

This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image of Liverpool (UK) to evaluate their potential to predict Living Environment Deprivation at a small statistical area level. We also contribute to the methodological literature on the estimation of socioeconomic indices with remote-sensing data by introducing elements from modern machine learning. In addition to classical approaches such as Ordinary Least Squares (OLS) regression and a spatial lag model, we explore the potential of the Gradient Boost Regressor and Random Forests to improve predictive performance and accuracy. In addition to novel predicting methods, we also introduce tools for model interpretation and evaluation such as feature importance and partial dependence plots, or cross-validation. Our results show that Random Forest proved to be the best model with an R2 of around 0.54, followed by Gradient Boost Regressor with 0.5. Both the spatial lag model and the OLS fall behind with significantly lower performances of 0.43 and 0.3, respectively. PMID:28464010

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning.

PubMed

Arribas-Bel, Daniel; Patino, Jorge E; Duque, Juan C

2017-01-01

This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image of Liverpool (UK) to evaluate their potential to predict Living Environment Deprivation at a small statistical area level. We also contribute to the methodological literature on the estimation of socioeconomic indices with remote-sensing data by introducing elements from modern machine learning. In addition to classical approaches such as Ordinary Least Squares (OLS) regression and a spatial lag model, we explore the potential of the Gradient Boost Regressor and Random Forests to improve predictive performance and accuracy. In addition to novel predicting methods, we also introduce tools for model interpretation and evaluation such as feature importance and partial dependence plots, or cross-validation. Our results show that Random Forest proved to be the best model with an R2 of around 0.54, followed by Gradient Boost Regressor with 0.5. Both the spatial lag model and the OLS fall behind with significantly lower performances of 0.43 and 0.3, respectively.

Enhancing dissolved oxygen control using an on-line hybrid fuzzy-neural soft-sensing model-based control system in an anaerobic/anoxic/oxic process.

PubMed

Huang, Mingzhi; Wan, Jinquan; Hu, Kang; Ma, Yongwen; Wang, Yan

2013-12-01

An on-line hybrid fuzzy-neural soft-sensing model-based control system was developed to optimize dissolved oxygen concentration in a bench-scale anaerobic/anoxic/oxic (A(2)/O) process. In order to improve the performance of the control system, a self-adapted fuzzy c-means clustering algorithm and adaptive network-based fuzzy inference system (ANFIS) models were employed. The proposed control system permits the on-line implementation of every operating strategy of the experimental system. A set of experiments involving variable hydraulic retention time (HRT), influent pH (pH), dissolved oxygen in the aerobic reactor (DO), and mixed-liquid return ratio (r) was carried out. Using the proposed system, the amount of COD in the effluent stabilized at the set-point and below. The improvement was achieved with optimum dissolved oxygen concentration because the performance of the treatment process was optimized using operating rules implemented in real time. The system allows various expert operational approaches to be deployed with the goal of minimizing organic substances in the outlet while using the minimum amount of energy.

A Review of Simulators with Haptic Devices for Medical Training.

PubMed

Escobar-Castillejos, David; Noguez, Julieta; Neri, Luis; Magana, Alejandra; Benes, Bedrich

2016-04-01

Medical procedures often involve the use of the tactile sense to manipulate organs or tissues by using special tools. Doctors require extensive preparation in order to perform them successfully; for example, research shows that a minimum of 750 operations are needed to acquire sufficient experience to perform medical procedures correctly. Haptic devices have become an important training alternative and they have been considered to improve medical training because they let users interact with virtual environments by adding the sense of touch to the simulation. Previous articles in the field state that haptic devices enhance the learning of surgeons compared to current training environments used in medical schools (corpses, animals, or synthetic skin and organs). Consequently, virtual environments use haptic devices to improve realism. The goal of this paper is to provide a state of the art review of recent medical simulators that use haptic devices. In particular we focus on stitching, palpation, dental procedures, endoscopy, laparoscopy, and orthopaedics. These simulators are reviewed and compared from the viewpoint of used technology, the number of degrees of freedom, degrees of force feedback, perceived realism, immersion, and feedback provided to the user. In the conclusion, several observations per area and suggestions for future work are provided.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

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

Kim, S; Young, C; Mizaikoff, B

Fundamental vibrational and rotational modes associated with most inorganic and organic molecules are spectroscopically accessible within the mid-infrared (MIR; 3-20 {micro}m) regime of the electromagnetic spectrum. The interaction between MIR photons and organic molecules provides particularly sharp transitions, which - despite the wide variety of organic molecules - provide unique MIR absorption spectra reflecting the molecularly characteristic arrangement of chemical bonds within the probed molecules via the frequency position of the associated vibrational and rotational transitions. Given the inherent molecular selectivity and achievable sensitivity, MIR spectroscopy provides an ideal platform for optical sensing applications. Despite this potential, early MIR sensingmore » applications were limited to localized applications due to the size of the involved instrumentation, and limited availability of appropriately compact MIR optical components including light sources, detectors, waveguides, and spectrometers. During the last decades, engineering advances in photonics and optical engineering have facilitated the translation of benchtop-style MIR spectroscopy into miniaturized optical sensing schemes providing a footprint compatible with portable instrumentation requirements for field deployable analytical tools. In this trend article, we will discuss recent advances and future strategies for miniaturizing MIR sensor technology. The Beer-Lambert law implies that achievable limit of detection (LOD) for any optical sensor system improves by increasing the interaction length between photons and target analyte species such as e.g., folding the optical path multiple times as in multi-pass gas phase sensing; however, this governing paradigm naturally leads to an increase in system dimensions. Hence, miniaturization of optical sensing system requires scaling down of each optical component, yet improving the performance of each optical element within a smaller form factor for overall at least maintaining, or ideally improving the achievable sensitivity.« less

A visual water vapor photonic crystal sensor with PVA/SiO2 opal structure

NASA Astrophysics Data System (ADS)

Yang, Haowei; Pan, Lei; Han, Yingping; Ma, Lihua; Li, Yao; Xu, Hongbo; Zhao, Jiupeng

2017-11-01

In study, we proposed a simple yet fast optical sensing motif based on thimbleful of polyvinyl alcohol (PVA) infiltrated photonic crystal (PC), which allows for high efficiency in vapor sensing through changes in their inter-layer space. Linear response to a broad dynamic range of vapor concentration was realized. Ultrafast response time (<1 s) and excellent recyclability were also demonstrated. Selective response to a vapor was exhibited, reflecting well the characteristic sorption properties of PVA, with which colorimetric reporting was readily achieved. These substantial improvements in performance are attributed to the efficacy of signal transduction and the enhanced signal transduction because of thimbleful PVA infiltrated space between adjacent SiO2 nanospheres.

Engineering quorum sensing signaling of Pseudomonas for enhanced wastewater treatment and electricity harvest: A review.

PubMed

Yong, Yang-Chun; Wu, Xiang-Yang; Sun, Jian-Zhong; Cao, Ying-Xiu; Song, Hao

2015-12-01

Cell-cell communication that enables synchronized population behaviors in microbial communities dictates various biological processes. It is of great interest to unveil the underlying mechanisms of fine-tuning cell-cell communication to achieve environmental and energy applications. Pseudomonas is a ubiquitous microbe in environments that had wide applications in bioremediation and bioenergy generation. The quorum sensing (QS, a generic cell-cell communication mechanism) systems of Pseudomonas underlie the aromatics biodegradation, denitrification and electricity harvest. Here, we reviewed the recent progresses of the genetic strategies in engineering QS circuits to improve efficiency of wastewater treatment and the performance of microbial fuel cells. Copyright © 2014 Elsevier Ltd. All rights reserved.

Peripheral neuropathy: an often-overlooked cause of falls in the elderly.

PubMed

Richardson, J K; Ashton-Miller, J A

1996-06-01

Peripheral neuropathy is common in the elderly and results in impairments in distal proprioception and strength that hinder balance and predispose them to falls. The loss of heel reflexes, decreased vibratory sense that improves proximally, impaired position sense at the great toe, and inability to maintain unipedal stance for 10 seconds in three attempts all suggest functionally significant peripheral neuropathy. Physicians can help their patients with peripheral neuropathy to prevent falls by teaching them and their families about peripheral nerve dysfunction and its effects on balance and by advising patients to substitute vision for the lost somatosensory function, correctly use a cane, wear proper shoes and orthotics, and perform balance and upper extremity strengthening exercises.

Visual working memory and number sense: Testing the double deficit hypothesis in mathematics.

PubMed

Toll, Sylke W M; Kroesbergen, Evelyn H; Van Luit, Johannes E H

2016-09-01

Evidence exists that there are two main underlying cognitive factors in mathematical difficulties: working memory and number sense. It is suggested that real math difficulties appear when both working memory and number sense are weak, here referred to as the double deficit (DD) hypothesis. The aim of this study was to test the DD hypothesis within a longitudinal time span of 2 years. A total of 670 children participated. The mean age was 4.96 years at the start of the study and 7.02 years at the end of the study. At the end of the first year of kindergarten, both visual-spatial working memory and number sense were measured by two different tasks. At the end of first grade, mathematical performance was measured with two tasks, one for math facts and one for math problems. Multiple regressions revealed that both visual working memory and symbolic number sense are predictors of mathematical performance in first grade. Symbolic number sense appears to be the strongest predictor for both math areas (math facts and math problems). Non-symbolic number sense only predicts performance in math problems. Multivariate analyses of variance showed that a combination of visual working memory and number sense deficits (NSDs) leads to the lowest performance on mathematics. Our DD hypothesis was confirmed. Both visual working memory and symbolic number sense in kindergarten are related to mathematical performance 2 years later, and a combination of visual working memory and NSDs leads to low performance in mathematical performance. © 2016 The British Psychological Society.

Graphene-bimetal plasmonic platform for ultra-sensitive biosensing

NASA Astrophysics Data System (ADS)

Tong, Jinguang; Jiang, Li; Chen, Huifang; Wang, Yiqin; Yong, Ken-Tye; Forsberg, Erik; He, Sailing

2018-03-01

A graphene-bimetal plasmonic platform for surface plasmon resonance biosensing with ultra-high sensitivity was proposed and optimized. In this hybrid configuration, graphene nanosheets was employed to effectively absorb the excitation light and serve as biomolecular recognition elements for increased adsorption of analytes. Coating of an additional Au film prevents oxidation of the Ag substrate during manufacturing process and enhances the sensitivity at the same time. Thus, a bimetal Au-Ag substrate enables improved sensing performance and promotes stability of this plasmonic sensor. In this work we optimized the number of graphene layers as well as the thickness of the Au film and the Ag substrate based on the phase-interrogation sensitivity. We found an optimized configuration consisting of 6 layers of graphene coated on a bimetal surface consisting of a 5 nm Au film and a 30 nm Ag film. The calculation results showed the configuration could achieve a phase sensitivity as high as 1 . 71 × 106 deg/RIU, which was more than 2 orders of magnitude higher than that of bimetal structure and graphene-silver structure. Due to this enhanced sensing performance, the graphene-bimetal plasmonic platform proposed in this paper is potential for ultra-sensitive plasmonic sensing.

Enhanced geometries of macroporous silicon photonic crystals for optical gas sensing applications

NASA Astrophysics Data System (ADS)

Cardador, D.; Vega, D.; Segura, D.; Trifonov, T.; Rodríguez, A.

2017-07-01

A macroporous silicon photonic crystal is designed and optimized theoretically for its use in gas sensing applications and IR optical filters. Light impinges perpendicularly onto the sample surface (vertical propagation) so a three-dimensional (3d) structure is used. For gas sensing, a sharp resonance is desired in order to isolate an absorption line of the gas of interest. The high Q-factors needed mandate the use of a plane defect inside the PhC to give rise to a resonant mode inside the bandgap tuned to the gas absorption line. Furthermore to allow gas passage through the device, an open membrane is required. This can affect the mechanical resilience. To improve the strength of the photonic crystal the pores are extended after the ;active; 3d part. The number of modulations, and the extension length have been optimized to obtain the largest Q-factor with reasonable transmitted power. These proposed structures have been experimentally performed, probing an enhancement of almost an order of magnitude in the Q-factor in respect with the basic case. Simulations considering CO2 have been performed showing that the proposed structures are promising as precise optical gas sensors.

Scalability Issues for Remote Sensing Infrastructure: A Case Study

PubMed Central

Liu, Yang; Picard, Sean; Williamson, Carey

2017-01-01

For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure. PMID:28468262

Do dogs sense hypoglycaemia?

PubMed

Weber, K S; Roden, M; Müssig, K

2016-07-01

To summarize the current knowledge on the phenomenon of dogs, both trained and untrained, sensing hypoglycaemia and alerting their owners to it. Electronic databases were searched for all types of articles reporting on untrained or trained 'diabetes alert' dogs. Articles published up until December 2014 in the English or German language were included. Several case reports and observational studies provide evidence that animals can perform at a level above that attributable to chance, and may reliably detect low diurnal as well as nocturnal hypoglycaemic episodes. Behavioural changes in untrained dogs were reported during 38-100% of hypoglycaemic events experienced by their owners. The sensitivity and specificity of the performance of trained diabetes alert dogs sensing hypoglycaemia ranged from 22 to 100% and 71 to 90%, respectively. Additionally, 75-81% of patients with diabetes who owned a trained dog reported a subsequent improvement in their quality of life. Nevertheless, the available data are limited and heterogeneous because they rely on low patient numbers and survey-based studies prone to recall bias. Further research is needed to confirm the preliminary data on the reliability and mechanism underlying the dogs' abilities to detect hypoglycaemia, and its impact on patient outcomes. © 2015 Diabetes UK.

Vehicular Visible Light Networks for Urban Mobile Crowd Sensing

PubMed Central

2018-01-01

Crowd sensing is a powerful tool to map and predict interests and events. In the future, it could be boosted by an increasing number of connected vehicles sharing information and intentions. This will be made available by on board wireless connected devices able to continuously communicate with other vehicles and with the environment. Among the enabling technologies, visible light communication (VLC) represents a low cost solution in the short term. In spite of the fact that vehicular communications cannot rely on the sole VLC due to the limitation provided by the light which allows communications in visibility only, VLC can however be considered to complement other wireless communication technologies which could be overloaded in dense scenarios. In this paper we evaluate the performance of VLC connected vehicles when urban crowd sensing is addressed and we compare the performance of sole vehicular visible light networks with that of VLC as a complementary technology of IEEE 802.11p. Results, obtained through a realistic simulation tool taking into account both the roadmap constraints and the technologies protocols, help to understand when VLC provides the major improvement in terms of delivered data varying the number and position of RSUs and the FOV of the receiver. PMID:29649149

Telerobotic Perception During Asteroid and Mars Regolith Operations Project

NASA Technical Reports Server (NTRS)

Gaddis, Steven; Zeitlin, Nancy (Compiler); Mueller, Robert (Compiler)

2015-01-01

Current space telerobotic systems are constrained to only operating in bright light and dust-free conditions. This project will study the effects of difficult lighting and dust conditions on telerobotic perception systems to better assess and refine regolith operations on other neighboring celestial bodies. In partnership with Embry-Riddle Aeronautical University and Caterpillar, Inc., optical, LiDAR and RADAR sensing equipment will be used in performing the study. This project will create a known dust environment in the Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory regolith test bin to characterize the behavior of the sensing equipment in various calibrated lighting and dust conditions. It will also identify potential methods for mitigating the impacts of these undesirable conditions on the performance of the sensing equipment. Enhancing the capability of telerobotic perception systems will help improve life on earth for those working in dangerous, dusty mining conditions, as well as help advance the same technologies used for safer self-driving automobiles in various lighting and weather conditions. It will also prove to be a critical skill needed for advancing robotic and human exploration throughout our solar system, for activities such as mining on an asteroid or pioneering the first colony on Mars.

A novel non-contact radar sensor for affective and interactive analysis.

PubMed

Lin, Hong-Dun; Lee, Yen-Shien; Shih, Hsiang-Lan; Chuang, Bor-Nian

2013-01-01

Currently, many physiological signal sensing techniques have been applied for affective analysis in Human-Computer Interaction applications. Most known maturely developed sensing methods (EEG/ECG/EMG/Temperature/BP etc. al.) replied on contact way to obtain desired physiological information for further data analysis. However, those methods might cause some inconvenient and uncomfortable problems, and not easy to be used for affective analysis in interactive performing. To improve this issue, a novel technology based on low power radar technology (Nanosecond Pulse Near-field Sensing, NPNS) with 300 MHz radio-frequency was proposed to detect humans' pulse signal by the non-contact way for heartbeat signal extraction. In this paper, a modified nonlinear HRV calculated algorithm was also developed and applied on analyzing affective status using extracted Peak-to-Peak Interval (PPI) information from detected pulse signal. The proposed new affective analysis method is designed to continuously collect the humans' physiological signal, and validated in a preliminary experiment with sound, light and motion interactive performance. As a result, the mean bias between PPI (from NPNS) and RRI (from ECG) shows less than 1ms, and the correlation is over than 0.88, respectively.

An approach to improve the spatial resolution of a force mapping sensing system

NASA Astrophysics Data System (ADS)

Negri, Lucas Hermann; Manfron Schiefer, Elberth; Sade Paterno, Aleksander; Muller, Marcia; Luís Fabris, José

2016-02-01

This paper proposes a smart sensor system capable of detecting sparse forces applied to different positions of a metal plate. The sensing is performed with strain transducers based on fiber Bragg gratings (FBG) distributed under the plate. Forces actuating in nine squared regions of the plate, resulting from up to three different loads applied simultaneously to the plate, were monitored with seven transducers. The system determines the magnitude of the force/pressure applied on each specific area, even in the absence of a dedicated transducer for that area. The set of strain transducers with coupled responses and a compressive sensing algorithm are employed to solve the underdetermined inverse problem which emerges from mapping the force. In this configuration, experimental results have shown that the system is capable of recovering the value of the load distributed on the plate with a signal-to-noise ratio better than 12 dB, when the plate is submitted to three simultaneous test loads. The proposed method is a practical illustration of compressive sensing algorithms for the reduction of the number of FBG-based transducers used in a quasi-distributed configuration.

Resonant efficiency improvement design of piezoelectric biosensor for bacteria gravimetric sensing.

PubMed

Tsai, Jang-Zern; Chen, Ching-Jung; Shie, Dung-Ting; Liu, Jen-Tsai

2014-01-01

The piezoelectric biosensor have been widely used in ultra-small mass detection of biomolecular, based on PZT piezoelectric material can create a variety of compositions geometrically; it could widely develop a high-frequency resonator and measure the change of the slightest mass while improve the limited detection simultaneously. Therefore, the piezoelectric biosensor of this study was fabricated by a spin-coating method and backside etching process for improving the characteristic of piezoelectric biosensor. The result exhibited that the 250 μm × 250 μm working size has the most favorable piezoelectric characteristic. The tunability was approximately 38.56 % and it showed that reducing the substrate thickness could obtain a clear resonance signal in a range of 60 to 380 MHz. In theory calculated for gravimetric sensing, it could achieve 0.1 ng sensing sensitivity. In gravimetric sensing, the sensing range was between 50,000~100,000 CFU/ml. Sensing range was lower in clinical urinary tract infection (100,000 CFU/ml), thus demonstrating its usefulness for preventive medicine. It can understand the piezoelectric sensor of this study has potential application in the future for biomedical gravimetric sensing.

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.

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.

Improved reconstruction and sensing techniques for personnel screening in three-dimensional cylindrical millimeter-wave portal scanning

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

Fernandes, Justin L.; Rappaport, Carey M.; Sheen, David M.

2011-05-01

The cylindrical millimeter-wave imaging technique, developed at Pacific Northwest National Laboratory (PNNL) and commercialized by L-3 Communications/Safeview in the ProVision system, is currently being deployed in airports and other high security locations to meet person-borne weapon and explosive detection requirements. While this system is efficient and effective in its current form, there are a number of areas in which the detection performance may be improved through using different reconstruction algorithms and sensing configurations. PNNL and Northeastern University have teamed together to investigate higher-order imaging artifacts produced by the current cylindrical millimeter-wave imaging technique using full-wave forward modeling and laboratory experimentation.more » Based on imaging results and scattered field visualizations using the full-wave forward model, a new imaging system is proposed. The new system combines a multistatic sensor configuration with the generalized synthetic aperture focusing technique (GSAFT). Initial results show an improved ability to image in areas of the body where target shading, specular and higher-order reflections cause images produced by the monostatic system difficult to interpret.« less

Can multilinguality improve Biomedical Word Sense Disambiguation?

PubMed

Duque, Andres; Martinez-Romo, Juan; Araujo, Lourdes

2016-12-01

Ambiguity in the biomedical domain represents a major issue when performing Natural Language Processing tasks over the huge amount of available information in the field. For this reason, Word Sense Disambiguation is critical for achieving accurate systems able to tackle complex tasks such as information extraction, summarization or document classification. In this work we explore whether multilinguality can help to solve the problem of ambiguity, and the conditions required for a system to improve the results obtained by monolingual approaches. Also, we analyze the best ways to generate those useful multilingual resources, and study different languages and sources of knowledge. The proposed system, based on co-occurrence graphs containing biomedical concepts and textual information, is evaluated on a test dataset frequently used in biomedicine. We can conclude that multilingual resources are able to provide a clear improvement of more than 7% compared to monolingual approaches, for graphs built from a small number of documents. Also, empirical results show that automatically translated resources are a useful source of information for this particular task. Copyright © 2016 Elsevier Inc. All rights reserved.

Effect of whey protein hydrolysate on performance and recovery of top-class orienteering runners.

PubMed

Hansen, Mette; Bangsbo, Jens; Jensen, Jørgen; Bibby, Bo Martin; Madsen, Klavs

2015-04-01

This trial aimed to examine the effect of whey protein hydrolysate intake before and after exercise sessions on endurance performance and recovery in elite orienteers during a training camp. Eighteen elite orienteers participated in a randomized controlled intervention trial during a 1-week training camp (13 exercise sessions). Half of the runners (PRO-CHO) ingested a protein drink before (0.3 g kg(-1)) and a protein-carbohydrate drink after (0.3 g protein kg(-1) and 1 g carbohydrate kg(-1)) each exercise session. The others ingested energy and time-matched carbohydrate drinks (CHO). A 4-km run-test with 20 control points was performed before and on the last day of the intervention. Blood and saliva were obtained in the mornings, before and after run-tests, and after the last training session. During the intervention, questionnaires were fulfilled regarding psychological sense of performance capacity and motivation. PRO-CHO and not CHO improved performance in the 4-km run-test (interaction p < .05). An increase in serum creatine kinase was observed during the week, which was greater in CHO than PRO-CHO (interaction p < .01). Lactate dehydrogenase (p < .001) and cortisol (p = .057) increased during the week, but the change did not differ between groups. Reduction in sense of performance capacity during the intervention was greater in CHO (p < .05) than PRO-CHO. In conclusion, ingestion of whey protein hydrolysate before and after each exercise session improves performance and reduces markers of muscle damage during a strenuous 1-week training camp. The results indicate that protein supplementation in conjunction with each exercise session facilitates the recovery from strenuous training in elite orienteers.

Sense of coherence, self-regulated learning and academic performance in first year nursing students: A cluster analysis approach.

PubMed

Salamonson, Yenna; Ramjan, Lucie M; van den Nieuwenhuizen, Simon; Metcalfe, Lauren; Chang, Sungwon; Everett, Bronwyn

2016-03-01

This paper examines the relationship between nursing students' sense of coherence, self-regulated learning and academic performance in bioscience. While there is increasing recognition of a need to foster students' self-regulated learning, little is known about the relationship of psychological strengths, particularly sense of coherence and academic performance. Using a prospective, correlational design, 563 first year nursing students completed the three dimensions of sense of coherence scale - comprehensibility, manageability and meaningfulness, and five components of self-regulated learning strategy - elaboration, organisation, rehearsal, self-efficacy and task value. Cluster analysis was used to group respondents into three clusters, based on their sense of coherence subscale scores. Although there were no sociodemographic differences in sense of coherence subscale scores, those with higher sense of coherence were more likely to adopt self-regulated learning strategies. Furthermore, academic grades collected at the end of semester revealed that higher sense of coherence was consistently related to achieving higher academic grades across all four units of study. Students with higher sense of coherence were more self-regulated in their learning approach. More importantly, the study suggests that sense of coherence may be an explanatory factor for students' successful adaptation and transition in higher education, as indicated by the positive relationship of sense of coherence to academic performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Photoactivated Mixed In-Plane and Edge-Enriched p-Type MoS2 Flake-Based NO2 Sensor Working at Room Temperature.

PubMed

Agrawal, Abhay V; Kumar, Rahul; Venkatesan, Swaminathan; Zakhidov, Alex; Yang, Guang; Bao, Jiming; Kumar, Mahesh; Kumar, Mukesh

2018-05-25

Toxic gases are produced during the burning of fossil fuels. Room temperature (RT) fast detection of toxic gases is still challenging. Recently, MoS 2 transition metal dichalcogenides have sparked great attention in the research community due to their performance in gas sensing applications. However, MoS 2 based gas sensors still suffer from long response and recovery times, especially at RT. Considering this challenge, here, we report photoactivated highly reversible and fast detection of NO 2 sensors at room temperature (RT) by using mixed in-plane and edge-enriched p-MoS 2 flakes (mixed MoS 2 ). The sensor showed fast response with good sensitivity of ∼10.36% for 10 ppm of NO 2 at RT without complete recovery. However, complete recovery was obtained with better sensor performance under UV light illumination at RT. The UV assisted NO 2 sensing showed improved performance in terms of fast response and recovery kinetics with enhanced sensitivity to 10 ppm NO 2 concentration. The sensor performance is also investigated under thermal energy, and a better sensor performance with reduced sensitivity and high selectivity toward NO 2 was observed. A detailed gas sensing mechanism based on the density functional theory (DFT) calculations for favorable NO 2 adsorption sites on in-plane and edge-enriched MoS 2 flakes is proposed. This study revealed the role of favorable adsorption sites in MoS 2 flakes for the enhanced interaction of target gases and developed a highly sensitive, reversible, and fast gas sensor for next-generation toxic gases at room temperature.

Comparative VOCs sensing performance for conducting polymer and porphyrin functionalized carbon nanotubes based sensors

NASA Astrophysics Data System (ADS)

Datta, Kunal; Rushi, Arti; Ghosh, Prasanta; Shirsat, Mahendra

2018-05-01

We report sensors for detection of ethyl alcohol, a prominent volatile organic compound (VOC). Single walled carbon nanotubes were selected as main sensing backbone. As efficiency of sensor is dependent upon the choice of sensing materials, the performances of conducting polymer and porphyrin based sensors were compared. Chemiresistive sensing modality was adopted to observe the performance of sensors. It has been found that porphyrin based sensor shows higher affinity towards ethyl alcohol.

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Noise-Enhanced Eversion Force Sense in Ankles With or Without Functional Instability.

PubMed

Ross, Scott E; Linens, Shelley W; Wright, Cynthia J; Arnold, Brent L

2015-08-01

Force sense impairments are associated with functional ankle instability. Stochastic resonance stimulation (SRS) may have implications for correcting these force sense deficits. To determine if SRS improved force sense. Case-control study. Research laboratory. Twelve people with functional ankle instability (age = 23 ± 3 years, height = 174 ± 8 cm, mass = 69 ± 10 kg) and 12 people with stable ankles (age = 22 ± 2 years, height = 170 ± 7 cm, mass = 64 ± 10 kg). The eversion force sense protocol required participants to reproduce a targeted muscle tension (10% of maximum voluntary isometric contraction). This protocol was assessed under SRSon and SRSoff (control) conditions. During SRSon, random subsensory mechanical noise was applied to the lower leg at a customized optimal intensity for each participant. Constant error, absolute error, and variable error measures quantified accuracy, overall performance, and consistency of force reproduction, respectively. With SRS, we observed main effects for force sense absolute error (SRSoff = 1.01 ± 0.67 N, SRSon = 0.69 ± 0.42 N) and variable error (SRSoff = 1.11 ± 0.64 N, SRSon = 0.78 ± 0.56 N) (P < .05). No other main effects or treatment-by-group interactions were found (P > .05). Although SRS reduced the overall magnitude (absolute error) and variability (variable error) of force sense errors, it had no effect on the directionality (constant error). Clinically, SRS may enhance muscle tension ability, which could have treatment implications for ankle stability.

Interinstrument comparison of remote-sensing devices and a new method for calculating on-road nitrogen oxides emissions and validation of vehicle-specific power.

PubMed

Rushton, Christopher E; Tate, James E; Shepherd, Simon P; Carslaw, David C

2018-02-01

Emissions of nitrogen oxides (NOx) by vehicles in real driving environments are only partially understood. This has been brought to the attention of the world with recent revelations of the cheating of the type of approval tests exposed in the dieselgate scandal. Remote-sensing devices offer investigators an opportunity to directly measure in situ real driving emissions of tens of thousands of vehicles. Remote-sensing NO 2 measurements are not as widely available as would be desirable. The aim of this study is to improve the ability of investigators to estimate the NO 2 emissions and to improve the confidence of the total NOx results calculated from standard remote-sensing device (RSD) measurements. The accuracy of the RSD speed and acceleration module was also validated using state-of-the-art onboard global positioning system (GPS) tracking. Two RSDs used in roadside vehicle emissions surveys were tested side by side under off-carriageway conditions away from transient pollution sources to ascertain the consistency of their measurements. The speed correlation was consistent across the range of measurements at 95% confidence and the acceleration correlation was consistent at 95% confidence intervals for all but the most extreme acceleration cases. VSP was consistent at 95% confidence across all measurements except for those at VSP ≥ 15 kW t -1 , which show a small underestimate. The controlled distribution gas nitric oxide measurements follow a normal distribution with 2σ equal to 18.9% of the mean, compared to 15% observed during factory calibration indicative of additional error introduced into the system. Systematic errors of +84 ppm were observed but within the tolerance of the control gas. Interinstrument correlation was performed, with the relationship between the FEAT and the RSD4600 being linear with a gradient of 0.93 and an R 2 of 0.85, indicating good correlation. A new method to calculate NOx emissions using fractional NO 2 combined with NO measurements made by the RSD4600 was constructed, validated, and shown to be more accurate than previous methods. Synchronized remote-sensing measurements of NO were taken using two different remote-sensing devices in an off-road study. It was found that the measurements taken by both instruments were well correlated. Fractional NO 2 measurements from a prior study, measurable on only one device, were used to create new NO x emission factors for the device that could not be measured by the second device. These estimates were validated against direct measurement of total NO x emission factors and shown to be an improvement on previous methodologies. Validation of vehicle-specific power was performed with good correlation observed.

Ergonomic audit of a specially engineered sonic powered toothbrush with unique sensing and control technologies, the Sonicare Flexcare, and the Oral-B Smart Series 5000.

PubMed

Hunter, Gail; Burns, Laurie; Bone, Brian; Mintel, Thomas; Jimenez, Eduardo

2012-01-01

The presence of ergonomic features can impact the marketplace success of a new product. Metaphase Design Group, Inc., in partnership with the Colgate-Palmolive Company, conducted an ergonomic audit on three electric toothbrushes: a specially engineered sonic powered toothbrush with unique sensing and control technologies, the Sonicare FlexCare, and the Oral-B Smart Series 5000. The ergonomic audit was conducted by Metaphase Design Groups's ergonomic and usability experts. Two experts used the toothbrushes over a one-week period and assessed the performance of each brush against a set of ergonomic principles. The three toothbrushes have some solid ergonomic features. They each have adequate grip zones, provide grip security with elastomeric materials, and provide easy access to the on/off button. The most distinctive feature is the longitudinal shape of the handle of the specially engineered sonic powered toothbrush with unique sensing and control technologies. This handle angles downward at the top end and provides additional advantages through improved grip security and visibility. Yet all three toothbrushes have different opportunities for improvement. The Sonicare Flex Care toothbrush has a cluttered and complicated user interface that is difficult to read. The disadvantages of the Oral-B Smart Series 5000 toothbrush are related to its physical dimensions and audible feedback. The specially engineered sonic powered toothbrush with unique sensing afid control technologies is surprising to use with its changes in speeds, brush movements, and resulting changes in audible feedback.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Optimization of geometric characteristics to improve sensing performance of MEMS piezoresistive strain sensors

NASA Astrophysics Data System (ADS)

Mohammed, Ahmed A. S.; Moussa, Walied A.; Lou, Edmond

2010-01-01

In this paper, the design of MEMS piezoresistive strain sensor is described. ANSYS®, finite element analysis (FEA) software, was used as a tool to model the performance of the silicon-based sensor. The incorporation of stress concentration regions (SCRs), to localize stresses, was explored in detail. This methodology employs the structural design of the sensor silicon carrier. Therefore, the induced strain in the sensing chip yielded stress concentration in the vicinity of the SCRs. Hence, this concept was proved to enhance the sensor sensitivity. Another advantage of the SCRs is to reduce the sensor transverse gauge factor, which offered a great opportunity to develop a MEMS sensor with minimal cross sensitivity. Two basic SCR designs were studied. The depth of the SCRs was also investigated. Moreover, FEA simulation is utilized to investigate the effect of the sensing element depth on the sensor sensitivity. Simulation results showed that the sensor sensitivity is independent of the piezoresistors' depth. The microfabrication process flow was introduced to prototype the different sensor designs. The experiments covered operating temperature range from -50 °C to +50 °C. Finally, packaging scheme and bonding adhesive selection were discussed. The experimental results showed good agreement with the FEA simulation results. The findings of this study confirmed the feasibility of introducing SCRs in the sensor silicon carrier to improve the sensor sensitivity while using relatively high doping levels (5 × 1019 atoms cm-3). The fabricated sensors have a gauge factor about three to four times higher compared to conventional thin-foil strain gauges.

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

Sulfophenyl-Functionalized Reduced Graphene Oxide Networks on Electrospun 3D Scaffold for Ultrasensitive NO₂ Gas Sensor.

PubMed

Zou, Bin; Guo, Yunlong; Shen, Nannan; Xiao, Anshan; Li, Mingjun; Zhu, Liang; Wan, Pengbo; Sun, Xiaoming

2017-12-19

Ultrasensitive room temperature real-time NO₂ sensors are highly desirable due to potential threats on environmental security and personal respiratory. Traditional NO₂ gas sensors with highly operated temperatures (200-600 °C) and limited reversibility are mainly constructed from semiconducting oxide-deposited ceramic tubes or inter-finger probes. Herein, we report the functionalized graphene network film sensors assembled on an electrospun three-dimensional (3D) nanonetwork skeleton for ultrasensitive NO₂ sensing. The functional 3D scaffold was prepared by electrospinning interconnected polyacrylonitrile (PAN) nanofibers onto a nylon window screen to provide a 3D nanonetwork skeleton. Then, the sulfophenyl-functionalized reduced graphene oxide (SFRGO) was assembled on the electrospun 3D nanonetwork skeleton to form SFRGO network films. The assembled functionalized graphene network film sensors exhibit excellent NO₂ sensing performance (10 ppb to 20 ppm) at room temperature, reliable reversibility, good selectivity, and better sensing cycle stability. These improvements can be ascribed to the functionalization of graphene with electron-withdrawing sulfophenyl groups, the high surface-to-volume ratio, and the effective sensing channels from SFRGO wrapping onto the interconnected 3D scaffold. The SFRGO network-sensing film has the advantages of simple preparation, low cost, good processability, and ultrasensitive NO₂ sensing, all advantages that can be utilized for potential integration into smart windows and wearable electronic devices for real-time household gas sensors.

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

Field-effect sensors - from pH sensing to biosensing: sensitivity enhancement using streptavidin-biotin as a model system.

PubMed

Lowe, Benjamin M; Sun, Kai; Zeimpekis, Ioannis; Skylaris, Chris-Kriton; Green, Nicolas G

2017-11-06

Field-Effect Transistor sensors (FET-sensors) have been receiving increasing attention for biomolecular sensing over the last two decades due to their potential for ultra-high sensitivity sensing, label-free operation, cost reduction and miniaturisation. Whilst the commercial application of FET-sensors in pH sensing has been realised, their commercial application in biomolecular sensing (termed BioFETs) is hindered by poor understanding of how to optimise device design for highly reproducible operation and high sensitivity. In part, these problems stem from the highly interdisciplinary nature of the problems encountered in this field, in which knowledge of biomolecular-binding kinetics, surface chemistry, electrical double layer physics and electrical engineering is required. In this work, a quantitative analysis and critical review has been performed comparing literature FET-sensor data for pH-sensing with data for sensing of biomolecular streptavidin binding to surface-bound biotin systems. The aim is to provide the first systematic, quantitative comparison of BioFET results for a single biomolecular analyte, specifically streptavidin, which is the most commonly used model protein in biosensing experiments, and often used as an initial proof-of-concept for new biosensor designs. This novel quantitative and comparative analysis of the surface potential behaviour of a range of devices demonstrated a strong contrast between the trends observed in pH-sensing and those in biomolecule-sensing. Potential explanations are discussed in detail and surface-chemistry optimisation is shown to be a vital component in sensitivity-enhancement. Factors which can influence the response, yet which have not always been fully appreciated, are explored and practical suggestions are provided on how to improve experimental design.

A scale for measuring feelings of support and security regarding cancer care in a region of Japan: a potential new endpoint of cancer care.

PubMed

Igarashi, Ayumi; Miyashita, Mitsunori; Morita, Tatsuya; Akizuki, Nobuya; Akiyama, Miki; Shirahige, Yutaka; Eguchi, Kenji

2012-02-01

Having a sense of security about the availability of care is important for cancer patients and their families. To develop a scale for the general population to evaluate feelings of support and security regarding cancer care, and to identify factors associated with a sense of security. A cross-sectional anonymous questionnaire was administered to 8000 subjects in four areas of Japan. Sense of security was measured using five statements and using a seven-point Likert scale: "If I get cancer 1) I would feel secure in receiving cancer treatment, 2) my pain would be well relieved, 3) medical staff will adequately respond to my concerns and pain, 4) I would feel secure as a variety of medical care services are available, and 5) I would feel secure in receiving care at home." We performed an exploratory factor analysis as well as uni- and multivariate analyses to examine factors associated with such a sense of security. The five items regarding sense of security were aggregated into one factor, and Cronbach's α was 0.91. In the Yamagata area where palliative care services were not available, the sense of security was significantly lower than in the other three regions. Female gender (P=0.035), older age (P<0.001), and having cancer (P<0.001) were significantly associated with a strong sense of security. A new scale that evaluates sense of security with regard to cancer care was developed. Future studies should examine whether establishing a regional health care system that provides quality palliative care could improve the sense of security of the general population. Copyright © 2012 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

On the asymptotic optimality and improved strategies of SPTB heuristic for open-shop scheduling problem

NASA Astrophysics Data System (ADS)

Bai, Danyu; Zhang, Zhihai

2014-08-01

This article investigates the open-shop scheduling problem with the optimal criterion of minimising the sum of quadratic completion times. For this NP-hard problem, the asymptotic optimality of the shortest processing time block (SPTB) heuristic is proven in the sense of limit. Moreover, three different improvements, namely, the job-insert scheme, tabu search and genetic algorithm, are introduced to enhance the quality of the original solution generated by the SPTB heuristic. At the end of the article, a series of numerical experiments demonstrate the convergence of the heuristic, the performance of the improvements and the effectiveness of the quadratic objective.

Integrated Sensing Processor, Phase 2

DTIC Science & Technology

2005-12-01

performance analysis for several baseline classifiers including neural nets, linear classifiers, and kNN classifiers. Use of CCDR as a preprocessing step...below the level of the benchmark non-linear classifier for this problem ( kNN ). Furthermore, the CCDR preconditioned kNN achieved a 10% improvement over...the benchmark kNN without CCDR. Finally, we found an important connection between intrinsic dimension estimation via entropic graphs and the optimal

The suitability of remotely sensed soil moisture for improving operational flood forecasting

NASA Astrophysics Data System (ADS)

Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

2014-06-01

We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model (LISFLOOD) for flood predictions with lead times of up to 10 days. For this study, satellite-derived soil moisture from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) and SMOS (Soil Moisture and Ocean Salinity) is assimilated into the LISFLOOD model for the Upper Danube Basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into the hydrological model, an ensemble Kalman filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure increased performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation data set. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the mean absolute error (MAE) of the ensemble mean is reduced by 35%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of baseflows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the continuous ranked probability score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more observational data is assimilated into the system. The added values of the satellite data is largest when these observations are assimilated in combination with distributed discharge observations. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

Quantitative optical imaging and sensing by joint design of point spread functions and estimation algorithms

NASA Astrophysics Data System (ADS)

Quirin, Sean Albert

The joint application of tailored optical Point Spread Functions (PSF) and estimation methods is an important tool for designing quantitative imaging and sensing solutions. By enhancing the information transfer encoded by the optical waves into an image, matched post-processing algorithms are able to complete tasks with improved performance relative to conventional designs. In this thesis, new engineered PSF solutions with image processing algorithms are introduced and demonstrated for quantitative imaging using information-efficient signal processing tools and/or optical-efficient experimental implementations. The use of a 3D engineered PSF, the Double-Helix (DH-PSF), is applied as one solution for three-dimensional, super-resolution fluorescence microscopy. The DH-PSF is a tailored PSF which was engineered to have enhanced information transfer for the task of localizing point sources in three dimensions. Both an information- and optical-efficient implementation of the DH-PSF microscope are demonstrated here for the first time. This microscope is applied to image single-molecules and micro-tubules located within a biological sample. A joint imaging/axial-ranging modality is demonstrated for application to quantifying sources of extended transverse and axial extent. The proposed implementation has improved optical-efficiency relative to prior designs due to the use of serialized cycling through select engineered PSFs. This system is demonstrated for passive-ranging, extended Depth-of-Field imaging and digital refocusing of random objects under broadband illumination. Although the serialized engineered PSF solution is an improvement over prior designs for the joint imaging/passive-ranging modality, it requires the use of multiple PSFs---a potentially significant constraint. Therefore an alternative design is proposed, the Single-Helix PSF, where only one engineered PSF is necessary and the chromatic behavior of objects under broadband illumination provides the necessary information transfer. The matched estimation algorithms are introduced along with an optically-efficient experimental system to image and passively estimate the distance to a test object. An engineered PSF solution is proposed for improving the sensitivity of optical wave-front sensing using a Shack-Hartmann Wave-front Sensor (SHWFS). The performance limits of the classical SHWFS design are evaluated and the engineered PSF system design is demonstrated to enhance performance. This system is fabricated and the mechanism for additional information transfer is identified.

Benchmarking reference services: an introduction.

PubMed

Marshall, J G; Buchanan, H S

1995-01-01

Benchmarking is based on the common sense idea that someone else, either inside or outside of libraries, has found a better way of doing certain things and that your own library's performance can be improved by finding out how others do things and adopting the best practices you find. Benchmarking is one of the tools used for achieving continuous improvement in Total Quality Management (TQM) programs. Although benchmarking can be done on an informal basis, TQM puts considerable emphasis on formal data collection and performance measurement. Used to its full potential, benchmarking can provide a common measuring stick to evaluate process performance. This article introduces the general concept of benchmarking, linking it whenever possible to reference services in health sciences libraries. Data collection instruments that have potential application in benchmarking studies are discussed and the need to develop common measurement tools to facilitate benchmarking is emphasized.

Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Cox, Cary M.

This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work also explores the concept of an edge within hyperspectral space, the relative importance of spatial and spectral resolutions as they pertain to HSI edge detection and how effectively compressed HSI data improves edge detection results. The HSI edge detection experiments yielded valuable insights into the algorithms' strengths, weaknesses and optimal alignment to remote sensing applications. The gradient-based edge operator produced strong edge planes across a range of evaluation measures and applications, particularly with respect to false negatives, unbroken edges, urban mapping, vegetation mapping and oil spill mapping applications. False positives and uncompressed HSI data presented occasional challenges to the algorithm. The HySPADE edge operator produced satisfactory results with respect to localization, single-point response, oil spill mapping and trace chemical detection, and was challenged by false positives, declining spectral resolution and vegetation mapping applications. The level set edge detector produced high-quality edge planes for most tests and demonstrated strong performance with respect to false positives, single-point response, oil spill mapping and mineral mapping. False negatives were a regular challenge for the level set edge detection algorithm. Finally, HSI data optimized for spectral information compression and noise was shown to improve edge detection performance across all three algorithms, while the gradient-based algorithm and HySPADE demonstrated significant robustness to declining spectral and spatial resolutions.

Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

NASA Astrophysics Data System (ADS)

Lin, S.; Li, J.; Liu, Q.

2018-04-01

Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

MEMS SoC: observer-based coplanar gyro-free inertial measurement unit

NASA Astrophysics Data System (ADS)

Chen, Tsung-Lin; Park, Sungsu

2005-09-01

This paper presents a novel design of a coplanar gyro-free inertial measurement unit (IMU) that consists of seven to nine single-axis linear accelerometers, and it can be utilized to perform the six DOF measurements for an object in motion. Unlike other gyro-fee IMUs, this design uses redundant accelerometers and state estimation techniques to facilitate the in situ and mass fabrication for the employed accelerometers. The alignment error from positioning accelerometers onto a measurement unit and the fabrication cost of an IMU can greatly be reduced. The outputs of the proposed design are three linear accelerations and three angular velocities. As compared to other gyro-free IMUs, the proposed design uses less integral operation and thus improves its sensing resolution and drifting problem. The sensing resolution of a gyro-free IMU depends on the sensing resolution of the employed accelerometers as well as the size of the measurement unit. Simulation results indicate that the sensing resolution of the proposed design is 2° s-1 for the angular velocity and 10 μg for the linear acceleration when nine single-axis accelerometers, each with 10 μg sensing resolution, are deployed on a 4 inch diameter disc. Also, thanks to the iterative EKF algorithm, the angle estimation error is within 10-3 deg at 2 s.

Reliable fusion of control and sensing in intelligent machines. Thesis

NASA Technical Reports Server (NTRS)

Mcinroy, John E.

1991-01-01

Although robotics research has produced a wealth of sophisticated control and sensing algorithms, very little research has been aimed at reliably combining these control and sensing strategies so that a specific task can be executed. To improve the reliability of robotic systems, analytic techniques are developed for calculating the probability that a particular combination of control and sensing algorithms will satisfy the required specifications. The probability can then be used to assess the reliability of the design. An entropy formulation is first used to quickly eliminate designs not capable of meeting the specifications. Next, a framework for analyzing reliability based on the first order second moment methods of structural engineering is proposed. To ensure performance over an interval of time, lower bounds on the reliability of meeting a set of quadratic specifications with a Gaussian discrete time invariant control system are derived. A case study analyzing visual positioning in robotic system is considered. The reliability of meeting timing and positioning specifications in the presence of camera pixel truncation, forward and inverse kinematic errors, and Gaussian joint measurement noise is determined. This information is used to select a visual sensing strategy, a kinematic algorithm, and a discrete compensator capable of accomplishing the desired task. Simulation results using PUMA 560 kinematic and dynamic characteristics are presented.

UV-light-assisted ethanol sensing characteristics of g-C3N4/ZnO composites at room temperature

NASA Astrophysics Data System (ADS)

Zhai, Jiali; Wang, Tao; Wang, Chuang; Liu, Dechen

2018-05-01

A highly efficient UV-light-assisted room temperature sensor based on g-C3N4/ZnO composites were prepared by an in situ precipitation method. The thermostability, composition, structure, and morphology properties of the as-prepared g-C3N4/ZnO composites were characterized by TGA, XRD, FT-IR, TEM, and XPS, respectively. And then, we studied the ethanol (C2H5OH) sensing performance of the g-C3N4/ZnO composites at the room temperature. Compared with pure ZnO and g-C3N4, the gas sensing activity of g-C3N4/ZnO composites was greatly improved at room temperature, for example, the g-C3N4/ZnO-8% composites showed an obvious response of 121-40 ppm C2H5OH at room temperature, which was 60 times higher than the pure ZnO based on the sensors under the same condition. The great enhancement of the C2H5OH sensing properties of composites can be understood by the efficient separation of photogenerated charge carriers of g-C3N4/ZnO heterogeneous and the UV-light catalytic effect. Finally, a possible mechanism for the gas sensing activity was proposed.

Design of a Novel Flexible Capacitive Sensing Mattress for Monitoring Sleeping Respiratory

PubMed Central

Chang, Wen-Ying; Huang, Chien-Chun; Chen, Chi-Chun; Chang, Chih-Cheng; Yang, Chin-Lung

2014-01-01

In this paper, an algorithm to extract respiration signals using a flexible projected capacitive sensing mattress (FPCSM) designed for personal health assessment is proposed. Unlike the interfaces of conventional measurement systems for poly-somnography (PSG) and other alternative contemporary systems, the proposed FPCSM uses projected capacitive sensing capability that is not worn or attached to the body. The FPCSM is composed of a multi-electrode sensor array that can not only observe gestures and motion behaviors, but also enables the FPCSM to function as a respiration monitor during sleep using the proposed approach. To improve long-term monitoring when body movement is possible, the FPCSM enables the selection of data from the sensing array, and the FPCSM methodology selects the electrodes with the optimal signals after the application of a channel reduction algorithm that counts the reversals in the capacitive sensing signals as a quality indicator. The simple algorithm is implemented in the time domain. The FPCSM system is used in experimental tests and is simultaneously compared with a commercial PSG system for verification. Multiple synchronous measurements are performed from different locations of body contact, and parallel data sets are collected. The experimental comparison yields a correlation coefficient of 0.88 between FPCSM and PSG, demonstrating the feasibility of the system design. PMID:25420152

Extensibility effect of poly(3-hexylthiophene) on the glucose sensing performance of mixed poly(3-hexylthiophene)/octadecylamine/glucose oxidase Langmuir-Blodgett films.

PubMed

Wang, Ke-Hsuan; Hsu, Wen-Ping; Chen, Liang-Huei; Lin, Wei-Don; Lee, Yuh-Lang

2017-07-01

Poly(3-hexylthiophene) (P3HT) is utilized as a material to enhance the glucose sensing performance of glucose oxidase (GOx) Langmuir-Blodgett (LB) films. To enhance the extensibility and homogeneity of the P3HT in the LB films, octadecylamine (ODA) is introduced. The characteristics of the mixed P3HT/ODA Langmuir monolayers are investigated first and then, utilized as template layers to adsorb GOx from the subphase, preparing P3HT/ODA/GOx Langmuir-Blodgett films for glucose sensing. The results show that P3HT molecules tend to aggregate at the air/liquid interface and, furthermore, the P3HT monolayer has a weak ability to adsorb GOx from the subphase. By using mixed P3HT/ODA monolayer, the presence of ODA not only inhibits the aggregation of P3HT, but also increases the adsorption ability of the monolayer to GOx. The extensibility of P3HT and the homogeneity of the P3HT/ODA monolayers are closely related to the concentration of P3HT/ODA stock solutions. On the glucose sensing experiments, the performance of the P3HT/ODA/GOx LB film is greatly improved due to the presence of P3HT and, furthermore, the sensibility increases with increasing extensibility of P3HT molecules. The best sensitivity achieved for the P3HT/ODA/GOx film is 5.4μAmM -1 cm -2 which is over two times the value obtained by the ODA/GOx film (2.3μAmM -1 cm -2 ). Copyright © 2017 Elsevier B.V. All rights reserved.

Two-D results on human operator perception

NASA Technical Reports Server (NTRS)

Siapkara, A. A.; Sheridan, T. B.

1981-01-01

The application of multidimensional scaling methodology in human factors engineering is presented. The nonorthogonality of internally perceived task variables is exhibited for first and second order plants with both dependent and independent task variables. Directions of operator preference are shown for actual performance, pilot opinion rating, and subjective measures of fatigue, adaptability, and system recognition. Improvement of performance in second order systems is exhibited by the use of bang-bang feedback information. Dissimilarity measures for system comparison are suggested in order to account for human operator rotations and subjective sense of time.

Cost and performance: complements for improvement.

PubMed

Rouse, Paul; Harrison, Julie; Turner, Nikki

2011-10-01

Activity-based costing (ABC) and Data Envelopment Analysis (DEA) share similar views of resource consumption in the production of outputs. While DEA has a high level focus typically using aggregated data in the form of inputs and outputs, ABC is more detailed and oriented around very disaggregated data. We use a case study of immunisation activities in 24 New Zealand primary care practices to illustrate how DEA and ABC can be used in conjunction to improve performance analysis and benchmarking. Results show that practice size, socio-economic environment, parts of the service delivery process as well as regular administrative tasks are major cost and performance drivers for general practices in immunisation activities. It is worth noting that initial analyses of the ABC results, using contextual information and conventional methods of analysis such as regression and correlations, did not result in any patterns of significance. Reorganising this information using the DEA efficiency scores has revealed trends that make sense to practitioners and provide insights into where to place efforts for improvement.

Benefits of Using Remote Sensing for Health Alerts and Chronic Respiratory Exposures

NASA Technical Reports Server (NTRS)

Luvall, J. C.

2010-01-01

Respiratory diseases such as asthma can be triggered by environmental conditions that can be monitored using Earth observing data and environmental forecast models. Frequent dust storms in the southwestern United States, the annual cycle of juniper pollen events in the spring, and increased aerosol and ozone concentrations in summer, are health concerns shared by the community at large. Being able to forecast the occurrence of these events would help the health care community prepare for increased visits to emergency rooms, as well as allow public health officials to issue alerts to affected persons. This information also is important to epidemiologists for analyzing long-term trends and impacts of these events on the health and well-being of the community. Earth observing data collected by remote sensing platforms are important for improving the performance of models that can forecast these events, and in turn, improve products and information for decision-making by public health authorities. This presentation will discuss the benefits of using remote sensing data for forecasting environmental events that can adversely affect individuals with respiratory ailments. The presentations will include a brief discussion on relevant Earth observing data, the forecast models used, and societal benefits of the resulting products and information. Several NASA-funded projects will be highlighted as examples

Potential impact of remote sensing data on sea-state analysis and prediction

NASA Technical Reports Server (NTRS)

Cardone, V. J.

1983-01-01

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Progress in the Development of CdZnTe Unipolar Detectors for Different Anode Geometries and Data Corrections

PubMed Central

Zhang, Qiushi; Zhang, Congzhe; Lu, Yanye; Yang, Kun; Ren, Qiushi

2013-01-01

CdZnTe detectors have been under development for the past two decades, providing good stopping power for gamma rays, lightweight camera heads and improved energy resolution. However, the performance of this type of detector is limited primarily by incomplete charge collection problems resulting from charge carriers trapping. This paper is a review of the progress in the development of CdZnTe unipolar detectors with some data correction techniques for improving performance of the detectors. We will first briefly review the relevant theories. Thereafter, two aspects of the techniques for overcoming the hole trapping issue are summarized, including irradiation direction configuration and pulse shape correction methods. CdZnTe detectors of different geometries are discussed in detail, covering the principal of the electrode geometry design, the design and performance characteristics, some detector prototypes development and special correction techniques to improve the energy resolution. Finally, the state of art development of 3-D position sensing and Compton imaging technique are also discussed. Spectroscopic performance of CdZnTe semiconductor detector will be greatly improved even to approach the statistical limit on energy resolution with the combination of some of these techniques. PMID:23429509

Applications of FBG sensors on telecom satellites

NASA Astrophysics Data System (ADS)

Abad, S.; Araújo, F. M.; Ferreira, L. A.; Pedersen, F.; Esteban, M. A.; McKenzie, I.; Karafolas, N.

2017-11-01

Monitoring needs of spacecraft are rapidly increasing due to new and more challenging missions, along with demands to reduce launching costs by minimizing the manufacture, assembly, integration and test time and employing new low weight materials balanced by the need for maximizing system lifetime while maintaining good reliability. Conventional electronic sensors are characterized by their low multiplexing capability and their EMI/RF susceptibility and it is in this scenario that Fiber Optic Sensors (FOS) in general, and more specifically Fiber Bragg Grating (FBG) technology offers important benefits, improving in various ways the already deployed sensing subsystems (e.g. reducing the weight associated with sensor cabling, increasing the number of sensing points) and enabling new monitoring applications that were not possible by using conventional sensing technologies. This work presents the activities performed and the lessons learnt in the frame of ESA's ARTES-5 project "Fiber Optic Sensing Subsystem for Spacecraft Health Monitoring in Telecommunication Satellites". This project finished in July 2009, with the implementation and testing of two different demonstrators employing FBG sensor technology: FBG sensors for temperature monitoring in high voltage environments, and in particular in several parts of electric propulsion subsystems [1], and FBG sensors for thermal monitoring of array-antennas during RF testing [2]. In addition, the contacts performed with different actors within the space community allowed the identification of a special area of interest for the substitution of regular thermocouple instrumentation by FBG technology for thermal vacuum ground testing of satellites.

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Experiment Development

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Applications of the similarity relations in radiative transfer to remote sensing implementation and flux simulation

NASA Astrophysics Data System (ADS)

Yang, P.; Ding, J.; Tang, G.; King, M. D.; Platnick, S. E.; Meyer, K.; Mlawer, E. J.

2017-12-01

Van de Hulst (1974) showed several quasi-invariant quantities in radiative transfer concerning multiple scattering. Recently, we illustrated that the aforesaid quasi-invariant quantities are useful in remote sensing of ice cloud properties from spaceborne radiometric observations (Ding et al. 2017). Specifically, the overall performance of an ice cloud optical property model can be estimated without carrying out detailed retrieval implementation. In this presentation, we will review the radiative transfer similarity relations and some recent results including the study by Ding et al. (2017). Furthermore, we will illustrate an application of the similarity relations to improvement of broadband radiative flux computation. For example, the Rapid Radiative Transfer Model (RRTM, Mlawer et al, 1999) does not consider multiple scattering in the longwave spectral regime (RRTMG-LW) ("G" indicates a version suitable for GCM applications). We show that the similarity relations can be used to effectively improve the accuracy of RRTMG-LW without increasing computational effort.

High-Performance Piezoresistive MEMS Strain Sensor with Low Thermal Sensitivity

PubMed Central

Mohammed, Ahmed A. S.; Moussa, Walied A.; Lou, Edmond

2011-01-01

This paper presents the experimental evaluation of a new piezoresistive MEMS strain sensor. Geometric characteristics of the sensor silicon carrier have been employed to improve the sensor sensitivity. Surface features or trenches have been introduced in the vicinity of the sensing elements. These features create stress concentration regions (SCRs) and as a result, the strain/stress field was altered. The improved sensing sensitivity compensated for the signal loss. The feasibility of this methodology was proved in a previous work using Finite Element Analysis (FEA). This paper provides the experimental part of the previous study. The experiments covered a temperature range from −50 °C to +50 °C. The MEMS sensors are fabricated using five different doping concentrations. FEA is also utilized to investigate the effect of material properties and layer thickness of the bonding adhesive on the sensor response. The experimental findings are compared to the simulation results to guide selection of bonding adhesive and installation procedure. Finally, FEA was used to analyze the effect of rotational/alignment errors. PMID:22319384

Ultrahigh Temperature Capacitive Pressure Sensor

NASA Technical Reports Server (NTRS)

Harsh, Kevin

2014-01-01

Robust, miniaturized sensing systems are needed to improve performance, increase efficiency, and track system health status and failure modes of advanced propulsion systems. Because microsensors must operate in extremely harsh environments, there are many technical challenges involved in developing reliable systems. In addition to high temperatures and pressures, sensing systems are exposed to oxidation, corrosion, thermal shock, fatigue, fouling, and abrasive wear. In these harsh conditions, sensors must be able to withstand high flow rates, vibration, jet fuel, and exhaust. In order for existing and future aeropropulsion turbine engines to improve safety and reduce cost and emissions while controlling engine instabilities, more accurate and complete sensor information is necessary. High-temperature (300 to 1,350 C) capacitive pressure sensors are of particular interest due to their high measurement bandwidth and inherent suitability for wireless readout schemes. The objective of this project is to develop a capacitive pressure sensor based on silicon carbon nitride (SiCN), a new class of high-temperature ceramic materials, which possesses excellent mechanical and electric properties at temperatures up to 1,600 C.

The Robonaut 2 Hand - Designed to do Work with Tools

NASA Technical Reports Server (NTRS)

Bridgwater, L. B.; Ihrke, C. A.; Diftler, M. A.; Abdallah, M. E.; Radford, N. A.; Rogers, J. M.; Yayathi, S.; Askew, R. S.; Linn, D. M.

2011-01-01

The second generation Robonaut hand has many advantages over its predecessor. This mechatronic device is more dexterous and has improved force control and sensing giving it the capability to grasp and actuate a wider range of tools. It can achieve higher peak forces at higher speeds than the original. Developed as part of a partnership between General Motors and NASA, the hand is designed to more closely approximate a human hand. Having a more anthropomorphic design allows the hand to attain a larger set of useful grasps for working with human interfaces. Key to the hand s improved performance is the use of lower friction drive elements and a redistribution of components from the hand to the forearm, permitting more sensing in the fingers and palm where it is most important. The following describes the design, mechanical/electrical integration, and control features of the hand. Lessons learned during the development and initial operations along with planned refinements to make it more effective are presented.

Lack of interaction between sensing-intuitive learning styles and problem-first versus information-first instruction: a randomized crossover trial.

PubMed

Cook, David A; Thompson, Warren G; Thomas, Kris G; Thomas, Matthew R

2009-03-01

Adaptation to learning styles has been proposed to enhance learning. We hypothesized that learners with sensing learning style would perform better using a problem-first instructional method while intuitive learners would do better using an information-first method. Randomized, controlled, crossover trial. Resident ambulatory clinics. 123 internal medicine residents. Four Web-based modules in ambulatory internal medicine were developed in both "didactic" (information first, followed by patient problem and questions) and "problem" (case and questions first, followed by information) format. Knowledge posttest, format preference, learning style (Index of Learning Styles). Knowledge scores were similar between the didactic (mean +/- standard error, 83.0 +/- 0.8) and problem (82.3 +/- 0.8) formats (p = .42; 95% confidence interval [CI] for difference, -2.3 to 0.9). There was no difference between formats in regression slopes of knowledge scores on sensing-intuitive scores (p = .63) or in analysis of knowledge scores by styles classification (sensing 82.5 +/- 1.0, intermediate 83.7 +/- 1.2, intuitive 81.0 +/- 1.5; p = .37 for main effect, p = .59 for interaction with format). Format preference was neutral (3.2 +/- 0.2 [1 strongly prefers didactic, 6 strongly prefers problem], p = .12), and there was no association between learning styles and preference (p = .44). Formats were similar in time to complete modules (43.7 +/- 2.2 vs 43.2 +/- 2.2 minutes, p = .72). Starting instruction with a problem (versus employing problems later on) may not improve learning outcomes. Sensing and intuitive learners perform similarly following problem-first and didactic-first instruction. Results may apply to other instructional media.

Properties of centralized cooperative sensing in cognitive radio networks

NASA Astrophysics Data System (ADS)

Skokowski, Paweł; Malon, Krzysztof; Łopatka, Jerzy

2017-04-01

Spectrum sensing is a functionality that enables network creation in the cognitive radio technology. Spectrum sensing is use for building the situation awareness knowledge for better use of radio resources and to adjust network parameters in case of jamming, interferences from legacy systems, decreasing link quality caused e.g. by nodes positions changes. This paper presents results from performed tests to compare cooperative centralized sensing versus local sensing. All tests were performed in created simulator developed in Matlab/Simulink environment.

First year medical students' learning style preferences and their correlation with performance in different subjects within the medical course.

PubMed

Hernández-Torrano, Daniel; Ali, Syed; Chan, Chee-Kai

2017-08-08

Students commencing their medical training arrive with different educational backgrounds and a diverse range of learning experiences. Consequently, students would have developed preferred approaches to acquiring and processing information or learning style preferences. Understanding first-year students' learning style preferences is important to success in learning. However, little is understood about how learning styles impact learning and performance across different subjects within the medical curriculum. Greater understanding of the relationship between students' learning style preferences and academic performance in specific medical subjects would be valuable. This cross-sectional study examined the learning style preferences of first-year medical students and how they differ across gender. This research also analyzed the effect of learning styles on academic performance across different subjects within a medical education program in a Central Asian university. A total of 52 students (57.7% females) from two batches of first-year medical school completed the Index of Learning Styles Questionnaire, which measures four dimensions of learning styles: sensing-intuitive; visual-verbal; active-reflective; sequential-global. First-year medical students reported preferences for visual (80.8%) and sequential (60.5%) learning styles, suggesting that these students preferred to learn through demonstrations and diagrams and in a linear and sequential way. Our results indicate that male medical students have higher preference for visual learning style over verbal, while females seemed to have a higher preference for sequential learning style over global. Significant associations were found between sensing-intuitive learning styles and performance in Genetics [β = -0.46, B = -0.44, p < 0.01] and Anatomy [β = -0.41, B = -0.61, p < 0.05] and between sequential-global styles and performance in Genetics [β = 0.36, B = 0.43, p < 0.05]. More specifically, sensing learners were more likely to perform better than intuitive learners in the two subjects and global learners were more likely to perform better than sequential learners in Genetics. This knowledge will be helpful to individual students to improve their performance in these subjects by adopting new sensing learning techniques. Instructors can also benefit by modifying and adapting more appropriate teaching approaches in these subjects. Future studies to validate this observation will be valuable.

Combining machine learning and remotely sensed bandratios to investigate chlorophyll content and photosynthetic processes

NASA Astrophysics Data System (ADS)

Gholizadeh, Hamed

Photosynthesis in aquatic and terrestrial ecosystems is the key component of the food chain and the most important driver of the global carbon cycle. Therefore, estimation of photosynthesis at large spatial scales is of great scientific importance and can only practically be achieved by remote sensing data and techniques. In this dissertation, remotely sensed information and techniques, as well as field measurements, are used to improve current approaches of assessing photosynthetic processes. More specifically, three topics are the focus here: (1) investigating the application of spectral vegetation indices as proxies for terrestrial chlorophyll in a mangrove ecosystem, (2) evaluating and improving one of the most common empirical ocean-color algorithms (OC4), and (3) developing an improved approach based on sunlit-to-shaded scaled photochemical reflectance index (sPRI) ratios for detecting drought signals in a deciduous forest at eastern United States. The results indicated that although the green normalized difference vegetation index (GNDVI) is an efficient proxy for terrestrial chlorophyll content, there are opportunities to improve the performance of vegetation indices by optimizing the band weights. In regards to the second topic, we concluded that the parameters of the OC4 algorithm and similar empirical models should be tuned regionally and the addition of sea-surface temperature makes the global ocean-color approaches more valid. Results obtained from the third topic showed that considering shaded and sunlit portions of the canopy (i.e., two-leaf models instead of single big leaf models) and taking into account the divergent stomatal behavior of the species (i.e. isohydric and anisohydric) can improve the capability of sPRI in detecting drought. In addition to investigating the photosynthetic processes, the other common theme of the three research topics is the evaluation of "off- the-shelf" solutions to remote-sensing problems. Although widely used approaches such as normalized difference vegetation index (NDVI) are easy to apply and are often efficient choices in remote sensing applications, the use of these approaches should be justified and their shortcomings need to be considered in the context of the research application. When developing new remote sensing approaches, special attention should be paid to (1) initial data analysis such as statistical data transformations (e.g. Tukey ladder-of-powers transformation) and (2) rigorous validation design by creating separate training and validation data sets preferably using both field measurements and satellite-based data. Developing a sound approach and applying a rigorous validation methodology go hand in hand. In sum, all approaches have advantages and disadvantages or as George Box puts it, "all models are wrong but some are useful".

Preparation and Humidity Sensing Properties of KCl/MCM-41 Composite

NASA Astrophysics Data System (ADS)

Liu, Li; Kou, Li-Ying; Zhong, Zhi-Cheng; Wang, Lian-Yuan; Liu, Li-Fang; Li, Wei

2010-05-01

KCl/mobil composition of matter-41 (MCM-41) composite has been synthesized via a heat-treating process and characterized by x-ray diffraction, high resolution transmission electron microscopy, and nitrogen adsorption/desorption isotherms. In contrast with pure MCM-41, KCl/MCM-41 composite exhibits improved humidity sensing properties within the relative humidity range of 11-95%. The impedance of KCl/MCM-41 composite changes by about four orders of magnitude over the whole humidity range with the response time and the recovery times are about 30 s and 35 s, respectively. Small humidity hysteresis and good stability are also observed based on our product. These results make our product a good candidate in fabricating humidity sensors with high performances and low synthetic complexity.

Fibre Optic Mechanical Sensors For Aerospace Applications

NASA Astrophysics Data System (ADS)

Batchellor, C. R.; Dakin, J. P.; Pearce, D. A. J.

1989-04-01

A fiber optic multisensor methane detection system matched to topology and environment of a coal mine is reported. The system involves time domain multiplexed (TDM) methane sensors based on selective absorption of source radiation by atomic or molecular species in the gas sensing heads. A two-wavelength ratiometric approach allows simple self referencing, cancels out errors arising from other contaminants, and improves the measurement contrast. The laboratory system consists of a high radiance LED source, multimode fiber, optical sensing head, optical bandpass filters, and involves synchronous detection with low noise photodiodes and a lock-in amplifier. Detection sensitivity upon spectral resolution of the optical filters has also been investigated and described. The system performance was evaluated and the results are presented.

Self-Referenced Fiber Optic System For Remote Methane Detection

NASA Astrophysics Data System (ADS)

Zientkiewicz, Jacek K.

1989-10-01

The paper discusses a fiber optic multisensor methane detection system matched to topology and environment of the underground mine. The system involves time domain multiplexed (TDM) methane sensors based on selective absorption of source radiation by atomic/molecular species in the gas sensing heads. A two-wavelength ratiometric approach allows simple self-referencing, cancels out errors arising from other contaminants, and improves the measurement contrast. The laboratory system consists of a high radiance LED source, multimode fiber, optical sensing head, optical bandpass filters, and involves synchronous detection with low noise photodiodes and a lock-in amplifier. Detection sensitivity versus spectral resolution of the optical filters has also been investigated and described. The system performance was evaluated and the results are presented.

Mobile Phones Democratize and Cultivate Next-Generation Imaging, Diagnostics and Measurement Tools

PubMed Central

Ozcan, Aydogan

2014-01-01

In this article, I discuss some of the emerging applications and the future opportunities and challenges created by the use of mobile phones and their embedded components for the development of next-generation imaging, sensing, diagnostics and measurement tools. The massive volume of mobile phone users, which has now reached ~7 billion, drives the rapid improvements of the hardware, software and high-end imaging and sensing technologies embedded in our phones, transforming the mobile phone into a cost-effective and yet extremely powerful platform to run e.g., biomedical tests and perform scientific measurements that would normally require advanced laboratory instruments. This rapidly evolving and continuing trend will help us transform how medicine, engineering and sciences are practiced and taught globally. PMID:24647550

Acetylcholinesterase-reduced graphene oxide hybrid films for organophosphorus neurotoxin sensing via quartz crystal microbalance

NASA Astrophysics Data System (ADS)

Tang, Shi; Ma, Wenying; Xie, Guangzhong; Su, Yuanjie; Jiang, Yadong

2016-09-01

An acetylcholinesterase (AChE)-reduced graphene oxide (RGO) hybrid films based biosensor enabled by quartz crystal microbalance (QCM) has been developed for the detection of organophosphorus neurotoxin in gas phase at room temperature. To improve the sensing performance, RGO was used to immobilize large quantities of enzyme and provide a favorable microenvironment to maintain the enzyme activity. The experimental results reveal that the response of AChE-RGO/glutaraldehyde based sensors is about 8 times larger than that of the AChE with the sensitivity of 1.583 Hz/mg/m3. 1.0 mg amount of RGO, 5% concentration of glutaraldehyde and pH 6.8 is the optimal condition of this biosensor.

Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

PubMed

Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

2014-03-24

Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

Wireless Sensor Array Network DoA Estimation from Compressed Array Data via Joint Sparse Representation.

PubMed

Yu, Kai; Yin, Ming; Luo, Ji-An; Wang, Yingguan; Bao, Ming; Hu, Yu-Hen; Wang, Zhi

2016-05-23

A compressive sensing joint sparse representation direction of arrival estimation (CSJSR-DoA) approach is proposed for wireless sensor array networks (WSAN). By exploiting the joint spatial and spectral correlations of acoustic sensor array data, the CSJSR-DoA approach provides reliable DoA estimation using randomly-sampled acoustic sensor data. Since random sampling is performed at remote sensor arrays, less data need to be transmitted over lossy wireless channels to the fusion center (FC), and the expensive source coding operation at sensor nodes can be avoided. To investigate the spatial sparsity, an upper bound of the coherence of incoming sensor signals is derived assuming a linear sensor array configuration. This bound provides a theoretical constraint on the angular separation of acoustic sources to ensure the spatial sparsity of the received acoustic sensor array signals. The Cram e ´ r-Rao bound of the CSJSR-DoA estimator that quantifies the theoretical DoA estimation performance is also derived. The potential performance of the CSJSR-DoA approach is validated using both simulations and field experiments on a prototype WSAN platform. Compared to existing compressive sensing-based DoA estimation methods, the CSJSR-DoA approach shows significant performance improvement.

The Multi-Center Airborne Coherent Atmospheric Wind Sensor: Recent Measurements and Future Applications

NASA Technical Reports Server (NTRS)

Rothermel, Jeffry; Cutten, Dean R.; Hardesty, R. Michael; Howell, James N.; Darby, Lisa S.; Tratt, David M.; Menzies, Robert T.

1999-01-01

The coherent Doppler lidar, when operated from an airborne platform, offers a unique measurement capability for study of atmospheric dynamical and physical properties. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are at a disadvantage in terms of spatial resolution and coverage. Recent experience suggests airborne coherent Doppler lidar can yield unique wind measurements of--and during operation within--extreme weather phenomena. This paper presents the first airborne coherent Doppler lidar measurements of hurricane wind fields. The lidar atmospheric remote sensing groups of National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, National Oceanic and Atmospheric Administration (NOAA) Environmental Technology Laboratory, and Jet Propulsion Laboratory jointly developed an airborne lidar system, the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS). The centerpiece of MACAWS is the lidar transmitter from the highly successful NOAA Windvan. Other field-tested lidar components have also been used, when feasible, to reduce costs and development time. The methodology for remotely sensing atmospheric wind fields with scanning coherent Doppler lidar was demonstrated in 1981; enhancements were made and the system was reflown in 1984. MACAWS has potentially greater scientific utility, compared to the original airborne scanning lidar system, owing to a factor of approx. 60 greater energy-per-pulse from the NOAA transmitter. MACAWS development was completed and the system was first flown in 1995. Following enhancements to improve performance, the system was re-flown in 1996 and 1998. The scientific motivation for MACAWS is three-fold: obtain fundamental measurements of subgrid scale (i.e., approx. 2-200 km) processes and features which may be used to improve parameterizations in hydrological, climate, and general/regional circulation models; obtain similar datasets to improve understanding and predictive capabilities for similarly-scaled processes and features; and simulate and validate the performance of prospective satellite Doppler lidars for global tropospheric wind measurement.

The Evolution of Remotely Sensed Precipitation Products for Hydrological Applications with a Focus on the Tropical Rainfall Measurement Mission (TRMM)

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M.

2012-12-01

This study examines the evolution of how remotely sensed precipitation products have impacted hydrologic modeling from six basins across the continental United States. Precipitation products include both ground-based (Multisensor Precipitation Estimator - MPE) and space-based products. Two space-based products are from the Tropical Rainfall Measurement Mission (TRMM) and include the real-time TRMM Multi-Satellite Precipitation Analysis (TMPA-RT) and TRMM 3B42 Research product. Precipitation products are compared between early (2004-2008) and late (2008-2010) periods. Additionally, version 6 and the new version 7 of these TRMM products are examined. Watersheds examined were moderately large (1000 to 1,000 square kilometers) and included the San Pedro (Arizona), Cimarron (Oklahoma); Alapaha (Georgia), mid-Nueces (Texas), San Casimiro (Texas), and the mid-Rio Grande basins, which is a bi-national basin that spans the Texas-Mexico border. Precipitation products are used to drive streamflow simulations using the Soil Water Assessment Tool (SWAT). The main results of this study concludes that MPE is a mature remote sensing product that generally supports superior hydrologic simulations based on standard performance metrics such as mass balance error, Nash-Sutcliffe efficiency coefficient, and coefficient of persistence. TRMM products support acceptable simulations and have improved in performance between early and late periods for TMPA-RT (both versions) and version 6 of TRMM 3B42 Research in five out of the six basins examined. This improvement is related to modification of TRMM in January 2009 with the addition of more satellite data and a climatologic bias correction, which greatly improves the real-time TMPA-RT product. Conversely, version 7 of the TRMM 3B42 Research has a positive bias compared to version 6, which is translated into poorer hydrological simulations of streamflow. Future research is urgently needed to determine if the issues observed in this study are indicative of a broader problem associated with the most recent version of TRMM.

Finding Meaning: Sense Inventories for Improved Word Sense Disambiguation

ERIC Educational Resources Information Center

Brown, Susan Windisch

2010-01-01

The deep semantic understanding necessary for complex natural language processing tasks, such as automatic question-answering or text summarization, would benefit from highly accurate word sense disambiguation (WSD). This dissertation investigates what makes an appropriate and effective sense inventory for WSD. Drawing on theories and…

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

Recent advances in surface plasmon resonance imaging: detection speed, sensitivity, and portability

NASA Astrophysics Data System (ADS)

Zeng, Youjun; Hu, Rui; Wang, Lei; Gu, Dayong; He, Jianan; Wu, Shu-Yuen; Ho, Ho-Pui; Li, Xuejin; Qu, Junle; Gao, Bruce Zhi; Shao, Yonghong

2017-06-01

Surface plasmon resonance (SPR) biosensor is a powerful tool for studying the kinetics of biomolecular interactions because they offer unique real-time and label-free measurement capabilities with high detection sensitivity. In the past two decades, SPR technology has been successfully commercialized and its performance has continuously been improved with lots of engineering efforts. In this review, we describe the recent advances in SPR technologies. The developments of SPR technologies focusing on detection speed, sensitivity, and portability are discussed in details. The incorporation of imaging techniques into SPR sensing is emphasized. In addition, our SPR imaging biosensors based on the scanning of wavelength by a solid-state tunable wavelength filter are highlighted. Finally, significant advances of the vast developments in nanotechnology-associated SPR sensing for sensitivity enhancements are also reviewed. It is hoped that this review will provide some insights for researchers who are interested in SPR sensing, and help them develop SPR sensors with better sensitivity and higher throughput.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Integration of remote sensing technique and hydrologic model for monitoring tidal flat dynamics of Juiduansha in Shanghai

NASA Astrophysics Data System (ADS)

Zheng, Zongsheng; Zhou, Yunxuan; Jiang, Xuezhong

2007-06-01

Ground survey is restricted by the difficulty of access to wide-range and dynamic salt marsh. Waterline method and hydrodynamic model were investigated to construct Digital Elevation Model (DEM) at Jiudunasha Shoals. A series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of 2000-2004. The assignment of an elevation to each waterline at the satellite overpass was performed according to hydrodynamic model. The corrected waterlines labeled elevations were used to construct Triangulated Irregular Networks (TINs). Then an interpolation for each grid elevation was performed in accordance with the associated triangle. This initial DEM, produced using the corrected waterline set, was then used to refine the topography in the intertidal zone, and the model was re-run to produce improved water levels and a new DEM. This procedure was iterated by comparing modeled and actual waterlines until no further improvement occurred. Three DEMs of different intervals were built by this approach and were compared to evaluate the effect of Deep Water Channel Project (DWCP) at the north of Jiuduansha Island. Waterline method combined with numerical model, is an effective tool for constructing digital elevation model of mudflats. The result can provide invaluable information for coastal land use and engineer construction.

Fast and accurate denoising method applied to very high resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Masse, Antoine; Lefèvre, Sébastien; Binet, Renaud; Artigues, Stéphanie; Lassalle, Pierre; Blanchet, Gwendoline; Baillarin, Simon

2017-10-01

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

Exploitation of Unique Properties of Zeolites in the Development of Gas Sensors

PubMed Central

Zheng, Yangong; Li, Xiaogan; Dutta, Prabir K.

2012-01-01

The unique properties of microporous zeolites, including ion-exchange properties, adsorption, molecular sieving, catalysis, conductivity have been exploited in improving the performance of gas sensors. Zeolites have been employed as physical and chemical filters to improve the sensitivity and selectivity of gas sensors. In addition, direct interaction of gas molecules with the extraframework cations in the nanoconfined space of zeolites has been explored as a basis for developing new impedance-type gas/vapor sensors. In this review, we summarize how these properties of zeolites have been used to develop new sensing paradigms. There is a considerable breadth of transduction processes that have been used for zeolite incorporated sensors, including frequency measurements, optical and the entire gamut of electrochemical measurements. It is clear from the published literature that zeolites provide a route to enhance sensor performance, and it is expected that commercial manifestation of some of the approaches discussed here will take place. The future of zeolite-based sensors will continue to exploit its unique properties and use of other microporous frameworks, including metal organic frameworks. Zeolite composites with electronic materials, including metals will lead to new paradigms in sensing. Use of nano-sized zeolite crystals and zeolite membranes will enhance sensor properties and make possible new routes of miniaturized sensors. PMID:22666081

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Anesthesiology resident personality type correlates with faculty assessment of resident performance.

PubMed

Schell, Randall M; Dilorenzo, Amy N; Li, Hsin-Fang; Fragneto, Regina Y; Bowe, Edwin A; Hessel, Eugene A

2012-11-01

To study the association between anesthesiology residents' personality preference types, faculty evaluations of residents' performance, and knowledge. Convenience sample and prospective study. Academic department of anesthesiology. Consenting anesthesiology residents (n = 36). All participants completed the Myers Briggs Type Indicator® (MBTI®). All residents' 6-month summation of daily focal evaluations completed by faculty [daily performance score (DPS); 1 = unsatisfactory, 2 = needs improvement, 3 = meets expectations, 4 = exceeds expectations], as well as a global assessment of performance (GAP) score based on placement of each resident into perceived quartile compared with their peers (ie,1 = first, or top, quartile) by senior faculty (n = 7) who also completed the MBTI, were obtained. The resident MBTI personality preferences were compared with the DPS and GAP scores, the United States Medical Licensing Examination (USMLE) I and II scores, and faculty MBTI personality type. There was no association between personality preference type and performance on standardized examinations (USMLE I, II). The mean GAP score was better (higher quartile score) for Extraverts than Introverts (median 2.0 vs 2.6, P = 0.0047) and for Sensing versus Intuition (median 2.0 vs 2.6, P = 0.0206) preference. Faculty evaluator MBTI preference type did not influence the GAP scores they assigned residents. Like GAP, the DPS was better for residents with Sensing versus Intuition preference (median 3.5 vs 3.3, P = 0.0111). No difference in DPS was noted between Extraverts and Introverts. Personality preference type was not associated with resident performance on standardized examinations, but it was associated with faculty evaluations of resident performance. Residents with Sensing personality preference were evaluated more favorably on global and focal faculty evaluations than those residents who chose the Intuition preference. Extraverted residents were evaluated more favorably on global but not focal assessment of performance. Copyright © 2012 Elsevier Inc. All rights reserved.

Applying active learning to supervised word sense disambiguation in MEDLINE.

PubMed

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models.

Multi-material optoelectronic fiber devices

NASA Astrophysics Data System (ADS)

Sorin, F.; Yan, Wei; Volpi, Marco; Page, Alexis G.; Nguyen Dang, Tung; Qu, Y.

2017-05-01

The recent ability to integrate materials with different optical and optoelectronic properties in prescribed architectures within flexible fibers is enabling novel opportunities for advanced optical probes, functional surfaces and smart textiles. In particular, the thermal drawing process has known a series of breakthroughs in recent years that have expanded the range of materials and architectures that can be engineered within uniform fibers. Of particular interest in this presentation will be optoelectronic fibers that integrate semiconductors electrically addressed by conducting materials. These long, thin and flexible fibers can intercept optical radiation, localize and inform on a beam direction, detect its wavelength and even harness its energy. They hence constitute ideal candidates for applications such as remote and distributed sensing, large-area optical-detection arrays, energy harvesting and storage, innovative health care solutions, and functional fabrics. To improve performance and device complexity, tremendous progresses have been made in terms of the integrated semiconductor architectures, evolving from large fiber solid-core, to sub-hundred nanometer thin-films, nano-filaments and even nanospheres. To bridge the gap between the optoelectronic fiber concept and practical applications however, we still need to improve device performance and integration. In this presentation we will describe the materials and processing approaches to realize optoelectronic fibers, as well as give a few examples of demonstrated systems for imaging as well as light and chemical sensing. We will then discuss paths towards practical applications focusing on two main points: fiber connectivity, and improving the semiconductor microstructure by developing scalable approaches to make fiber-integrated single-crystal nanowire based devices.

Phase sensitive diffraction sensor for high sensitivity refractive index measurement

NASA Astrophysics Data System (ADS)

Kumawat, Nityanand; Varma, Manoj; Kumar, Sunil

2018-02-01

In this study a diffraction based sensor has been developed for bio molecular sensing applications and performing assays in real time. A diffraction grating fabricated on a glass substrate produced diffraction patterns both in transmission and reflection when illuminated by a laser diode. We used zeroth order I(0,0) as reference and first order I(0,1) as signal channel and conducted ratiometric measurements that reduced noise by more than 50 times. The ratiometric approach resulted in a very simple instrumentation with very high sensitivity. In the past, we have shown refractive index measurements both for bulk and surface adsorption using the diffractive self-referencing approach. In the current work we extend the same concept to higher diffraction orders. We have considered order I(0,1) and I(1,1) and performed ratiometric measurements I(0,1)/I(1,1) to eliminate the common mode fluctuations. Since orders I(0,1) and I(1,1) behaved opposite to each other, the resulting ratio signal amplitude increased more than twice compared to our previous results. As a proof of concept we used different salt concentrations in DI water. Increased signal amplitude and improved fluid injection system resulted in more than 4 times improvement in detection limit, giving limit of detection 1.3×10-7 refractive index unit (RIU) compared to our previous results. The improved refractive index sensitivity will help significantly for high sensitivity label free bio sensing application in a very cost-effective and simple experimental set-up.

Applying active learning to supervised word sense disambiguation in MEDLINE

PubMed Central

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

Objectives This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. Methods We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Results Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. Conclusions This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models. PMID:23364851

The design of high performance, low power triple-track magnetic sensor chip.

PubMed

Wu, Xiulong; Li, Minghua; Lin, Zhiting; Xi, Mengyuan; Chen, Junning

2013-07-09

This paper presents a design of a high performance and low power consumption triple-track magnetic sensor chip which was fabricated in TSMC 0.35 μm CMOS process. This chip is able to simultaneously sense, decode and read out the information stored in triple-track magnetic cards. A reference voltage generating circuit, a low-cost filter circuit, a power-on reset circuit, an RC oscillator, and a pre-decoding circuit are utilized as the basic modules. The triple-track magnetic sensor chip has four states, i.e., reset, sleep, swiping card and data read-out. In sleep state, the internal RC oscillator is closed, which means that the digital part does not operate to optimize energy consumption. In order to improve decoding accuracy and expand the sensing range of the signal, two kinds of circuit are put forward, naming offset correction circuit, and tracking circuit. With these two circuits, the sensing function of this chip can be more efficiently and accurately. We simulated these circuit modules with TSMC technology library. The results showed that these modules worked well within wide range input signal. Based on these results, the layout and tape-out were carried out. The measurement results showed that the chip do function well within a wide swipe speed range, which achieved the design target.

The Design of High Performance, Low Power Triple-Track Magnetic Sensor Chip

PubMed Central

Wu, Xiulong; Li, Minghua; Lin, Zhiting; Xi, Mengyuan; Chen, Junning

2013-01-01

This paper presents a design of a high performance and low power consumption triple-track magnetic sensor chip which was fabricated in TSMC 0.35 μm CMOS process. This chip is able to simultaneously sense, decode and read out the information stored in triple-track magnetic cards. A reference voltage generating circuit, a low-cost filter circuit, a power-on reset circuit, an RC oscillator, and a pre-decoding circuit are utilized as the basic modules. The triple-track magnetic sensor chip has four states, i.e., reset, sleep, swiping card and data read-out. In sleep state, the internal RC oscillator is closed, which means that the digital part does not operate to optimize energy consumption. In order to improve decoding accuracy and expand the sensing range of the signal, two kinds of circuit are put forward, naming offset correction circuit, and tracking circuit. With these two circuits, the sensing function of this chip can be more efficiently and accurately. We simulated these circuit modules with TSMC technology library. The results showed that these modules worked well within wide range input signal. Based on these results, the layout and tape-out were carried out. The measurement results showed that the chip do function well within a wide swipe speed range, which achieved the design target. PMID:23839231

A technology review of time-of-flight photon counting for advanced remote sensing

NASA Astrophysics Data System (ADS)

Lamb, Robert A.

2010-04-01

Time correlated single photon counting (TCSPC) has made tremendous progress during the past ten years enabling improved performance in precision time-of-flight (TOF) rangefinding and lidar. In this review the development and performance of several ranging systems is presented that use TCSPC for accurate ranging and range profiling over distances up to 17km. A range resolution of a few millimetres is routinely achieved over distances of several kilometres. These systems include single wavelength devices operating in the visible; multi-wavelength systems covering the visible and near infra-red; the use of electronic gating to reduce in-band solar background and, most recently, operation at high repetition rates without range aliasing- typically 10MHz over several kilometres. These systems operate at very low optical power (<100μW). The technique therefore has potential for eye-safe lidar monitoring of the environment and obvious military, security and surveillance sensing applications. The review will highlight the theoretical principles of photon counting and progress made in developing absolute ranging techniques that enable high repetition rate data acquisition that avoids range aliasing. Technology trends in TCSPC rangefinding are merging with those of quantum cryptography and its future application to revolutionary quantum imaging provides diverse and exciting research into secure covert sensing, ultra-low power active imaging and quantum rangefinding.

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

2003-04-01

At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

Palladium Gate All Around - Hetero Dielectric -Tunnel FET based highly sensitive Hydrogen Gas Sensor

NASA Astrophysics Data System (ADS)

Madan, Jaya; Chaujar, Rishu

2016-12-01

The paper presents a novel highly sensitive Hetero-Dielectric-Gate All Around Tunneling FET (HD-GAA-TFET) based Hydrogen Gas Sensor, incorporating the advantages of band to band tunneling (BTBT) mechanism. Here, the Palladium supported silicon dioxide is used as a sensing media and sensing relies on the interaction of hydrogen with Palladium-SiO2-Si. The high surface to volume ratio in the case of cylindrical GAA structure enhances the fortuities for surface reactions between H2 gas and Pd, and thus improves the sensitivity and stability of the sensor. Behaviour of the sensor in presence of hydrogen and at elevated temperatures is discussed. The conduction path of the sensor which is dependent on sensors radius has also been varied for the optimized sensitivity and static performance analysis of the sensor where the proposed design exhibits a superior performance in terms of threshold voltage, subthreshold swing, and band to band tunneling rate. Stability of the sensor with respect to temperature affectability has also been studied, and it is found that the device is reasonably stable and highly sensitive over the bearable temperature range. The successful utilization of HD-GAA-TFET in gas sensors may open a new door for the development of novel nanostructure gas sensing devices.

Contraction Sensing with Smart Braid McKibben Muscles

PubMed Central

Felt, Wyatt; Chin, Khai Yi; Remy, C. David

2016-01-01

The inherent compliance of soft fluidic actuators makes them attractive for use in wearable devices and soft robotics. Their flexible nature permits them to be used without traditional rotational or prismatic joints. Without these joints, however, measuring the motion of the actuators is challenging. Actuator-level sensors could improve the performance of continuum robots and robots with compliant or multi-degree-of-freedom joints. We make the reinforcing braid of a pneumatic artificial muscle (PAM or McKibben muscle) “smart” by weaving it from conductive, insulated wires. These wires form a solenoid-like circuit with an inductance that more than doubles over the PAM contraction. The reinforcing and sensing fibers can be used to measure the contraction of a PAM actuator with a simple, linear function of the measured inductance. Whereas other proposed self-sensing techniques rely on the addition of special elastomers or transducers, the technique presented in this work can be implemented without modifications of this kind. We present and experimentally validate two models for Smart Braid sensors based on the long solenoid approximation and the Neumann formula, respectively. We test a McKibben muscle made from a Smart Braid in quasistatic conditions with various end-loads and in dynamic conditions. We also test the performance of the Smart Braid sensor alongside steel. PMID:28503062

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

PubMed Central

Dinh, Thanh; Kim, Younghan

2016-01-01

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

Novel pH-sensitive photopolymer hydrogel and its holographic sensing response for solution characterization

NASA Astrophysics Data System (ADS)

Liu, Hongpeng; Yu, Dan; Zhou, Ke; Wang, Shichan; Luo, Suhua; Li, Li; Wang, Weibo; Song, Qinggong

2018-05-01

Optical sensor based on pH-sensitive hydrogel has important practical applications in medical diagnosis and bio-sensor areas. This report details the experimental and theoretical results from a novel photosensitive polymer hydrogel holographic sensor, which formed by thermal polymerization of 2-hydroxyethyl methacrylate, for the detection of pH in buffer. Volume grating recorded in the polymer hydrogel was employed in response to the performance of solution. Methacrylic acid with carboxyl groups was selected as the primary co-monomer to functionalize the matrix. Peak diffraction spectrum of holographic grating determined as a primary sensing parameter was characterized to reflect the change in pH. The extracted linear relation between peak wavelength and pH value provided a probability for the practical application of holographic sensor. To explore the sensing mechanism deeply, a theoretical model was used to describe the relevant holographic processes, including grating formation, dark diffusional enhancement, and final fringe swelling. Numerical result further showed all of the dynamic processes and internal sensing physical mechanism. These experimental and numerical results provided a significant foundation for the development of novel holographic sensor based on polymer hydrogel and improvement of its practical applicability.

Investigation on Smart Parts with Embedded Piezoelectric Sensors via Additive Manufacturing

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

Lin, Yirong

The goal of this proposed research is to design, fabricate, and evaluate “smart parts” with embedded sensors for energy systems. The “smart parts” will be fabricated using Electron Beam Melting (EBM) 3D printing technique with built-in piezoceramic sensors. The objectives of the proposed project are: 1) Fabricate energy system related components with embedded sensors, 2) Evaluate the mechanical properties and sensing functionalities of the “smart parts” with embedded piezoceramic sensors, and 3) Assess in-situ sensing capability of energy system parts. The second year’s research of the research is centered on fabrication of the “smart parts” with considerations of overall materialmore » property as well as demonstration of sensing functionalities. The results for the final report are presented here, including all research accomplishment, project management. Details are included such as: how the design and fabrication of sensor packaging could improve the sensor performance, demonstration of “smart parts” sensing capabilities, analysis on the elements that constitute the “smart sensors”, advanced “stop and go” fabrication process, smart injector fabrication using SLM technology, smart injector testing in combustion environments etc. Research results to date have generated several posters and papers.« less

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

PubMed

Dinh, Thanh; Kim, Younghan

2016-06-28

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

Magnetic resonance imaging-compatible tactile sensing device based on a piezoelectric array.

PubMed

Hamed, Abbi; Masamune, Ken; Tse, Zion Tsz Ho; Lamperth, Michael; Dohi, Takeyoshi

2012-07-01

Minimally invasive surgery is a widely used medical technique, one of the drawbacks of which is the loss of direct sense of touch during the operation. Palpation is the use of fingertips to explore and make fast assessments of tissue morphology. Although technologies are developed to equip minimally invasive surgery tools with haptic feedback capabilities, the majority focus on tissue stiffness profiling and tool-tissue interaction force measurement. For greatly increased diagnostic capability, a magnetic resonance imaging-compatible tactile sensor design is proposed, which allows minimally invasive surgery to be performed under image guidance, combining the strong capability of magnetic resonance imaging soft tissue and intuitive palpation. The sensing unit is based on a piezoelectric sensor methodology, which conforms to the stringent mechanical and electrical design requirements imposed by the magnetic resonance environment The sensor mechanical design and the device integration to a 0.2 Tesla open magnetic resonance imaging scanner are described, together with the device's magnetic resonance compatibility testing. Its design limitations and potential future improvements are also discussed. A tactile sensing unit based on a piezoelectric sensor principle is proposed, which is designed for magnetic resonance imaging guided interventions.

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction.

PubMed

Abdel-Sayed, Michael M; Khattab, Ahmed; Abu-Elyazeed, Mohamed F

2016-11-01

Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted [Formula: see text] minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal [Formula: see text] minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to [Formula: see text] minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

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.

Liquid-Solid Dual-Gate Organic Transistors with Tunable Threshold Voltage for Cell Sensing.

PubMed

Zhang, Yu; Li, Jun; Li, Rui; Sbircea, Dan-Tiberiu; Giovannitti, Alexander; Xu, Junling; Xu, Huihua; Zhou, Guodong; Bian, Liming; McCulloch, Iain; Zhao, Ni

2017-11-08

Liquid electrolyte-gated organic field effect transistors and organic electrochemical transistors have recently emerged as powerful technology platforms for sensing and simulation of living cells and organisms. For such applications, the transistors are operated at a gate voltage around or below 0.3 V because prolonged application of a higher voltage bias can lead to membrane rupturing and cell death. This constraint often prevents the operation of the transistors at their maximum transconductance or most sensitive regime. Here, we exploit a solid-liquid dual-gate organic transistor structure, where the threshold voltage of the liquid-gated conduction channel is controlled by an additional gate that is separated from the channel by a metal-oxide gate dielectric. With this design, the threshold voltage of the "sensing channel" can be linearly tuned in a voltage window exceeding 0.4 V. We have demonstrated that the dual-gate structure enables a much better sensor response to the detachment of human mesenchymal stem cells. In general, the capability of tuning the optimal sensing bias will not only improve the device performance but also broaden the material selection for cell-based organic bioelectronics.

Biosensing Using Microring Resonator Interferograms

PubMed Central

Hsu, Shih-Hsiang; Yang, Yung-Chia; Su, Yu-Hou; Wang, Sheng-Min; Huang, Shih-An; Lin, Ching-Yu

2014-01-01

Optical low-coherence interferometry (OLCI) takes advantage of the variation in refractive index in silicon-wire microring resonator (MRR) effective lengths to perform glucose biosensing using MRR interferograms. The MRR quality factor (Q), proportional to the effective length, could be improved using the silicon-wire propagation loss and coupling ratio from the MRR coupler. Our study showed that multimode interference (MMI) performed well in broad band response, but the splitting ratio drifted to 75/25 due to the stress issue. The glucose sensing sensitivity demonstrated 0.00279 meter per refractive-index-unit (RIU) with a Q factor of ∼30,000 under transverse electric polarization. The 1,310 nm DFB laser was built in the OLCI system as the optical ruler achieving 655 nm characterization accuracy. The lowest sensing limitation was therefore 2 × 10−4 RIU. Moreover, the MRR effective length from the glucose sensitivity could be utilized to experimentally demonstrate the silicon wire effective refractive index with a width of 0.45 μm and height of 0.26 μm. PMID:24434876

Preschoolers' precision of the approximate number system predicts later school mathematics performance.

PubMed

Mazzocco, Michèle M M; Feigenson, Lisa; Halberda, Justin

2011-01-01

The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities.

Electrostatically Levitated Ring-Shaped Rotational-Gyro/Accelerometer

NASA Astrophysics Data System (ADS)

Murakoshi, Takao; Endo, Yasuo; Fukatsu, Keisuke; Nakamura, Sigeru; Esashi, Masayoshi

2003-04-01

This paper reports an electrostatically levitated inertia measurement system which is based on the principle of a rotational gyro. The device has several advantages: the levitation of the rotor in a vacuum eliminates mechanical friction resulting in high sensitivity; the position control for the levitation allows accelerations to be sensed in the tri-axis; and the fabrication of the device by a micromachining technique has the cost advantages afforded by miniaturization. Latest measurements yield a noise floor of the gyro and that of the accelerometer as low as 0.15 deg/h1/2 and 30 μG/Hz1/2, respectively. This performance is achieved by a new sensor design. To further improve of the previous device, a ring-shaped structure is designed and fabricated by deep reactive ion etching using inductively coupled plasma. The rotor levitation is performed with capacitive detection and electrostatic actuation. Multiaxis closed-loop control is realized by differential capacitance sensing and frequency multiplying. The rotation of the micro gyro is based on the principle of a planar variable capacitance motor.

Preschoolers' Precision of the Approximate Number System Predicts Later School Mathematics Performance

PubMed Central

Mazzocco, Michèle M. M.; Feigenson, Lisa; Halberda, Justin

2011-01-01

The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities. PMID:21935362

Design and Evaluation of a Robust PID Controller for a Fully Implantable Artificial Pancreas

PubMed Central

2015-01-01

Treatment of type 1 diabetes mellitus could be greatly improved by applying a closed-loop control strategy to insulin delivery, also known as an artificial pancreas (AP). In this work, we outline the design of a fully implantable AP using intraperitoneal (IP) insulin delivery and glucose sensing. The design process utilizes the rapid glucose sensing and insulin action offered by the IP space to tune a PID controller with insulin feedback to provide safe and effective insulin delivery. The controller was tuned to meet robust performance and stability specifications. An anti-reset windup strategy was introduced to prevent dangerous undershoot toward hypoglycemia after a large meal disturbance. The final controller design achieved 78% of time within the tight glycemic range of 80–140 mg/dL, with no time spent in hypoglycemia. The next step is to test this controller design in an animal model to evaluate the in vivo performance. PMID:26538805

High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures

PubMed Central

Kim, Daehyun; Trzasko, Joshua; Smelyanskiy, Mikhail; Haider, Clifton; Dubey, Pradeep; Manduca, Armando

2011-01-01

Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However, the computationally intensive nature of CS reconstructions has precluded their use in routine clinical practice. In this work, we investigate how different throughput-oriented architectures can benefit one CS algorithm and what levels of acceleration are feasible on different modern platforms. We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. We then show that Intel's Knights Ferry can perform the same 3D MRI reconstruction in only 12 seconds, bringing CS methods even closer to clinical viability. PMID:21922017